wip?

server: add python tool parsing logic
2025-12-24 08:10:54 -05:00 · 2025-05-07 19:00:44 -07:00 · 2025-05-02 16:23:54 -07:00
521 changed files with 49033 additions and 312788 deletions
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -23,7 +23,7 @@ jobs:
          echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${GITHUB_REF_NAME#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_OUTPUT

  darwin-build:
-    runs-on: macos-13-xlarge
+    runs-on: macos-13
    environment: release
    needs: setup-environment
    strategy:
@@ -54,6 +54,48 @@ jobs:
          name: build-${{ matrix.os }}-${{ matrix.arch }}
          path: dist/*

+  darwin-sign:
+    runs-on: macos-13
+    environment: release
+    needs: darwin-build
+    steps:
+      - uses: actions/checkout@v4
+      - run: |
+          echo $MACOS_SIGNING_KEY | base64 --decode > certificate.p12
+          security create-keychain -p password build.keychain
+          security default-keychain -s build.keychain
+          security unlock-keychain -p password build.keychain
+          security import certificate.p12 -k build.keychain -P $MACOS_SIGNING_KEY_PASSWORD -T /usr/bin/codesign
+          security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k password build.keychain
+          security set-keychain-settings -lut 3600 build.keychain
+        env:
+          MACOS_SIGNING_KEY: ${{ secrets.MACOS_SIGNING_KEY }}
+          MACOS_SIGNING_KEY_PASSWORD: ${{ secrets.MACOS_SIGNING_KEY_PASSWORD }}
+      - uses: actions/download-artifact@v4
+        with:
+          name: build-darwin-amd64
+          path: dist/darwin-amd64
+      - uses: actions/download-artifact@v4
+        with:
+          name: build-darwin-arm64
+          path: dist/darwin-arm64
+      - run: |
+          export VERSION=${GITHUB_REF_NAME#v}
+          ./scripts/build_darwin.sh sign macapp
+        env:
+          APPLE_IDENTITY: ${{ secrets.APPLE_IDENTITY }}
+          APPLE_PASSWORD: ${{ secrets.APPLE_PASSWORD }}
+          APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
+          APPLE_ID: ${{ vars.APPLE_ID }}
+          SDKROOT: /Applications/Xcode_14.1.0.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
+          DEVELOPER_DIR: /Applications/Xcode_14.1.0.app/Contents/Developer
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-darwin
+          path: |
+            dist/Ollama-darwin.zip
+            dist/ollama-darwin.tgz
+
  windows-depends:
    strategy:
      matrix:
@@ -63,38 +105,19 @@ jobs:
        include:
          - os: windows
            arch: amd64
-            preset: 'CUDA 12'
-            install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-            cuda-version: '12.8'
-            flags: ''
-            runner_dir: 'cuda_v12'
+            preset: 'CUDA 11'
+            install: https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe
+            cuda-version: '11.3'
          - os: windows
            arch: amd64
-            preset: 'CUDA 13'
-            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-              - '"crt"'
-              - '"nvvm"'
-              - '"nvptxcompiler"'
-            cuda-version: '13.0'
-            flags: ''
-            runner_dir: 'cuda_v13'
+            preset: 'CUDA 12'
+            install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
+            cuda-version: '12.8'
          - os: windows
            arch: amd64
            preset: 'ROCm 6'
            install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
            rocm-version: '6.2'
-            flags: '-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
-            runner_dir: ''
    runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
    environment: release
    env:
@@ -118,7 +141,7 @@ jobs:
          $ErrorActionPreference = "Stop"
          if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
            Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
+            $subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
            Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
          }

@@ -137,9 +160,6 @@ jobs:
          echo "$hipPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
          echo "CC=$hipPath\bin\clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
          echo "CXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIPCXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIP_PLATFORM=amd" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "CMAKE_PREFIX_PATH=$hipPath" | Out-File -FilePath $env:GITHUB_ENV -Append
      - if: matrix.preset == 'CPU'
        run: |
          echo "CC=clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
@@ -158,9 +178,9 @@ jobs:
          key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
      - name: Build target "${{ matrix.preset }}"
        run: |
-          Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
-          Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
-          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }} -DOLLAMA_RUNNER_DIR="${{ matrix.runner_dir }}"
+          Import-Module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
+          Enter-VsDevShell -VsInstallPath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
+          cmake --preset "${{ matrix.preset }}"
          cmake --build --parallel --preset "${{ matrix.preset }}"
          cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || 'CPU' }}" --strip --parallel 8
        env:
@@ -210,11 +230,61 @@ jobs:
          go-version-file: go.mod
      - run: |
          go build -o dist/${{ matrix.os }}-${{ matrix.arch }}/ .
+      - if: matrix.arch == 'arm64'
+        run: |
+          Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vc_redist.arm64.exe" -OutFile "dist\windows-arm64\vc_redist.arm64.exe"
+      - run: |
+          $env:VERSION='${{ github.ref_name }}' -Replace "v(.*)", '$1'
+          & .\scripts\build_windows.ps1 buildApp
+        env:
+          VCToolsRedistDir: stub
      - uses: actions/upload-artifact@v4
        with:
          name: build-${{ matrix.os }}-${{ matrix.arch }}
          path: |
            dist\${{ matrix.os }}-${{ matrix.arch }}\*.exe
+            dist\${{ matrix.os }}-${{ matrix.arch }}-app.exe
+
+  windows-sign:
+    runs-on: windows-2022
+    environment: release
+    needs: [windows-depends, windows-build]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: google-github-actions/auth@v2
+        with:
+          project_id: ollama
+          credentials_json: ${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}
+      - run: |
+          $ErrorActionPreference = "Stop"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${{ runner.temp }}\sdksetup.exe"
+          Start-Process "${{ runner.temp }}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${{ runner.temp }}\plugin.zip"
+          Expand-Archive -Path "${{ runner.temp }}\plugin.zip" -DestinationPath "${{ runner.temp }}\plugin\"
+          & "${{ runner.temp }}\plugin\*\kmscng.msi" /quiet
+
+          echo "${{ vars.OLLAMA_CERT }}" >ollama_inc.crt
+      - uses: actions/download-artifact@v4
+        with:
+          pattern: build-windows-*
+          path: dist\
+          merge-multiple: true
+      - uses: actions/download-artifact@v4
+        with:
+          pattern: depends-windows-amd64-*
+          path: dist\windows-amd64\
+          merge-multiple: true
+      - run: |
+          & .\scripts\build_windows.ps1 gatherDependencies sign buildInstaller distZip
+        env:
+          KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-windows
+          path: |
+            dist\OllamaSetup.exe
+            dist\ollama-windows-*.zip

  linux-build:
    strategy:
@@ -247,26 +317,21 @@ jobs:
            CGO_CFLAGS=${{ env.CGO_CFLAGS }}
            CGO_CXXFLAGS=${{ env.CGO_CXXFLAGS }}
          outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
-          cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
+          cache-from: type=registry,ref=ollama/ollama:latest
          cache-to: type=inline
      - run: |
          for COMPONENT in bin/* lib/ollama/*; do
            case "$COMPONENT" in
-              bin/ollama)                echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/*.so*)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/cuda_v*)        echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/cuda_jetpack5)  echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
-              lib/ollama/cuda_jetpack6)  echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
-              lib/ollama/rocm)           echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
+              bin/ollama)               echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
+              lib/ollama/*.so)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
+              lib/ollama/cuda_v11)      echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
+              lib/ollama/cuda_v12)      echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
+              lib/ollama/cuda_jetpack5) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
+              lib/ollama/cuda_jetpack6) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
+              lib/ollama/rocm)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
            esac
          done
        working-directory: dist/${{ matrix.os }}-${{ matrix.arch }}
-      - run: |
-          echo "Manifests"
-          for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in ; do
-            echo $ARCHIVE
-            cat $ARCHIVE
-          done
      - run: |
          for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in; do
            tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | pigz -9vc >$(basename ${ARCHIVE//.*/}.tgz);
@@ -320,8 +385,8 @@ jobs:
          context: .
          platforms: ${{ matrix.os }}/${{ matrix.arch }}
          build-args: ${{ matrix.build-args }}
-          outputs: type=image,name=${{ vars.DOCKER_REPO }},push-by-digest=true,name-canonical=true,push=true
-          cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
+          outputs: type=image,name=ollama/ollama,push-by-digest=true,name-canonical=true,push=true
+          cache-from: type=registry,ref=ollama/ollama:latest
          cache-to: type=inline
      - run: |
          mkdir -p ${{ matrix.os }}-${{ matrix.arch }}
@@ -353,7 +418,7 @@ jobs:
            latest=false
            suffix=${{ matrix.suffix }}
          images: |
-            ${{ vars.DOCKER_REPO }}
+            ollama/ollama
          tags: |
            type=ref,enable=true,priority=600,prefix=pr-,event=pr
            type=semver,pattern={{version}}
@@ -363,24 +428,40 @@ jobs:
          path: ${{ runner.temp }}
          merge-multiple: true
      - run: |
-          docker buildx imagetools create $(echo '${{ steps.metadata.outputs.json }}' | jq -cr '.tags | map("-t", .) | join(" ")') $(cat *-${{ matrix.suffix }}.txt | xargs printf '${{ vars.DOCKER_REPO }}@%s ')
-          docker buildx imagetools inspect ${{ vars.DOCKER_REPO }}:${{ steps.metadata.outputs.version }}
+          docker buildx imagetools create $(echo '${{ steps.metadata.outputs.json }}' | jq -cr '.tags | map("-t", .) | join(" ")') $(cat *-${{ matrix.suffix }}.txt | xargs printf 'ollama/ollama@%s ')
+          docker buildx imagetools inspect ollama/ollama:${{ steps.metadata.outputs.version }}
        working-directory: ${{ runner.temp }}

-  # Trigger downstream release process
-  trigger:
-    runs-on: ubuntu-latest
+  # Aggregate all the assets and ship a release
+  release:
+    needs: [darwin-sign, windows-sign, linux-build]
+    runs-on: linux
    environment: release
-    needs: [darwin-build, windows-build, windows-depends, linux-build]
    permissions:
      contents: write
    env:
      GH_TOKEN: ${{ github.token }}
    steps:
      - uses: actions/checkout@v4
-      - name: Create or update Release for tag
+      - uses: actions/download-artifact@v4
+        with:
+          name: dist-darwin
+          path: dist
+      - uses: actions/download-artifact@v4
+        with:
+          name: dist-windows
+          path: dist
+      - uses: actions/download-artifact@v4
+        with:
+          pattern: dist-linux-*
+          path: dist
+          merge-multiple: true
+      - run: find . -type f -not -name 'sha256sum.txt' | xargs sha256sum | tee sha256sum.txt
+        working-directory: dist
+      - name: Create or update Release
        run: |
          RELEASE_VERSION="$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)"
+
          echo "Looking for existing release for ${RELEASE_VERSION}"
          OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${RELEASE_VERSION}\") | .tagName")
          if [ -n "$OLD_TAG" ]; then
@@ -394,12 +475,5 @@ jobs:
              --generate-notes \
              --prerelease
          fi
-      - name: Trigger downstream release process
-        run: |
-          curl -L \
-            -X POST \
-            -H "Accept: application/vnd.github+json" \
-            -H "Authorization: Bearer ${{ secrets.RELEASE_TOKEN }}" \
-            -H "X-GitHub-Api-Version: 2022-11-28" \
-            https://api.github.com/repos/ollama/${{ vars.RELEASE_REPO }}/dispatches \
-            -d "{\"event_type\": \"trigger-workflow\", \"client_payload\": {\"run_id\": \"${GITHUB_RUN_ID}\", \"version\": \"${GITHUB_REF_NAME#v}\", \"origin\": \"${GITHUB_REPOSITORY}\", \"publish\": \"1\"}}"
+          echo "Uploading artifacts for tag ${GITHUB_REF_NAME}"
+          gh release upload ${GITHUB_REF_NAME} dist/* --clobber
--- a/.github/workflows/test.yaml
+++ b/.github/workflows/test.yaml
@@ -36,7 +36,7 @@ jobs:
              | xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
          }

-          echo changed=$(changed 'llama/llama.cpp/**/*' 'ml/backend/ggml/ggml/**/*') | tee -a $GITHUB_OUTPUT
+          echo changed=$(changed 'llama/llama.cpp/**' 'ml/backend/ggml/ggml/**') | tee -a $GITHUB_OUTPUT

  linux:
    needs: [changes]
@@ -46,7 +46,7 @@ jobs:
        include:
          - preset: CPU
          - preset: CUDA
-            container: nvidia/cuda:13.0.0-devel-ubuntu22.04
+            container: nvidia/cuda:11.8.0-devel-ubuntu22.04
            flags: '-DCMAKE_CUDA_ARCHITECTURES=87'
          - preset: ROCm
            container: rocm/dev-ubuntu-22.04:6.1.2
@@ -78,20 +78,11 @@ jobs:
        include:
          - preset: CPU
          - preset: CUDA
-            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
+            install: https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe
            flags: '-DCMAKE_CUDA_ARCHITECTURES=80'
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-              - '"crt"'
-              - '"nvvm"'
-              - '"nvptxcompiler"'
-            cuda-version: '13.0'
          - preset: ROCm
            install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
-            flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
+            flags: '-DAMDGPU_TARGETS=gfx1010'
    runs-on: windows
    steps:
      - run: |
@@ -111,8 +102,7 @@ jobs:
          $ErrorActionPreference = "Stop"
          if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
            Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
-            Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
+            Start-Process -FilePath .\install.exe -ArgumentList (@("-s", "cudart_11.3", "nvcc_11.3", "cublas_11.3", "cublas_dev_11.3")) -NoNewWindow -Wait
          }

          $cudaPath = (Resolve-Path "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*").path
@@ -130,9 +120,6 @@ jobs:
          echo "$hipPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
          echo "CC=$hipPath\bin\clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
          echo "CXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIPCXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIP_PLATFORM=amd" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "CMAKE_PREFIX_PATH=$hipPath" | Out-File -FilePath $env:GITHUB_ENV -Append
      - if: ${{ !cancelled() && steps.cache-install.outputs.cache-hit != 'true' }}
        uses: actions/cache/save@v4
        with:
@@ -146,8 +133,8 @@ jobs:
          path: ${{ github.workspace }}\.ccache
          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}
      - run: |
-          Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
-          Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
+          Import-Module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
+          Enter-VsDevShell -VsInstallPath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }}
          cmake --build --parallel --preset "${{ matrix.preset }}"
        env:
--- a/.gitignore
+++ b/.gitignore
@@ -6,7 +6,6 @@
 dist
 build
 .cache
-.gocache
 *.exe
 .idea
 test_data
--- a/.golangci.yaml
+++ b/.golangci.yaml
@@ -19,8 +19,8 @@ linters:
    - nolintlint
    - nosprintfhostport
    - staticcheck
+    - tenv
    - unconvert
-    - usetesting
    - wastedassign
    - whitespace
  disable:
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -3,7 +3,6 @@ cmake_minimum_required(VERSION 3.21)
 project(Ollama C CXX)

 include(CheckLanguage)
-include(GNUInstallDirs)

 find_package(Threads REQUIRED)

@@ -38,7 +37,7 @@ if (CMAKE_OSX_ARCHITECTURES MATCHES "x86_64")
 endif()

 set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
-set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama/${OLLAMA_RUNNER_DIR})
+set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama)

 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY         ${OLLAMA_BUILD_DIR})
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG   ${OLLAMA_BUILD_DIR})
@@ -52,8 +51,6 @@ include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/include
 include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu)
 include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu/amx)

-add_compile_definitions(NDEBUG GGML_VERSION=0x0 GGML_COMMIT=0x0)
-
 set(GGML_CPU ON)
 add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
 set_property(TARGET ggml PROPERTY EXCLUDE_FROM_ALL TRUE)
@@ -79,13 +76,14 @@ if(CMAKE_CUDA_COMPILER)

    find_package(CUDAToolkit)
    add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
+    set(OLLAMA_CUDA_INSTALL_DIR ${OLLAMA_INSTALL_DIR}/cuda_v${CUDAToolkit_VERSION_MAJOR})
    install(TARGETS ggml-cuda
        RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
+            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_LIBRARY_DIR}
            PRE_INCLUDE_REGEXES cublas cublasLt cudart
            PRE_EXCLUDE_REGEXES ".*"
-        RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
-        LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
+        RUNTIME DESTINATION ${OLLAMA_CUDA_INSTALL_DIR} COMPONENT CUDA
+        LIBRARY DESTINATION ${OLLAMA_CUDA_INSTALL_DIR} COMPONENT CUDA
    )
 endif()

@@ -116,11 +114,7 @@ if(CMAKE_HIP_COMPILER)

        set(OLLAMA_HIP_INSTALL_DIR ${OLLAMA_INSTALL_DIR}/rocm)
        install(TARGETS ggml-hip
-            RUNTIME_DEPENDENCY_SET rocm
-            RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
-            LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
-        )
-        install(RUNTIME_DEPENDENCY_SET rocm
+            RUNTIME_DEPENDENCIES
                DIRECTORIES ${HIP_BIN_INSTALL_DIR} ${HIP_LIB_INSTALL_DIR}
                PRE_INCLUDE_REGEXES hipblas rocblas amdhip64 rocsolver amd_comgr hsa-runtime64 rocsparse tinfo rocprofiler-register drm drm_amdgpu numa elf
                PRE_EXCLUDE_REGEXES ".*"
--- a/CMakePresets.json
+++ b/CMakePresets.json
@@ -6,8 +6,7 @@
      "binaryDir": "${sourceDir}/build",
      "installDir": "${sourceDir}/dist",
      "cacheVariables": {
-        "CMAKE_BUILD_TYPE": "Release",
-        "CMAKE_MSVC_RUNTIME_LIBRARY": "MultiThreaded"
+        "CMAKE_BUILD_TYPE": "Release"
      }
    },
    {
@@ -22,8 +21,8 @@
      "name": "CUDA 11",
      "inherits": [ "CUDA" ],
      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50-virtual;60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual",
-        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
+        "CMAKE_CUDA_ARCHITECTURES": "50;52;53;60;61;70;75;80;86",
+        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets"
      }
    },
    {
@@ -31,15 +30,7 @@
      "inherits": [ "CUDA" ],
      "cacheVariables": {
        "CMAKE_CUDA_ARCHITECTURES": "50;60;61;70;75;80;86;87;89;90;90a;120",
-        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
-      }
-    },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;110-virtual;120-virtual;121-virtual",
-        "CMAKE_CUDA_FLAGS": "-t 2"
+        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets"
      }
    },
    {
@@ -67,7 +58,6 @@
      "name": "ROCm 6",
      "inherits": [ "ROCm" ],
      "cacheVariables": {
-        "CMAKE_HIP_FLAGS": "-parallel-jobs=4",
        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1200;gfx1201;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
      }
    }
@@ -98,11 +88,6 @@
      "inherits": [ "CUDA" ],
      "configurePreset": "CUDA 12"
    },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 13"
-    },
    {
      "name": "JetPack 5",
      "inherits": [ "CUDA" ],
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -65,8 +65,7 @@ continuation of the sentence:
 Examples:

      llm/backend/mlx: support the llama architecture
-      CONTRIBUTING: provide clarity on good commit messages, and bad
-      docs: simplify manual installation with shorter curl commands
+      CONTRIBUTING: provide clairity on good commit messages, and bad

 Bad Examples:

--- a/72
+++ b/72
@@ -1,20 +1,18 @@
 # vim: filetype=dockerfile

 ARG FLAVOR=${TARGETARCH}
-ARG PARALLEL=8

 ARG ROCMVERSION=6.3.3
 ARG JETPACK5VERSION=r35.4.1
 ARG JETPACK6VERSION=r36.4.0
 ARG CMAKEVERSION=3.31.2

-# We require gcc v10 minimum.  v10.3 has regressions, so the rockylinux 8.5 AppStream has the latest compatible version
+# CUDA v11 requires gcc v10.  v10.3 has regressions, so the rockylinux 8.5 AppStream has the latest compatible version
 FROM --platform=linux/amd64 rocm/dev-almalinux-8:${ROCMVERSION}-complete AS base-amd64
 RUN yum install -y yum-utils \
    && yum-config-manager --add-repo https://dl.rockylinux.org/vault/rocky/8.5/AppStream/\$basearch/os/ \
    && rpm --import https://dl.rockylinux.org/pub/rocky/RPM-GPG-KEY-Rocky-8 \
    && dnf install -y yum-utils ccache gcc-toolset-10-gcc-10.2.1-8.2.el8 gcc-toolset-10-gcc-c++-10.2.1-8.2.el8 gcc-toolset-10-binutils-2.35-11.el8 \
-    && dnf install -y ccache \
    && yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
 ENV PATH=/opt/rh/gcc-toolset-10/root/usr/bin:$PATH

@@ -35,51 +33,35 @@ ENV LDFLAGS=-s
 FROM base AS cpu
 RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++
 ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
    cmake --preset 'CPU' \
-        && cmake --build --parallel ${PARALLEL} --preset 'CPU' \
-        && cmake --install build --component CPU --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'CPU' \
+        && cmake --install build --component CPU --strip --parallel 8

 FROM base AS cuda-11
-ARG CUDA11VERSION=11.8
+ARG CUDA11VERSION=11.3
 RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-}
 ENV PATH=/usr/local/cuda-11/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 11' -DOLLAMA_RUNNER_DIR="cuda_v11" \
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 11' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+    cmake --preset 'CUDA 11' \
+        && cmake --build --parallel --preset 'CUDA 11' \
+        && cmake --install build --component CUDA --strip --parallel 8

 FROM base AS cuda-12
 ARG CUDA12VERSION=12.8
 RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-}
 ENV PATH=/usr/local/cuda-12/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 12' -DOLLAMA_RUNNER_DIR="cuda_v12"\
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 12' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
-
-
-FROM base AS cuda-13
-ARG CUDA13VERSION=13.0
-RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-}
-ENV PATH=/usr/local/cuda-13/bin:$PATH
-ARG PARALLEL
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 13' -DOLLAMA_RUNNER_DIR="cuda_v13" \
-        && cmake --build --parallel ${PARALLEL} --preset 'CUDA 13' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
-
+    cmake --preset 'CUDA 12' \
+        && cmake --build --parallel --preset 'CUDA 12' \
+        && cmake --install build --component CUDA --strip --parallel 8

 FROM base AS rocm-6
 ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
    cmake --preset 'ROCm 6' \
-        && cmake --build --parallel ${PARALLEL} --preset 'ROCm 6' \
-        && cmake --install build --component HIP --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'ROCm 6' \
+        && cmake --install build --component HIP --strip --parallel 8

 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
 ARG CMAKEVERSION
@@ -87,11 +69,10 @@ RUN apt-get update && apt-get install -y curl ccache \
    && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
 COPY CMakeLists.txt CMakePresets.json .
 COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
    cmake --preset 'JetPack 5' \
-        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 5' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'JetPack 5' \
+        && cmake --install build --component CUDA --strip --parallel 8

 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
 ARG CMAKEVERSION
@@ -99,11 +80,10 @@ RUN apt-get update && apt-get install -y curl ccache \
    && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
 COPY CMakeLists.txt CMakePresets.json .
 COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-ARG PARALLEL
 RUN --mount=type=cache,target=/root/.ccache \
    cmake --preset 'JetPack 6' \
-        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 6' \
-        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
+        && cmake --build --parallel --preset 'JetPack 6' \
+        && cmake --install build --component CUDA --strip --parallel 8

 FROM base AS build
 WORKDIR /go/src/github.com/ollama/ollama
@@ -114,31 +94,27 @@ RUN go mod download
 COPY . .
 ARG GOFLAGS="'-ldflags=-w -s'"
 ENV CGO_ENABLED=1
-ARG CGO_CFLAGS
-ARG CGO_CXXFLAGS
 RUN --mount=type=cache,target=/root/.cache/go-build \
    go build -trimpath -buildmode=pie -o /bin/ollama .

 FROM --platform=linux/amd64 scratch AS amd64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
+COPY --from=cuda-11 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_v11
+COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12

 FROM --platform=linux/arm64 scratch AS arm64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
-COPY --from=jetpack-5 dist/lib/ollama /lib/ollama/cuda_jetpack5
-COPY --from=jetpack-6 dist/lib/ollama /lib/ollama/cuda_jetpack6
+COPY --from=cuda-11 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_v11
+COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12
+COPY --from=jetpack-5 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_jetpack5
+COPY --from=jetpack-6 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_jetpack6

 FROM scratch AS rocm
-COPY --from=rocm-6 dist/lib/ollama /lib/ollama
+COPY --from=rocm-6 dist/lib/ollama/rocm /lib/ollama/rocm

 FROM ${FLAVOR} AS archive
 COPY --from=cpu dist/lib/ollama /lib/ollama
 COPY --from=build /bin/ollama /bin/ollama

-FROM ubuntu:24.04
+FROM ubuntu:20.04
 RUN apt-get update \
    && apt-get install -y ca-certificates \
    && apt-get clean \
--- a/Makefile.sync
+++ b/Makefile.sync
@@ -1,6 +1,6 @@
-UPSTREAM=https://github.com/ggml-org/llama.cpp.git
+UPSTREAM=https://github.com/ggerganov/llama.cpp.git
 WORKDIR=llama/vendor
-FETCH_HEAD=e54d41befcc1575f4c898c5ff4ef43970cead75f
+FETCH_HEAD=2016f07bd106c73699ecbaace80f55db5ed95dac

 .PHONY: help
 help:
@@ -12,42 +12,31 @@ help:
 	@echo "    clean                Clean local repository"
 	@echo
 	@echo "Example:"
-	@echo "    make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches sync"
+	@echo "    make -f $(lastword $(MAKEFILE_LIST)) clean sync"

 .PHONY: sync
-sync: llama/build-info.cpp ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
+sync: llama/build-info.cpp llama/llama.cpp ml/backend/ggml/ggml

-llama/build-info.cpp: llama/build-info.cpp.in llama/llama.cpp
-	sed -e 's|@FETCH_HEAD@|$(FETCH_HEAD)|' <$< >$@
-
-ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal: ml/backend/ggml/ggml
-	go generate ./$(@D)
+.PHONY: llama/build-info.cpp
+llama/build-info.cpp: llama/build-info.cpp.in
+	sed -e 's|@FETCH_HEAD@|$(FETCH_HEAD)|' $< > $@

 .PHONY: llama/llama.cpp
-llama/llama.cpp: llama/vendor
-	rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /) $@
+llama/llama.cpp: llama/vendor/
+	rsync -arvzc -f "merge $@/.rsync-filter" $< $@

 .PHONY: ml/backend/ggml/ggml
-ml/backend/ggml/ggml: llama/vendor
-	rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /ggml/) $@
+ml/backend/ggml/ggml: llama/vendor/ggml/
+	rsync -arvzc -f "merge $@/.rsync-filter" $< $@

 PATCHES=$(wildcard llama/patches/*.patch)
-PATCHED=$(join $(dir $(PATCHES)), $(addsuffix ed, $(addprefix ., $(notdir $(PATCHES)))))

 .PHONY: apply-patches
 .NOTPARALLEL:
-apply-patches: $(PATCHED)
+apply-patches: $(addsuffix ed, $(PATCHES))

-llama/patches/.%.patched: llama/patches/%.patch
-	@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then \
-		touch $@;                                                                           \
-	else                                                                                    \
-		echo "Patch failed. Resolve any conflicts then continue.";                          \
-		echo "1. Run 'git -C $(WORKDIR) am --continue'";                                    \
-		echo "2. Run 'make -f $(lastword $(MAKEFILE_LIST)) format-patches'";                \
-		echo "3. Run 'make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches'";           \
-		exit 1;                                                                             \
-	fi
+%.patched: %.patch
+	@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then touch $@; else git -C $(WORKDIR) am --abort; exit 1; fi

 .PHONY: checkout
 checkout: $(WORKDIR)
@@ -68,5 +57,4 @@ format-patches: llama/patches

 .PHONE: clean
 clean: checkout
-	@git -C $(WORKDIR) am --abort || true
-	$(RM) llama/patches/.*.patched
+	$(RM) $(addsuffix ed, $(PATCHES))
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 <div align="center">
   <a href="https://ollama.com">
-    <img alt="ollama" width="240" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
+    <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
  </a>
 </div>

@@ -10,7 +10,7 @@ Get up and running with large language models.

 ### macOS

-[Download](https://ollama.com/download/Ollama.dmg)
+[Download](https://ollama.com/download/Ollama-darwin.zip)

 ### Windows

@@ -40,10 +40,10 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla

 ## Quickstart

-To run and chat with [Gemma 3](https://ollama.com/library/gemma3):
+To run and chat with [Llama 3.2](https://ollama.com/library/llama3.2):

 ```shell
-ollama run gemma3
+ollama run llama3.2
 ```

 ## Model library
@@ -61,8 +61,6 @@ Here are some example models that can be downloaded:
 | QwQ                | 32B        | 20GB  | `ollama run qwq`                 |
 | DeepSeek-R1        | 7B         | 4.7GB | `ollama run deepseek-r1`         |
 | DeepSeek-R1        | 671B       | 404GB | `ollama run deepseek-r1:671b`    |
-| Llama 4            | 109B       | 67GB  | `ollama run llama4:scout`        |
-| Llama 4            | 400B       | 245GB | `ollama run llama4:maverick`     |
 | Llama 3.3          | 70B        | 43GB  | `ollama run llama3.3`            |
 | Llama 3.2          | 3B         | 2.0GB | `ollama run llama3.2`            |
 | Llama 3.2          | 1B         | 1.3GB | `ollama run llama3.2:1b`         |
@@ -79,7 +77,7 @@ Here are some example models that can be downloaded:
 | Code Llama         | 7B         | 3.8GB | `ollama run codellama`           |
 | Llama 2 Uncensored | 7B         | 3.8GB | `ollama run llama2-uncensored`   |
 | LLaVA              | 7B         | 4.5GB | `ollama run llava`               |
-| Granite-3.3         | 8B         | 4.9GB | `ollama run granite3.3`          |
+| Granite-3.2         | 8B         | 4.9GB | `ollama run granite3.2`          |

 > [!NOTE]
 > You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
@@ -287,7 +285,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
 - [Saddle](https://github.com/jikkuatwork/saddle)
- [TagSpaces](https://www.tagspaces.org) (A platform for file-based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
+- [TagSpaces](https://www.tagspaces.org) (A platform for file based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
 - [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
@@ -314,8 +312,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat)
 - [Ollama-chats RPG](https://github.com/drazdra/ollama-chats)
 - [IntelliBar](https://intellibar.app/) (AI-powered assistant for macOS)
- [Jirapt](https://github.com/AliAhmedNada/jirapt) (Jira Integration to generate issues, tasks, epics)
- [ojira](https://github.com/AliAhmedNada/ojira) (Jira chrome plugin to easily generate descriptions for tasks)
 - [QA-Pilot](https://github.com/reid41/QA-Pilot) (Interactive chat tool that can leverage Ollama models for rapid understanding and navigation of GitHub code repositories)
 - [ChatOllama](https://github.com/sugarforever/chat-ollama) (Open Source Chatbot based on Ollama with Knowledge Bases)
 - [CRAG Ollama Chat](https://github.com/Nagi-ovo/CRAG-Ollama-Chat) (Simple Web Search with Corrective RAG)
@@ -329,14 +325,14 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
 - [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models)
 - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support, and multiple large language models.)
+- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support and multiple large language models.)
 - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
 - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
 - [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG)
- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in Discord)
+- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in discord )
 - [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
 - [R2R](https://github.com/SciPhi-AI/R2R) (Open-source RAG engine)
- [Ollama-Kis](https://github.com/elearningshow/ollama-kis) (A simple easy-to-use GUI with sample custom LLM for Drivers Education)
+- [Ollama-Kis](https://github.com/elearningshow/ollama-kis) (A simple easy to use GUI with sample custom LLM for Drivers Education)
 - [OpenGPA](https://opengpa.org) (Open-source offline-first Enterprise Agentic Application)
 - [Painting Droid](https://github.com/mateuszmigas/painting-droid) (Painting app with AI integrations)
 - [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
@@ -345,22 +341,22 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows)
 - [BoltAI for Mac](https://boltai.com) (AI Chat Client for Mac)
 - [Harbor](https://github.com/av/harbor) (Containerized LLM Toolkit with Ollama as default backend)
- [PyGPT](https://github.com/szczyglis-dev/py-gpt) (AI desktop assistant for Linux, Windows, and Mac)
- [Alpaca](https://github.com/Jeffser/Alpaca) (An Ollama client application for Linux and macOS made with GTK4 and Adwaita)
+- [PyGPT](https://github.com/szczyglis-dev/py-gpt) (AI desktop assistant for Linux, Windows and Mac)
+- [Alpaca](https://github.com/Jeffser/Alpaca) (An Ollama client application for linux and macos made with GTK4 and Adwaita)
 - [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT/blob/master/docs/content/platform/ollama.md) (AutoGPT Ollama integration)
 - [Go-CREW](https://www.jonathanhecl.com/go-crew/) (Powerful Offline RAG in Golang)
 - [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery)
- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j
+- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot and Ollama4j
 - [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
 - [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VSCode extension for multi-file/whole-repo coding
 - [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support)
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
+- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
 - [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library)
 - [crewAI with Mesop](https://github.com/rapidarchitect/ollama-crew-mesop) (Mesop Web Interface to run crewAI with Ollama)
 - [Tkinter-based client](https://github.com/chyok/ollama-gui) (Python tkinter-based Client for Ollama)
 - [LLMChat](https://github.com/trendy-design/llmchat) (Privacy focused, 100% local, intuitive all-in-one chat interface)
 - [Local Multimodal AI Chat](https://github.com/Leon-Sander/Local-Multimodal-AI-Chat) (Ollama-based LLM Chat with support for multiple features, including PDF RAG, voice chat, image-based interactions, and integration with OpenAI.)
- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG and deep research on Mac/Windows/Linux)
+- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG on Mac/Windows/Linux)
 - [OrionChat](https://github.com/EliasPereirah/OrionChat) - OrionChat is a web interface for chatting with different AI providers
 - [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.)
 - [Web management](https://github.com/lemonit-eric-mao/ollama-web-management) (Web management page)
@@ -372,7 +368,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [DualMind](https://github.com/tcsenpai/dualmind) (Experimental app allowing two models to talk to each other in the terminal or in a web interface)
 - [ollamarama-matrix](https://github.com/h1ddenpr0cess20/ollamarama-matrix) (Ollama chatbot for the Matrix chat protocol)
 - [ollama-chat-app](https://github.com/anan1213095357/ollama-chat-app) (Flutter-based chat app)
- [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard, and said in the meetings)
+- [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard and said in the meetings)
 - [Hexabot](https://github.com/hexastack/hexabot) (A conversational AI builder)
 - [Reddit Rate](https://github.com/rapidarchitect/reddit_analyzer) (Search and Rate Reddit topics with a weighted summation)
 - [OpenTalkGpt](https://github.com/adarshM84/OpenTalkGpt) (Chrome Extension to manage open-source models supported by Ollama, create custom models, and chat with models from a user-friendly UI)
@@ -390,7 +386,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [ChibiChat](https://github.com/CosmicEventHorizon/ChibiChat) (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints)
 - [LocalLLM](https://github.com/qusaismael/localllm) (Minimal Web-App to run ollama models on it with a GUI)
 - [Ollamazing](https://github.com/buiducnhat/ollamazing) (Web extension to run Ollama models)
- [OpenDeepResearcher-via-searxng](https://github.com/benhaotang/OpenDeepResearcher-via-searxng) (A Deep Research equivalent endpoint with Ollama support for running locally)
+- [OpenDeepResearcher-via-searxng](https://github.com/benhaotang/OpenDeepResearcher-via-searxng) (A Deep Research equivent endpoint with Ollama support for running locally)
 - [AntSK](https://github.com/AIDotNet/AntSK) (Out-of-the-box & Adaptable RAG Chatbot)
 - [MaxKB](https://github.com/1Panel-dev/MaxKB/) (Ready-to-use & flexible RAG Chatbot)
 - [yla](https://github.com/danielekp/yla) (Web interface to freely interact with your customized models)
@@ -398,23 +394,11 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool)
 - [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
- [Flufy](https://github.com/Aharon-Bensadoun/Flufy) (A beautiful chat interface for interacting with Ollama's API. Built with React, TypeScript, and Material-UI.)
 - [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
 - [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
 - [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
 - [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama)
 - [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable)
- [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers)
- [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.) 
- [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
- [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
- [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
- [Mayan EDMS](https://gitlab.com/mayan-edms/mayan-edms) (Open source document management system to organize, tag, search, and automate your files with powerful Ollama driven workflows.)
- [Serene Pub](https://github.com/doolijb/serene-pub) (Beginner friendly, open source AI Roleplaying App for Windows, Mac OS and Linux. Search, download and use models with Ollama all inside the app.)
- [Andes](https://github.com/aqerd/andes) (A Visual Studio Code extension that provides a local UI interface for Ollama models)
- [Clueless](https://github.com/KashyapTan/clueless) (Open Source & Local Cluely: A desktop application LLM assistant to help you talk to anything on your screen using locally served Ollama models. Also undetectable to screenshare)
- [ollama-co2](https://github.com/carbonatedWaterOrg/ollama-co2) (FastAPI web interface for monitoring and managing local and remote Ollama servers with real-time model monitoring and concurrent downloads)

 ### Cloud

@@ -456,11 +440,8 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
 - [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
 - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull, and download models from Ollama Registry in your terminal.
+- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull and download models from Ollama Registry in your terminal.
 - [GGUF-to-Ollama](https://github.com/jonathanhecl/gguf-to-ollama) - Importing GGUF to Ollama made easy (multiplatform)
- [AWS-Strands-With-Ollama](https://github.com/rapidarchitect/ollama_strands) - AWS Strands Agents with Ollama Examples
- [ollama-multirun](https://github.com/attogram/ollama-multirun) - A bash shell script to run a single prompt against any or all of your locally installed ollama models, saving the output and performance statistics as easily navigable web pages. ([Demo](https://attogram.github.io/ai_test_zone/))
- [ollama-bash-toolshed](https://github.com/attogram/ollama-bash-toolshed) - Bash scripts to chat with tool using models. Add new tools to your shed with ease. Runs on Ollama.

 ### Apple Vision Pro

@@ -487,7 +468,7 @@ See the [API documentation](./docs/api.md) for all endpoints.

 ### Libraries

- [LangChain](https://python.langchain.com/docs/integrations/chat/ollama/) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
+- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
 - [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama)
 - [crewAI](https://github.com/crewAIInc/crewAI)
 - [Yacana](https://remembersoftwares.github.io/yacana/) (User-friendly multi-agent framework for brainstorming and executing predetermined flows with built-in tool integration)
@@ -534,24 +515,20 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Swollama for Swift](https://github.com/marcusziade/Swollama) with [DocC](https://marcusziade.github.io/Swollama/documentation/swollama/)
 - [GoLamify](https://github.com/prasad89/golamify)
 - [Ollama for Haskell](https://github.com/tusharad/ollama-haskell)
- [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in a unified API)
+- [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in unified API)
 - [LlmTornado](https://github.com/lofcz/llmtornado) (C# library providing a unified interface for major FOSS & Commercial inference APIs)
 - [Ollama for Zig](https://github.com/dravenk/ollama-zig)
 - [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider)
 - [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic
 - [Ollama for D](https://github.com/kassane/ollama-d)
- [OllamaPlusPlus](https://github.com/HardCodeDev777/OllamaPlusPlus) (Very simple C++ library for Ollama)
- [any-llm](https://github.com/mozilla-ai/any-llm) (A single interface to use different llm providers by [mozilla.ai](https://www.mozilla.ai/))
- [any-agent](https://github.com/mozilla-ai/any-agent) (A single interface to use and evaluate different agent frameworks by [mozilla.ai](https://www.mozilla.ai/))
- [Neuro SAN](https://github.com/cognizant-ai-lab/neuro-san-studio) (Data-driven multi-agent orchestration framework) with [example](https://github.com/cognizant-ai-lab/neuro-san-studio/blob/main/docs/user_guide.md#ollama)

 ### Mobile

- [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS, and iPad)
+- [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS and iPad)
 - [Enchanted](https://github.com/AugustDev/enchanted)
 - [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
 - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
+- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
 - [Ollama Android Chat](https://github.com/sunshine0523/OllamaServer) (No need for Termux, start the Ollama service with one click on an Android device)
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)

@@ -575,7 +552,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
 - [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
 - [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use Ollama as a copilot like GitHub Copilot)
+- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use ollama as a copilot like Github copilot)
 - [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
 - [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and Hugging Face)
 - [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
@@ -585,8 +562,8 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
 - [ChatGPTBox: All in one browser extension](https://github.com/josStorer/chatGPTBox) with [Integrating Tutorial](https://github.com/josStorer/chatGPTBox/issues/616#issuecomment-1975186467)
 - [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depend on ollama server)
- [Terraform AWS Ollama & Open WebUI](https://github.com/xuyangbocn/terraform-aws-self-host-llm) (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front-end Open WebUI service.)
+- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
+- [Terraform AWS Ollama & Open WebUI](https://github.com/xuyangbocn/terraform-aws-self-host-llm) (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front end Open WebUI service.)
 - [node-red-contrib-ollama](https://github.com/jakubburkiewicz/node-red-contrib-ollama)
 - [Local AI Helper](https://github.com/ivostoykov/localAI) (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.)
 - [vnc-lm](https://github.com/jake83741/vnc-lm) (Discord bot for messaging with LLMs through Ollama and LiteLLM. Seamlessly move between local and flagship models.)
@@ -600,15 +577,10 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Simple-Discord-AI](https://github.com/zyphixor/simple-discord-ai)
 - [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) (telegram bot, primary for RP. Oobabooga-like buttons, [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui) API integration e.t.c)
 - [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs)
- [SimpleOllamaUnity](https://github.com/HardCodeDev777/SimpleOllamaUnity) (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime)
- [UnityCodeLama](https://github.com/HardCodeDev777/UnityCodeLama) (Unity Edtior tool to analyze scripts via Ollama)
- [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) (Private, on-device AI Assistant, no cloud dependencies)
- [GMAI - Gradle Managed AI](https://gmai.premex.se/) (Gradle plugin for automated Ollama lifecycle management during build phases)
- [NOMYO Router](https://github.com/nomyo-ai/nomyo-router) (A transparent Ollama proxy with model deployment aware routing which auto-manages multiple Ollama instances in a given network)

 ### Supported backends

- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
+- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.

 ### Observability
 - [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native intergration to Ollama.
--- a/api/client.go
+++ b/api/client.go
@@ -24,10 +24,7 @@ import (
 	"net/http"
 	"net/url"
 	"runtime"
-	"strconv"
-	"time"

-	"github.com/ollama/ollama/auth"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/version"
@@ -45,12 +42,6 @@ func checkError(resp *http.Response, body []byte) error {
 		return nil
 	}

-	if resp.StatusCode == http.StatusUnauthorized {
-		authError := AuthorizationError{StatusCode: resp.StatusCode}
-		json.Unmarshal(body, &authError)
-		return authError
-	}
-
 	apiError := StatusError{StatusCode: resp.StatusCode}

 	err := json.Unmarshal(body, &apiError)
@@ -85,14 +76,6 @@ func NewClient(base *url.URL, http *http.Client) *Client {
 	}
 }

-func getAuthorizationToken(ctx context.Context, challenge string) (string, error) {
-	token, err := auth.Sign(ctx, []byte(challenge))
-	if err != nil {
-		return "", err
-	}
-	return token, nil
-}
-
 func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
 	var reqBody io.Reader
 	var data []byte
@@ -114,21 +97,6 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	}

 	requestURL := c.base.JoinPath(path)
-
-	var token string
-	if envconfig.UseAuth() || c.base.Hostname() == "ollama.com" {
-		now := strconv.FormatInt(time.Now().Unix(), 10)
-		chal := fmt.Sprintf("%s,%s?ts=%s", method, path, now)
-		token, err = getAuthorizationToken(ctx, chal)
-		if err != nil {
-			return err
-		}
-
-		q := requestURL.Query()
-		q.Set("ts", now)
-		requestURL.RawQuery = q.Encode()
-	}
-
 	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), reqBody)
 	if err != nil {
 		return err
@@ -138,10 +106,6 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	request.Header.Set("Accept", "application/json")
 	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))

-	if token != "" {
-		request.Header.Set("Authorization", token)
-	}
-
 	respObj, err := c.http.Do(request)
 	if err != nil {
 		return err
@@ -179,22 +143,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	}

 	requestURL := c.base.JoinPath(path)
-
-	var token string
-	if envconfig.UseAuth() || c.base.Hostname() == "ollama.com" {
-		var err error
-		now := strconv.FormatInt(time.Now().Unix(), 10)
-		chal := fmt.Sprintf("%s,%s?ts=%s", method, path, now)
-		token, err = getAuthorizationToken(ctx, chal)
-		if err != nil {
-			return err
-		}
-
-		q := requestURL.Query()
-		q.Set("ts", now)
-		requestURL.RawQuery = q.Encode()
-	}
-
 	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), buf)
 	if err != nil {
 		return err
@@ -204,10 +152,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	request.Header.Set("Accept", "application/x-ndjson")
 	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))

-	if token != "" {
-		request.Header.Set("Authorization", token)
-	}
-
 	response, err := c.http.Do(request)
 	if err != nil {
 		return err
@@ -220,8 +164,7 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	scanner.Buffer(scanBuf, maxBufferSize)
 	for scanner.Scan() {
 		var errorResponse struct {
-			Error     string `json:"error,omitempty"`
-			SigninURL string `json:"signin_url,omitempty"`
+			Error string `json:"error,omitempty"`
 		}

 		bts := scanner.Bytes()
@@ -229,13 +172,11 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			return fmt.Errorf("unmarshal: %w", err)
 		}

-		if response.StatusCode == http.StatusUnauthorized {
-			return AuthorizationError{
-				StatusCode: response.StatusCode,
-				Status:     response.Status,
-				SigninURL:  errorResponse.SigninURL,
-			}
-		} else if response.StatusCode >= http.StatusBadRequest {
+		if errorResponse.Error != "" {
+			return errors.New(errorResponse.Error)
+		}
+
+		if response.StatusCode >= http.StatusBadRequest {
 			return StatusError{
 				StatusCode:   response.StatusCode,
 				Status:       response.Status,
@@ -243,10 +184,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			}
 		}

-		if errorResponse.Error != "" {
-			return errors.New(errorResponse.Error)
-		}
-
 		if err := fn(bts); err != nil {
 			return err
 		}
@@ -441,21 +378,3 @@ func (c *Client) Version(ctx context.Context) (string, error) {

 	return version.Version, nil
 }
-
-// Signout will signout a client for a local ollama server.
-func (c *Client) Signout(ctx context.Context) error {
-	return c.do(ctx, http.MethodPost, "/api/signout", nil, nil)
-}
-
-// Disconnect will disconnect an ollama instance from ollama.com.
-func (c *Client) Disconnect(ctx context.Context, encodedKey string) error {
-	return c.do(ctx, http.MethodDelete, fmt.Sprintf("/api/user/keys/%s", encodedKey), nil, nil)
-}
-
-func (c *Client) Whoami(ctx context.Context) (*UserResponse, error) {
-	var resp UserResponse
-	if err := c.do(ctx, http.MethodPost, "/api/me", nil, &resp); err != nil {
-		return nil, err
-	}
-	return &resp, nil
-}
--- a/api/client_test.go
+++ b/api/client_test.go
@@ -1,6 +1,7 @@
 package api

 import (
+	"context"
 	"encoding/json"
 	"fmt"
 	"net/http"
@@ -89,16 +90,6 @@ func TestClientStream(t *testing.T) {
 			},
 			wantErr: "mid-stream error",
 		},
-		{
-			name: "http status error takes precedence over general error",
-			responses: []any{
-				testError{
-					message:    "custom error message",
-					statusCode: http.StatusInternalServerError,
-				},
-			},
-			wantErr: "500",
-		},
 		{
 			name: "successful stream completion",
 			responses: []any{
@@ -146,7 +137,7 @@ func TestClientStream(t *testing.T) {
 			client := NewClient(&url.URL{Scheme: "http", Host: ts.Listener.Addr().String()}, http.DefaultClient)

 			var receivedChunks []ChatResponse
-			err := client.stream(t.Context(), http.MethodPost, "/v1/chat", nil, func(chunk []byte) error {
+			err := client.stream(context.Background(), http.MethodPost, "/v1/chat", nil, func(chunk []byte) error {
 				var resp ChatResponse
 				if err := json.Unmarshal(chunk, &resp); err != nil {
 					return fmt.Errorf("failed to unmarshal chunk: %w", err)
@@ -232,7 +223,7 @@ func TestClientDo(t *testing.T) {
 				ID      string `json:"id"`
 				Success bool   `json:"success"`
 			}
-			err := client.do(t.Context(), http.MethodPost, "/v1/messages", nil, &resp)
+			err := client.do(context.Background(), http.MethodPost, "/v1/messages", nil, &resp)

 			if tc.wantErr != "" {
 				if err == nil {
--- a/api/types.go
+++ b/api/types.go
@@ -11,8 +11,6 @@ import (
 	"strings"
 	"time"

-	"github.com/google/uuid"
-
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/types/model"
 )
@@ -38,19 +36,6 @@ func (e StatusError) Error() string {
 	}
 }

-type AuthorizationError struct {
-	StatusCode int
-	Status     string
-	SigninURL  string `json:"signin_url"`
-}
-
-func (e AuthorizationError) Error() string {
-	if e.Status != "" {
-		return e.Status
-	}
-	return "something went wrong, please see the ollama server logs for details"
-}
-
 // ImageData represents the raw binary data of an image file.
 type ImageData []byte

@@ -98,17 +83,6 @@ type GenerateRequest struct {
 	// Options lists model-specific options. For example, temperature can be
 	// set through this field, if the model supports it.
 	Options map[string]any `json:"options"`
-
-	// Think controls whether thinking/reasoning models will think before
-	// responding. Can be a boolean (true/false) or a string ("high", "medium", "low")
-	// for supported models. Needs to be a pointer so we can distinguish between false
-	// (request that thinking _not_ be used) and unset (use the old behavior
-	// before this option was introduced)
-	Think *ThinkValue `json:"think,omitempty"`
-
-	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
-	// template instead of calling the model.
-	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
 }

 // ChatRequest describes a request sent by [Client.Chat].
@@ -134,15 +108,6 @@ type ChatRequest struct {

 	// Options lists model-specific options.
 	Options map[string]any `json:"options"`
-
-	// Think controls whether thinking/reasoning models will think before
-	// responding. Can be a boolean (true/false) or a string ("high", "medium", "low")
-	// for supported models.
-	Think *ThinkValue `json:"think,omitempty"`
-
-	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
-	// template instead of calling the model.
-	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
 }

 type Tools []Tool
@@ -161,14 +126,10 @@ func (t Tool) String() string {
 // role ("system", "user", or "assistant"), the content and an optional list
 // of images.
 type Message struct {
-	Role    string `json:"role"`
-	Content string `json:"content"`
-	// Thinking contains the text that was inside thinking tags in the
-	// original model output when ChatRequest.Think is enabled.
-	Thinking  string      `json:"thinking,omitempty"`
+	Role      string      `json:"role"`
+	Content   string      `json:"content"`
 	Images    []ImageData `json:"images,omitempty"`
 	ToolCalls []ToolCall  `json:"tool_calls,omitempty"`
-	ToolName  string      `json:"tool_name,omitempty"`
 }

 func (m *Message) UnmarshalJSON(b []byte) error {
@@ -248,76 +209,21 @@ func (pt PropertyType) String() string {
 	return fmt.Sprintf("%v", []string(pt))
 }

-type ToolProperty struct {
-	AnyOf       []ToolProperty `json:"anyOf,omitempty"`
-	Type        PropertyType   `json:"type"`
-	Items       any            `json:"items,omitempty"`
-	Description string         `json:"description"`
-	Enum        []any          `json:"enum,omitempty"`
-}
-
-// ToTypeScriptType converts a ToolProperty to a TypeScript type string
-func (tp ToolProperty) ToTypeScriptType() string {
-	if len(tp.AnyOf) > 0 {
-		var types []string
-		for _, anyOf := range tp.AnyOf {
-			types = append(types, anyOf.ToTypeScriptType())
-		}
-		return strings.Join(types, " | ")
-	}
-
-	if len(tp.Type) == 0 {
-		return "any"
-	}
-
-	if len(tp.Type) == 1 {
-		return mapToTypeScriptType(tp.Type[0])
-	}
-
-	var types []string
-	for _, t := range tp.Type {
-		types = append(types, mapToTypeScriptType(t))
-	}
-	return strings.Join(types, " | ")
-}
-
-// mapToTypeScriptType maps JSON Schema types to TypeScript types
-func mapToTypeScriptType(jsonType string) string {
-	switch jsonType {
-	case "string":
-		return "string"
-	case "number", "integer":
-		return "number"
-	case "boolean":
-		return "boolean"
-	case "array":
-		return "any[]"
-	case "object":
-		return "Record<string, any>"
-	case "null":
-		return "null"
-	default:
-		return "any"
-	}
-}
-
-type ToolFunctionParameters struct {
-	Type       string                  `json:"type"`
-	Defs       any                     `json:"$defs,omitempty"`
-	Items      any                     `json:"items,omitempty"`
-	Required   []string                `json:"required"`
-	Properties map[string]ToolProperty `json:"properties"`
-}
-
-func (t *ToolFunctionParameters) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
 type ToolFunction struct {
-	Name        string                 `json:"name"`
-	Description string                 `json:"description"`
-	Parameters  ToolFunctionParameters `json:"parameters"`
+	Name        string `json:"name"`
+	Description string `json:"description"`
+	Parameters  struct {
+		Type       string   `json:"type"`
+		Defs       any      `json:"$defs,omitempty"`
+		Items      any      `json:"items,omitempty"`
+		Required   []string `json:"required"`
+		Properties map[string]struct {
+			Type        PropertyType `json:"type"`
+			Items       any          `json:"items,omitempty"`
+			Description string       `json:"description"`
+			Enum        []any        `json:"enum,omitempty"`
+		} `json:"properties"`
+	} `json:"parameters"`
 }

 func (t *ToolFunction) String() string {
@@ -328,38 +234,16 @@ func (t *ToolFunction) String() string {
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
 // similar to [GenerateResponse].
 type ChatResponse struct {
-	// Model is the model name that generated the response.
-	Model string `json:"model"`
+	Model      string    `json:"model"`
+	CreatedAt  time.Time `json:"created_at"`
+	Message    Message   `json:"message"`
+	DoneReason string    `json:"done_reason,omitempty"`

-	// RemoteModel is the name of the upstream model that generated the response.
-	RemoteModel string `json:"remote_model,omitempty"`
-
-	// RemoteHost is the URL of the upstream Ollama host that generated the response.
-	RemoteHost string `json:"remote_host,omitempty"`
-
-	// CreatedAt is the timestamp of the response.
-	CreatedAt time.Time `json:"created_at"`
-
-	// Message contains the message or part of a message from the model.
-	Message Message `json:"message"`
-
-	// Done specifies if the response is complete.
 	Done bool `json:"done"`

-	// DoneReason is the reason the model stopped generating text.
-	DoneReason string `json:"done_reason,omitempty"`
-
-	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
-
 	Metrics
 }

-// DebugInfo contains debug information for template rendering
-type DebugInfo struct {
-	RenderedTemplate string `json:"rendered_template"`
-	ImageCount       int    `json:"image_count,omitempty"`
-}
-
 type Metrics struct {
 	TotalDuration      time.Duration `json:"total_duration,omitempty"`
 	LoadDuration       time.Duration `json:"load_duration,omitempty"`
@@ -387,6 +271,9 @@ type Options struct {
 	RepeatPenalty    float32  `json:"repeat_penalty,omitempty"`
 	PresencePenalty  float32  `json:"presence_penalty,omitempty"`
 	FrequencyPenalty float32  `json:"frequency_penalty,omitempty"`
+	Mirostat         int      `json:"mirostat,omitempty"`
+	MirostatTau      float32  `json:"mirostat_tau,omitempty"`
+	MirostatEta      float32  `json:"mirostat_eta,omitempty"`
 	Stop             []string `json:"stop,omitempty"`
 }

@@ -396,7 +283,12 @@ type Runner struct {
 	NumBatch  int   `json:"num_batch,omitempty"`
 	NumGPU    int   `json:"num_gpu,omitempty"`
 	MainGPU   int   `json:"main_gpu,omitempty"`
+	LowVRAM   bool  `json:"low_vram,omitempty"`
+	F16KV     bool  `json:"f16_kv,omitempty"` // Deprecated: This option is ignored
+	LogitsAll bool  `json:"logits_all,omitempty"`
+	VocabOnly bool  `json:"vocab_only,omitempty"`
 	UseMMap   *bool `json:"use_mmap,omitempty"`
+	UseMLock  bool  `json:"use_mlock,omitempty"`
 	NumThread int   `json:"num_thread,omitempty"`
 }

@@ -412,12 +304,8 @@ type EmbedRequest struct {
 	// this request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`

-	// Truncate truncates the input to fit the model's max sequence length.
 	Truncate *bool `json:"truncate,omitempty"`

-	// Dimensions truncates the output embedding to the specified dimension.
-	Dimensions int `json:"dimensions,omitempty"`
-
 	// Options lists model-specific options.
 	Options map[string]any `json:"options"`
 }
@@ -455,47 +343,18 @@ type EmbeddingResponse struct {

 // CreateRequest is the request passed to [Client.Create].
 type CreateRequest struct {
-	// Model is the model name to create.
-	Model string `json:"model"`
-
-	// Stream specifies whether the response is streaming; it is true by default.
-	Stream *bool `json:"stream,omitempty"`
-
-	// Quantize is the quantization format for the model; leave blank to not change the quantization level.
+	Model    string `json:"model"`
+	Stream   *bool  `json:"stream,omitempty"`
 	Quantize string `json:"quantize,omitempty"`

-	// From is the name of the model or file to use as the source.
-	From string `json:"from,omitempty"`
-
-	// RemoteHost is the URL of the upstream ollama API for the model (if any).
-	RemoteHost string `json:"remote_host,omitempty"`
-
-	// Files is a map of files include when creating the model.
-	Files map[string]string `json:"files,omitempty"`
-
-	// Adapters is a map of LoRA adapters to include when creating the model.
-	Adapters map[string]string `json:"adapters,omitempty"`
-
-	// Template is the template used when constructing a request to the model.
-	Template string `json:"template,omitempty"`
-
-	// License is a string or list of strings for licenses.
-	License any `json:"license,omitempty"`
-
-	// System is the system prompt for the model.
-	System string `json:"system,omitempty"`
-
-	// Parameters is a map of hyper-parameters which are applied to the model.
-	Parameters map[string]any `json:"parameters,omitempty"`
-
-	// Messages is a list of messages added to the model before chat and generation requests.
-	Messages []Message `json:"messages,omitempty"`
-
-	Renderer string `json:"renderer,omitempty"`
-	Parser   string `json:"parser,omitempty"`
-
-	// Info is a map of additional information for the model
-	Info map[string]any `json:"info,omitempty"`
+	From       string            `json:"from,omitempty"`
+	Files      map[string]string `json:"files,omitempty"`
+	Adapters   map[string]string `json:"adapters,omitempty"`
+	Template   string            `json:"template,omitempty"`
+	License    any               `json:"license,omitempty"`
+	System     string            `json:"system,omitempty"`
+	Parameters map[string]any    `json:"parameters,omitempty"`
+	Messages   []Message         `json:"messages,omitempty"`

 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -533,12 +392,8 @@ type ShowResponse struct {
 	Parameters    string             `json:"parameters,omitempty"`
 	Template      string             `json:"template,omitempty"`
 	System        string             `json:"system,omitempty"`
-	Renderer      string             `json:"renderer,omitempty"`
-	Parser        string             `json:"parser,omitempty"`
 	Details       ModelDetails       `json:"details,omitempty"`
 	Messages      []Message          `json:"messages,omitempty"`
-	RemoteModel   string             `json:"remote_model,omitempty"`
-	RemoteHost    string             `json:"remote_host,omitempty"`
 	ModelInfo     map[string]any     `json:"model_info,omitempty"`
 	ProjectorInfo map[string]any     `json:"projector_info,omitempty"`
 	Tensors       []Tensor           `json:"tensors,omitempty"`
@@ -597,26 +452,30 @@ type ProcessResponse struct {

 // ListModelResponse is a single model description in [ListResponse].
 type ListModelResponse struct {
-	Name        string       `json:"name"`
-	Model       string       `json:"model"`
-	RemoteModel string       `json:"remote_model,omitempty"`
-	RemoteHost  string       `json:"remote_host,omitempty"`
-	ModifiedAt  time.Time    `json:"modified_at"`
-	Size        int64        `json:"size"`
-	Digest      string       `json:"digest"`
-	Details     ModelDetails `json:"details,omitempty"`
+	Name       string       `json:"name"`
+	Model      string       `json:"model"`
+	ModifiedAt time.Time    `json:"modified_at"`
+	Size       int64        `json:"size"`
+	Digest     string       `json:"digest"`
+	Details    ModelDetails `json:"details,omitempty"`
 }

 // ProcessModelResponse is a single model description in [ProcessResponse].
 type ProcessModelResponse struct {
-	Name          string       `json:"name"`
-	Model         string       `json:"model"`
-	Size          int64        `json:"size"`
-	Digest        string       `json:"digest"`
-	Details       ModelDetails `json:"details,omitempty"`
-	ExpiresAt     time.Time    `json:"expires_at"`
-	SizeVRAM      int64        `json:"size_vram"`
-	ContextLength int          `json:"context_length"`
+	Name      string       `json:"name"`
+	Model     string       `json:"model"`
+	Size      int64        `json:"size"`
+	Digest    string       `json:"digest"`
+	Details   ModelDetails `json:"details,omitempty"`
+	ExpiresAt time.Time    `json:"expires_at"`
+	SizeVRAM  int64        `json:"size_vram"`
+}
+
+type RetrieveModelResponse struct {
+	Id      string `json:"id"`
+	Object  string `json:"object"`
+	Created int64  `json:"created"`
+	OwnedBy string `json:"owned_by"`
 }

 type TokenResponse struct {
@@ -628,22 +487,12 @@ type GenerateResponse struct {
 	// Model is the model name that generated the response.
 	Model string `json:"model"`

-	// RemoteModel is the name of the upstream model that generated the response.
-	RemoteModel string `json:"remote_model,omitempty"`
-
-	// RemoteHost is the URL of the upstream Ollama host that generated the response.
-	RemoteHost string `json:"remote_host,omitempty"`
-
 	// CreatedAt is the timestamp of the response.
 	CreatedAt time.Time `json:"created_at"`

 	// Response is the textual response itself.
 	Response string `json:"response"`

-	// Thinking contains the text that was inside thinking tags in the
-	// original model output when ChatRequest.Think is enabled.
-	Thinking string `json:"thinking,omitempty"`
-
 	// Done specifies if the response is complete.
 	Done bool `json:"done"`

@@ -655,10 +504,6 @@ type GenerateResponse struct {
 	Context []int `json:"context,omitempty"`

 	Metrics
-
-	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
-
-	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
 }

 // ModelDetails provides details about a model.
@@ -671,18 +516,6 @@ type ModelDetails struct {
 	QuantizationLevel string   `json:"quantization_level"`
 }

-// UserResponse provides information about a user.
-type UserResponse struct {
-	ID        uuid.UUID `json:"id"`
-	Email     string    `json:"email"`
-	Name      string    `json:"name"`
-	Bio       string    `json:"bio,omitempty"`
-	AvatarURL string    `json:"avatarurl,omitempty"`
-	FirstName string    `json:"firstname,omitempty"`
-	LastName  string    `json:"lastname,omitempty"`
-	Plan      string    `json:"plan,omitempty"`
-}
-
 // Tensor describes the metadata for a given tensor.
 type Tensor struct {
 	Name  string   `json:"name"`
@@ -827,6 +660,9 @@ func DefaultOptions() Options {
 		RepeatPenalty:    1.1,
 		PresencePenalty:  0.0,
 		FrequencyPenalty: 0.0,
+		Mirostat:         0,
+		MirostatTau:      5.0,
+		MirostatEta:      0.1,
 		Seed:             -1,

 		Runner: Runner{
@@ -835,118 +671,13 @@ func DefaultOptions() Options {
 			NumBatch:  512,
 			NumGPU:    -1, // -1 here indicates that NumGPU should be set dynamically
 			NumThread: 0,  // let the runtime decide
+			LowVRAM:   false,
+			UseMLock:  false,
 			UseMMap:   nil,
 		},
 	}
 }

-// ThinkValue represents a value that can be a boolean or a string ("high", "medium", "low")
-type ThinkValue struct {
-	// Value can be a bool or string
-	Value interface{}
-}
-
-// IsValid checks if the ThinkValue is valid
-func (t *ThinkValue) IsValid() bool {
-	if t == nil || t.Value == nil {
-		return true // nil is valid (means not set)
-	}
-
-	switch v := t.Value.(type) {
-	case bool:
-		return true
-	case string:
-		return v == "high" || v == "medium" || v == "low"
-	default:
-		return false
-	}
-}
-
-// IsBool returns true if the value is a boolean
-func (t *ThinkValue) IsBool() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-	_, ok := t.Value.(bool)
-	return ok
-}
-
-// IsString returns true if the value is a string
-func (t *ThinkValue) IsString() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-	_, ok := t.Value.(string)
-	return ok
-}
-
-// Bool returns the value as a bool (true if enabled in any way)
-func (t *ThinkValue) Bool() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-
-	switch v := t.Value.(type) {
-	case bool:
-		return v
-	case string:
-		// Any string value ("high", "medium", "low") means thinking is enabled
-		return v == "high" || v == "medium" || v == "low"
-	default:
-		return false
-	}
-}
-
-// String returns the value as a string
-func (t *ThinkValue) String() string {
-	if t == nil || t.Value == nil {
-		return ""
-	}
-
-	switch v := t.Value.(type) {
-	case string:
-		return v
-	case bool:
-		if v {
-			return "medium" // Default level when just true
-		}
-		return ""
-	default:
-		return ""
-	}
-}
-
-// UnmarshalJSON implements json.Unmarshaler
-func (t *ThinkValue) UnmarshalJSON(data []byte) error {
-	// Try to unmarshal as bool first
-	var b bool
-	if err := json.Unmarshal(data, &b); err == nil {
-		t.Value = b
-		return nil
-	}
-
-	// Try to unmarshal as string
-	var s string
-	if err := json.Unmarshal(data, &s); err == nil {
-		// Validate string values
-		if s != "high" && s != "medium" && s != "low" {
-			return fmt.Errorf("invalid think value: %q (must be \"high\", \"medium\", \"low\", true, or false)", s)
-		}
-		t.Value = s
-		return nil
-	}
-
-	return fmt.Errorf("think must be a boolean or string (\"high\", \"medium\", \"low\")")
-}
-
-// MarshalJSON implements json.Marshaler
-func (t *ThinkValue) MarshalJSON() ([]byte, error) {
-	if t == nil || t.Value == nil {
-		return []byte("null"), nil
-	}
-	return json.Marshal(t.Value)
-}
-
 type Duration struct {
 	time.Duration
 }
@@ -971,7 +702,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
 		if t < 0 {
 			d.Duration = time.Duration(math.MaxInt64)
 		} else {
-			d.Duration = time.Duration(t * float64(time.Second))
+			d.Duration = time.Duration(int(t) * int(time.Second))
 		}
 	case string:
 		d.Duration, err = time.ParseDuration(t)
--- a/api/types_test.go
+++ b/api/types_test.go
@@ -17,11 +17,6 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
 		req  string
 		exp  *Duration
 	}{
-		{
-			name: "Unset",
-			req:  `{ }`,
-			exp:  nil,
-		},
 		{
 			name: "Positive Integer",
 			req:  `{ "keep_alive": 42 }`,
@@ -30,7 +25,7 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
 		{
 			name: "Positive Float",
 			req:  `{ "keep_alive": 42.5 }`,
-			exp:  &Duration{42500 * time.Millisecond},
+			exp:  &Duration{42 * time.Second},
 		},
 		{
 			name: "Positive Integer String",
@@ -377,114 +372,3 @@ func TestPropertyType_MarshalJSON(t *testing.T) {
 		})
 	}
 }
-
-func TestThinking_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		name             string
-		input            string
-		expectedThinking *ThinkValue
-		expectedError    bool
-	}{
-		{
-			name:             "true",
-			input:            `{ "think": true }`,
-			expectedThinking: &ThinkValue{Value: true},
-		},
-		{
-			name:             "false",
-			input:            `{ "think": false }`,
-			expectedThinking: &ThinkValue{Value: false},
-		},
-		{
-			name:             "unset",
-			input:            `{ }`,
-			expectedThinking: nil,
-		},
-		{
-			name:             "string_high",
-			input:            `{ "think": "high" }`,
-			expectedThinking: &ThinkValue{Value: "high"},
-		},
-		{
-			name:             "string_medium",
-			input:            `{ "think": "medium" }`,
-			expectedThinking: &ThinkValue{Value: "medium"},
-		},
-		{
-			name:             "string_low",
-			input:            `{ "think": "low" }`,
-			expectedThinking: &ThinkValue{Value: "low"},
-		},
-		{
-			name:             "invalid_string",
-			input:            `{ "think": "invalid" }`,
-			expectedThinking: nil,
-			expectedError:    true,
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			var req GenerateRequest
-			err := json.Unmarshal([]byte(test.input), &req)
-			if test.expectedError {
-				require.Error(t, err)
-			} else {
-				require.NoError(t, err)
-				if test.expectedThinking == nil {
-					assert.Nil(t, req.Think)
-				} else {
-					require.NotNil(t, req.Think)
-					assert.Equal(t, test.expectedThinking.Value, req.Think.Value)
-				}
-			}
-		})
-	}
-}
-
-func TestToolFunctionParameters_String(t *testing.T) {
-	tests := []struct {
-		name     string
-		params   ToolFunctionParameters
-		expected string
-	}{
-		{
-			name: "simple object with string property",
-			params: ToolFunctionParameters{
-				Type:     "object",
-				Required: []string{"name"},
-				Properties: map[string]ToolProperty{
-					"name": {
-						Type:        PropertyType{"string"},
-						Description: "The name of the person",
-					},
-				},
-			},
-			expected: `{"type":"object","required":["name"],"properties":{"name":{"type":"string","description":"The name of the person"}}}`,
-		},
-		{
-			name: "marshal failure returns empty string",
-			params: ToolFunctionParameters{
-				Type: "object",
-				Defs: func() any {
-					// Create a cycle that will cause json.Marshal to fail
-					type selfRef struct {
-						Self *selfRef
-					}
-					s := &selfRef{}
-					s.Self = s
-					return s
-				}(),
-				Properties: map[string]ToolProperty{},
-			},
-			expected: "",
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			result := test.params.String()
-			assert.Equal(t, test.expected, result)
-		})
-	}
-}
--- a/api/types_typescript_test.go
+++ b/api/types_typescript_test.go
@@ -1,142 +0,0 @@
-package api
-
-import (
-	"testing"
-)
-
-func TestToolParameterToTypeScriptType(t *testing.T) {
-	tests := []struct {
-		name     string
-		param    ToolProperty
-		expected string
-	}{
-		{
-			name: "single string type",
-			param: ToolProperty{
-				Type: PropertyType{"string"},
-			},
-			expected: "string",
-		},
-		{
-			name: "single number type",
-			param: ToolProperty{
-				Type: PropertyType{"number"},
-			},
-			expected: "number",
-		},
-		{
-			name: "integer maps to number",
-			param: ToolProperty{
-				Type: PropertyType{"integer"},
-			},
-			expected: "number",
-		},
-		{
-			name: "boolean type",
-			param: ToolProperty{
-				Type: PropertyType{"boolean"},
-			},
-			expected: "boolean",
-		},
-		{
-			name: "array type",
-			param: ToolProperty{
-				Type: PropertyType{"array"},
-			},
-			expected: "any[]",
-		},
-		{
-			name: "object type",
-			param: ToolProperty{
-				Type: PropertyType{"object"},
-			},
-			expected: "Record<string, any>",
-		},
-		{
-			name: "null type",
-			param: ToolProperty{
-				Type: PropertyType{"null"},
-			},
-			expected: "null",
-		},
-		{
-			name: "multiple types as union",
-			param: ToolProperty{
-				Type: PropertyType{"string", "number"},
-			},
-			expected: "string | number",
-		},
-		{
-			name: "string or null union",
-			param: ToolProperty{
-				Type: PropertyType{"string", "null"},
-			},
-			expected: "string | null",
-		},
-		{
-			name: "anyOf with single types",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"string"}},
-					{Type: PropertyType{"number"}},
-				},
-			},
-			expected: "string | number",
-		},
-		{
-			name: "anyOf with multiple types in each branch",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"string", "null"}},
-					{Type: PropertyType{"number"}},
-				},
-			},
-			expected: "string | null | number",
-		},
-		{
-			name: "nested anyOf",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"boolean"}},
-					{
-						AnyOf: []ToolProperty{
-							{Type: PropertyType{"string"}},
-							{Type: PropertyType{"number"}},
-						},
-					},
-				},
-			},
-			expected: "boolean | string | number",
-		},
-		{
-			name: "empty type returns any",
-			param: ToolProperty{
-				Type: PropertyType{},
-			},
-			expected: "any",
-		},
-		{
-			name: "unknown type maps to any",
-			param: ToolProperty{
-				Type: PropertyType{"unknown_type"},
-			},
-			expected: "any",
-		},
-		{
-			name: "multiple types including array",
-			param: ToolProperty{
-				Type: PropertyType{"string", "array", "null"},
-			},
-			expected: "string | any[] | null",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			result := tt.param.ToTypeScriptType()
-			if result != tt.expected {
-				t.Errorf("ToTypeScriptType() = %q, want %q", result, tt.expected)
-			}
-		})
-	}
-}
--- a/app/lifecycle/logging.go
+++ b/app/lifecycle/logging.go
@@ -4,14 +4,20 @@ import (
 	"fmt"
 	"log/slog"
 	"os"
+	"path/filepath"
 	"strconv"
 	"strings"

 	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/logutil"
 )

 func InitLogging() {
+	level := slog.LevelInfo
+
+	if envconfig.Debug() {
+		level = slog.LevelDebug
+	}
+
 	var logFile *os.File
 	var err error
 	// Detect if we're a GUI app on windows, and if not, send logs to console
@@ -27,8 +33,20 @@ func InitLogging() {
 			return
 		}
 	}
+	handler := slog.NewTextHandler(logFile, &slog.HandlerOptions{
+		Level:     level,
+		AddSource: true,
+		ReplaceAttr: func(_ []string, attr slog.Attr) slog.Attr {
+			if attr.Key == slog.SourceKey {
+				source := attr.Value.Any().(*slog.Source)
+				source.File = filepath.Base(source.File)
+			}
+			return attr
+		},
+	})
+
+	slog.SetDefault(slog.New(handler))

-	slog.SetDefault(logutil.NewLogger(logFile, envconfig.LogLevel()))
 	slog.Info("ollama app started")
 }

--- a/auth/auth.go
+++ b/auth/auth.go
@@ -18,13 +18,21 @@ import (

 const defaultPrivateKey = "id_ed25519"

-func GetPublicKey() (string, error) {
+func keyPath() (string, error) {
 	home, err := os.UserHomeDir()
 	if err != nil {
 		return "", err
 	}

-	keyPath := filepath.Join(home, ".ollama", defaultPrivateKey)
+	return filepath.Join(home, ".ollama", defaultPrivateKey), nil
+}
+
+func GetPublicKey() (string, error) {
+	keyPath, err := keyPath()
+	if err != nil {
+		return "", err
+	}
+
 	privateKeyFile, err := os.ReadFile(keyPath)
 	if err != nil {
 		slog.Info(fmt.Sprintf("Failed to load private key: %v", err))
@@ -51,12 +59,11 @@ func NewNonce(r io.Reader, length int) (string, error) {
 }

 func Sign(ctx context.Context, bts []byte) (string, error) {
-	home, err := os.UserHomeDir()
+	keyPath, err := keyPath()
 	if err != nil {
 		return "", err
 	}

-	keyPath := filepath.Join(home, ".ollama", defaultPrivateKey)
 	privateKeyFile, err := os.ReadFile(keyPath)
 	if err != nil {
 		slog.Info(fmt.Sprintf("Failed to load private key: %v", err))
--- a/benchmark/server_benchmark_test.go
+++ b/benchmark/server_benchmark_test.go
@@ -0,0 +1,178 @@
+package benchmark
+
+import (
+	"context"
+	"flag"
+	"fmt"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+// Command line flags
+var modelFlag string
+
+func init() {
+	flag.StringVar(&modelFlag, "m", "", "Name of the model to benchmark")
+	flag.Lookup("m").DefValue = "model"
+}
+
+// modelName returns the model name from flags, failing the test if not set
+func modelName(b *testing.B) string {
+	if modelFlag == "" {
+		b.Fatal("Error: -m flag is required for benchmark tests")
+	}
+	return modelFlag
+}
+
+type TestCase struct {
+	name      string
+	prompt    string
+	maxTokens int
+}
+
+// runGenerateBenchmark contains the common generate and metrics logic
+func runGenerateBenchmark(b *testing.B, ctx context.Context, client *api.Client, req *api.GenerateRequest) {
+	start := time.Now()
+	var ttft time.Duration
+	var metrics api.Metrics
+
+	err := client.Generate(ctx, req, func(resp api.GenerateResponse) error {
+		if ttft == 0 && resp.Response != "" {
+			ttft = time.Since(start)
+		}
+		if resp.Done {
+			metrics = resp.Metrics
+		}
+		return nil
+	})
+
+	// Report custom metrics as part of the benchmark results
+	b.ReportMetric(float64(ttft.Milliseconds()), "ttft_ms")
+	b.ReportMetric(float64(metrics.LoadDuration.Milliseconds()), "load_ms")
+
+	// Token throughput metrics
+	promptThroughput := float64(metrics.PromptEvalCount) / metrics.PromptEvalDuration.Seconds()
+	genThroughput := float64(metrics.EvalCount) / metrics.EvalDuration.Seconds()
+	b.ReportMetric(promptThroughput, "prompt_tok/s")
+	b.ReportMetric(genThroughput, "gen_tok/s")
+
+	// Token counts
+	b.ReportMetric(float64(metrics.PromptEvalCount), "prompt_tokens")
+	b.ReportMetric(float64(metrics.EvalCount), "gen_tokens")
+	if err != nil {
+		b.Fatal(err)
+	}
+}
+
+// BenchmarkColdStart runs benchmarks with model loading from cold state
+func BenchmarkColdStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/cold/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				b.StopTimer()
+				// Ensure model is unloaded before each iteration
+				unload(client, m, b)
+				b.StartTimer()
+
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// BenchmarkWarmStart runs benchmarks with pre-loaded model
+func BenchmarkWarmStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/warm/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Pre-warm the model
+			warmup(client, m, tt.prompt, b)
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// setup verifies server and model availability
+func setup(b *testing.B) *api.Client {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		b.Fatal(err)
+	}
+	if _, err := client.Show(context.Background(), &api.ShowRequest{Model: modelName(b)}); err != nil {
+		b.Fatalf("Model unavailable: %v", err)
+	}
+
+	return client
+}
+
+// warmup ensures the model is loaded and warmed up
+func warmup(client *api.Client, model string, prompt string, b *testing.B) {
+	for range 3 {
+		err := client.Generate(
+			context.Background(),
+			&api.GenerateRequest{
+				Model:   model,
+				Prompt:  prompt,
+				Options: map[string]any{"num_predict": 50, "temperature": 0.1},
+			},
+			func(api.GenerateResponse) error { return nil },
+		)
+		if err != nil {
+			b.Logf("Error during model warm-up: %v", err)
+		}
+	}
+}
+
+// unload forces model unloading using KeepAlive: 0 parameter
+func unload(client *api.Client, model string, b *testing.B) {
+	req := &api.GenerateRequest{
+		Model:     model,
+		KeepAlive: &api.Duration{Duration: 0},
+	}
+	if err := client.Generate(context.Background(), req, func(api.GenerateResponse) error { return nil }); err != nil {
+		b.Logf("Unload error: %v", err)
+	}
+	time.Sleep(1 * time.Second)
+}
--- a/cmd/cmd.go
+++ b/cmd/cmd.go
@@ -31,7 +31,6 @@ import (
 	"github.com/olekukonko/tablewriter"
 	"github.com/spf13/cobra"
 	"golang.org/x/crypto/ssh"
-	"golang.org/x/sync/errgroup"
 	"golang.org/x/term"

 	"github.com/ollama/ollama/api"
@@ -39,31 +38,12 @@ import (
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/parser"
 	"github.com/ollama/ollama/progress"
-	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/runner"
 	"github.com/ollama/ollama/server"
 	"github.com/ollama/ollama/types/model"
-	"github.com/ollama/ollama/types/syncmap"
 	"github.com/ollama/ollama/version"
 )

-const ConnectInstructions = "To sign in, navigate to:\n    %s\n\n"
-
-// ensureThinkingSupport emits a warning if the model does not advertise thinking support
-func ensureThinkingSupport(ctx context.Context, client *api.Client, name string) {
-	if name == "" {
-		return
-	}
-	resp, err := client.Show(ctx, &api.ShowRequest{Model: name})
-	if err != nil {
-		return
-	}
-	if slices.Contains(resp.Capabilities, model.CapabilityThinking) {
-		return
-	}
-	fmt.Fprintf(os.Stderr, "warning: model %q does not support thinking output\n", name)
-}
-
 var errModelfileNotFound = errors.New("specified Modelfile wasn't found")

 func getModelfileName(cmd *cobra.Command) (string, error) {
@@ -126,7 +106,7 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 	}
 	spinner.Stop()

-	req.Model = args[0]
+	req.Name = args[0]
 	quantize, _ := cmd.Flags().GetString("quantize")
 	if quantize != "" {
 		req.Quantize = quantize
@@ -137,54 +117,34 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}

-	var g errgroup.Group
-	g.SetLimit(max(runtime.GOMAXPROCS(0)-1, 1))
-
-	files := syncmap.NewSyncMap[string, string]()
-	for f, digest := range req.Files {
-		g.Go(func() error {
+	if len(req.Files) > 0 {
+		fileMap := map[string]string{}
+		for f, digest := range req.Files {
 			if _, err := createBlob(cmd, client, f, digest, p); err != nil {
 				return err
 			}
-
-			// TODO: this is incorrect since the file might be in a subdirectory
-			//       instead this should take the path relative to the model directory
-			//       but the current implementation does not allow this
-			files.Store(filepath.Base(f), digest)
-			return nil
-		})
+			fileMap[filepath.Base(f)] = digest
+		}
+		req.Files = fileMap
 	}

-	adapters := syncmap.NewSyncMap[string, string]()
-	for f, digest := range req.Adapters {
-		g.Go(func() error {
+	if len(req.Adapters) > 0 {
+		fileMap := map[string]string{}
+		for f, digest := range req.Adapters {
 			if _, err := createBlob(cmd, client, f, digest, p); err != nil {
 				return err
 			}
-
-			// TODO: same here
-			adapters.Store(filepath.Base(f), digest)
-			return nil
-		})
+			fileMap[filepath.Base(f)] = digest
+		}
+		req.Adapters = fileMap
 	}

-	if err := g.Wait(); err != nil {
-		return err
-	}
-
-	req.Files = files.Items()
-	req.Adapters = adapters.Items()
-
 	bars := make(map[string]*progress.Bar)
 	fn := func(resp api.ProgressResponse) error {
 		if resp.Digest != "" {
 			bar, ok := bars[resp.Digest]
 			if !ok {
-				msg := resp.Status
-				if msg == "" {
-					msg = fmt.Sprintf("pulling %s...", resp.Digest[7:19])
-				}
-				bar = progress.NewBar(msg, resp.Total, resp.Completed)
+				bar = progress.NewBar(fmt.Sprintf("pulling %s...", resp.Digest[7:19]), resp.Total, resp.Completed)
 				bars[resp.Digest] = bar
 				p.Add(resp.Digest, bar)
 			}
@@ -253,7 +213,7 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string, digest stri
 		}
 	}()

-	if err := client.CreateBlob(cmd.Context(), digest, io.TeeReader(bin, &pw)); err != nil {
+	if err = client.CreateBlob(cmd.Context(), digest, io.TeeReader(bin, &pw)); err != nil {
 		return "", err
 	}
 	return digest, nil
@@ -283,22 +243,9 @@ func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
 	req := &api.GenerateRequest{
 		Model:     opts.Model,
 		KeepAlive: opts.KeepAlive,
-
-		// pass Think here so we fail before getting to the chat prompt if the model doesn't support it
-		Think: opts.Think,
 	}

-	return client.Generate(cmd.Context(), req, func(r api.GenerateResponse) error {
-		if r.RemoteModel != "" && opts.ShowConnect {
-			p.StopAndClear()
-			if strings.HasPrefix(r.RemoteHost, "https://ollama.com") {
-				fmt.Fprintf(os.Stderr, "Connecting to '%s' on 'ollama.com' ⚡\n", r.RemoteModel)
-			} else {
-				fmt.Fprintf(os.Stderr, "Connecting to '%s' on '%s'\n", r.RemoteModel, r.RemoteHost)
-			}
-		}
-		return nil
-	})
+	return client.Generate(cmd.Context(), req, func(api.GenerateResponse) error { return nil })
 }

 func StopHandler(cmd *cobra.Command, args []string) error {
@@ -319,10 +266,9 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	interactive := true

 	opts := runOptions{
-		Model:       args[0],
-		WordWrap:    os.Getenv("TERM") == "xterm-256color",
-		Options:     map[string]any{},
-		ShowConnect: true,
+		Model:    args[0],
+		WordWrap: os.Getenv("TERM") == "xterm-256color",
+		Options:  map[string]any{},
 	}

 	format, err := cmd.Flags().GetString("format")
@@ -331,34 +277,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	}
 	opts.Format = format

-	thinkFlag := cmd.Flags().Lookup("think")
-	if thinkFlag.Changed {
-		thinkStr, err := cmd.Flags().GetString("think")
-		if err != nil {
-			return err
-		}
-
-		// Handle different values for --think
-		switch thinkStr {
-		case "", "true":
-			// --think or --think=true
-			opts.Think = &api.ThinkValue{Value: true}
-		case "false":
-			opts.Think = &api.ThinkValue{Value: false}
-		case "high", "medium", "low":
-			opts.Think = &api.ThinkValue{Value: thinkStr}
-		default:
-			return fmt.Errorf("invalid value for --think: %q (must be true, false, high, medium, or low)", thinkStr)
-		}
-	} else {
-		opts.Think = nil
-	}
-	hidethinking, err := cmd.Flags().GetBool("hidethinking")
-	if err != nil {
-		return err
-	}
-	opts.HideThinking = hidethinking
-
 	keepAlive, err := cmd.Flags().GetString("keepalive")
 	if err != nil {
 		return err
@@ -380,7 +298,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		}

 		prompts = append([]string{string(in)}, prompts...)
-		opts.ShowConnect = false
 		opts.WordWrap = false
 		interactive = false
 	}
@@ -423,11 +340,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}

-	opts.Think, err = inferThinkingOption(&info.Capabilities, &opts, thinkFlag.Changed)
-	if err != nil {
-		return err
-	}
-
 	opts.MultiModal = slices.Contains(info.Capabilities, model.CapabilityVision)

 	// TODO: remove the projector info and vision info checks below,
@@ -447,15 +359,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {

 	if interactive {
 		if err := loadOrUnloadModel(cmd, &opts); err != nil {
-			var sErr api.AuthorizationError
-			if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
-				fmt.Printf("You need to be signed in to Ollama to run Cloud models.\n\n")
-
-				if sErr.SigninURL != "" {
-					fmt.Printf(ConnectInstructions, sErr.SigninURL)
-				}
-				return nil
-			}
 			return err
 		}

@@ -476,59 +379,6 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	return generate(cmd, opts)
 }

-func SigninHandler(cmd *cobra.Command, args []string) error {
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		return err
-	}
-
-	user, err := client.Whoami(cmd.Context())
-	if err != nil {
-		var aErr api.AuthorizationError
-		if errors.As(err, &aErr) && aErr.StatusCode == http.StatusUnauthorized {
-			fmt.Println("You need to be signed in to Ollama to run Cloud models.")
-			fmt.Println()
-
-			if aErr.SigninURL != "" {
-				fmt.Printf(ConnectInstructions, aErr.SigninURL)
-			}
-			return nil
-		}
-		return err
-	}
-
-	if user != nil && user.Name != "" {
-		fmt.Printf("You are already signed in as user '%s'\n", user.Name)
-		fmt.Println()
-		return nil
-	}
-
-	return nil
-}
-
-func SignoutHandler(cmd *cobra.Command, args []string) error {
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		return err
-	}
-
-	err = client.Signout(cmd.Context())
-	if err != nil {
-		var aErr api.AuthorizationError
-		if errors.As(err, &aErr) && aErr.StatusCode == http.StatusUnauthorized {
-			fmt.Println("You are not signed in to ollama.com")
-			fmt.Println()
-			return nil
-		} else {
-			return err
-		}
-	}
-
-	fmt.Println("You have signed out of ollama.com")
-	fmt.Println()
-	return nil
-}
-
 func PushHandler(cmd *cobra.Command, args []string) error {
 	client, err := api.ClientFromEnvironment()
 	if err != nil {
@@ -581,8 +431,7 @@ func PushHandler(cmd *cobra.Command, args []string) error {
 		if spinner != nil {
 			spinner.Stop()
 		}
-		errStr := strings.ToLower(err.Error())
-		if strings.Contains(errStr, "access denied") || strings.Contains(errStr, "unauthorized") {
+		if strings.Contains(err.Error(), "access denied") {
 			return errors.New("you are not authorized to push to this namespace, create the model under a namespace you own")
 		}
 		return err
@@ -616,14 +465,7 @@ func ListHandler(cmd *cobra.Command, args []string) error {

 	for _, m := range models.Models {
 		if len(args) == 0 || strings.HasPrefix(strings.ToLower(m.Name), strings.ToLower(args[0])) {
-			var size string
-			if m.RemoteModel != "" {
-				size = "-"
-			} else {
-				size = format.HumanBytes(m.Size)
-			}
-
-			data = append(data, []string{m.Name, m.Digest[:12], size, format.HumanTime(m.ModifiedAt, "Never")})
+			data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), format.HumanTime(m.ModifiedAt, "Never")})
 		}
 	}

@@ -677,13 +519,12 @@ func ListRunningHandler(cmd *cobra.Command, args []string) error {
 			} else {
 				until = format.HumanTime(m.ExpiresAt, "Never")
 			}
-			ctxStr := strconv.Itoa(m.ContextLength)
-			data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), procStr, ctxStr, until})
+			data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), procStr, until})
 		}
 	}

 	table := tablewriter.NewWriter(os.Stdout)
-	table.SetHeader([]string{"NAME", "ID", "SIZE", "PROCESSOR", "CONTEXT", "UNTIL"})
+	table.SetHeader([]string{"NAME", "ID", "SIZE", "PROCESSOR", "UNTIL"})
 	table.SetHeaderAlignment(tablewriter.ALIGN_LEFT)
 	table.SetAlignment(tablewriter.ALIGN_LEFT)
 	table.SetHeaderLine(false)
@@ -708,8 +549,8 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
 		KeepAlive: &api.Duration{Duration: 0},
 	}
 	if err := loadOrUnloadModel(cmd, opts); err != nil {
-		if !strings.Contains(strings.ToLower(err.Error()), "not found") {
-			fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
+		if !strings.Contains(err.Error(), "not found") {
+			return fmt.Errorf("unable to stop existing running model \"%s\": %s", args[0], err)
 		}
 	}

@@ -820,36 +661,12 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 	}

 	tableRender("Model", func() (rows [][]string) {
-		if resp.RemoteHost != "" {
-			rows = append(rows, []string{"", "Remote model", resp.RemoteModel})
-			rows = append(rows, []string{"", "Remote URL", resp.RemoteHost})
-		}
-
 		if resp.ModelInfo != nil {
 			arch := resp.ModelInfo["general.architecture"].(string)
 			rows = append(rows, []string{"", "architecture", arch})
-
-			var paramStr string
-			if resp.Details.ParameterSize != "" {
-				paramStr = resp.Details.ParameterSize
-			} else if v, ok := resp.ModelInfo["general.parameter_count"]; ok {
-				if f, ok := v.(float64); ok {
-					paramStr = format.HumanNumber(uint64(f))
-				}
-			}
-			rows = append(rows, []string{"", "parameters", paramStr})
-
-			if v, ok := resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)]; ok {
-				if f, ok := v.(float64); ok {
-					rows = append(rows, []string{"", "context length", strconv.FormatFloat(f, 'f', -1, 64)})
-				}
-			}
-
-			if v, ok := resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)]; ok {
-				if f, ok := v.(float64); ok {
-					rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(f, 'f', -1, 64)})
-				}
-			}
+			rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ModelInfo["general.parameter_count"].(float64)))})
+			rows = append(rows, []string{"", "context length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64), 'f', -1, 64)})
+			rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64), 'f', -1, 64)})
 		} else {
 			rows = append(rows, []string{"", "architecture", resp.Details.Family})
 			rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
@@ -908,38 +725,11 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 				case float64:
 					v = fmt.Sprintf("%g", vData)
 				case []any:
-					targetWidth := 10 // Small width where we are displaying the data in a column
-
-					var itemsToShow int
-					totalWidth := 1 // Start with 1 for opening bracket
-
-					// Find how many we can fit
-					for i := range vData {
-						itemStr := fmt.Sprintf("%v", vData[i])
-						width := runewidth.StringWidth(itemStr)
-
-						// Add separator width (", ") for all items except the first
-						if i > 0 {
-							width += 2
-						}
-
-						// Check if adding this item would exceed our width limit
-						if totalWidth+width > targetWidth && i > 0 {
-							break
-						}
-
-						totalWidth += width
-						itemsToShow++
-					}
-
-					// Format the output
-					if itemsToShow < len(vData) {
-						v = fmt.Sprintf("%v", vData[:itemsToShow])
-						v = strings.TrimSuffix(v, "]")
-						v += fmt.Sprintf(" ...+%d more]", len(vData)-itemsToShow)
-					} else {
-						v = fmt.Sprintf("%v", vData)
+					n := 3
+					if len(vData) < n {
+						n = len(vData)
 					}
+					v = fmt.Sprintf("%v", vData[:n])
 				default:
 					v = fmt.Sprintf("%T", vData)
 				}
@@ -960,19 +750,10 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {

 	head := func(s string, n int) (rows [][]string) {
 		scanner := bufio.NewScanner(strings.NewReader(s))
-		count := 0
-		for scanner.Scan() {
-			text := strings.TrimSpace(scanner.Text())
-			if text == "" {
-				continue
+		for scanner.Scan() && (len(rows) < n || n < 0) {
+			if text := scanner.Text(); text != "" {
+				rows = append(rows, []string{"", strings.TrimSpace(text)})
 			}
-			count++
-			if n < 0 || count <= n {
-				rows = append(rows, []string{"", text})
-			}
-		}
-		if n >= 0 && count > n {
-			rows = append(rows, []string{"", "..."})
 		}
 		return
 	}
@@ -1084,20 +865,17 @@ func PullHandler(cmd *cobra.Command, args []string) error {
 type generateContextKey string

 type runOptions struct {
-	Model        string
-	ParentModel  string
-	Prompt       string
-	Messages     []api.Message
-	WordWrap     bool
-	Format       string
-	System       string
-	Images       []api.ImageData
-	Options      map[string]any
-	MultiModal   bool
-	KeepAlive    *api.Duration
-	Think        *api.ThinkValue
-	HideThinking bool
-	ShowConnect  bool
+	Model       string
+	ParentModel string
+	Prompt      string
+	Messages    []api.Message
+	WordWrap    bool
+	Format      string
+	System      string
+	Images      []api.ImageData
+	Options     map[string]any
+	MultiModal  bool
+	KeepAlive   *api.Duration
 }

 type displayResponseState struct {
@@ -1136,11 +914,10 @@ func displayResponse(content string, wordWrap bool, state *displayResponseState)
 				}

 				switch ch {
-				case ' ', '\t':
+				case ' ':
 					state.wordBuffer = ""
-				case '\n', '\r':
+				case '\n':
 					state.lineLength = 0
-					state.wordBuffer = ""
 				default:
 					state.wordBuffer += string(ch)
 				}
@@ -1154,26 +931,6 @@ func displayResponse(content string, wordWrap bool, state *displayResponseState)
 	}
 }

-func thinkingOutputOpeningText(plainText bool) string {
-	text := "Thinking...\n"
-
-	if plainText {
-		return text
-	}
-
-	return readline.ColorGrey + readline.ColorBold + text + readline.ColorDefault + readline.ColorGrey
-}
-
-func thinkingOutputClosingText(plainText bool) string {
-	text := "...done thinking.\n\n"
-
-	if plainText {
-		return text
-	}
-
-	return readline.ColorGrey + readline.ColorBold + text + readline.ColorDefault
-}
-
 func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
 	client, err := api.ClientFromEnvironment()
 	if err != nil {
@@ -1198,55 +955,19 @@ func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
 	}()

 	var state *displayResponseState = &displayResponseState{}
-	var thinkingContent strings.Builder
 	var latest api.ChatResponse
 	var fullResponse strings.Builder
-	var thinkTagOpened bool = false
-	var thinkTagClosed bool = false
-
-	role := "assistant"
+	var role string

 	fn := func(response api.ChatResponse) error {
-		if response.Message.Content != "" || !opts.HideThinking {
-			p.StopAndClear()
-		}
+		p.StopAndClear()

 		latest = response

 		role = response.Message.Role
-		if response.Message.Thinking != "" && !opts.HideThinking {
-			if !thinkTagOpened {
-				fmt.Print(thinkingOutputOpeningText(false))
-				thinkTagOpened = true
-				thinkTagClosed = false
-			}
-			thinkingContent.WriteString(response.Message.Thinking)
-			displayResponse(response.Message.Thinking, opts.WordWrap, state)
-		}
-
 		content := response.Message.Content
-		if thinkTagOpened && !thinkTagClosed && (content != "" || len(response.Message.ToolCalls) > 0) {
-			if !strings.HasSuffix(thinkingContent.String(), "\n") {
-				fmt.Println()
-			}
-			fmt.Print(thinkingOutputClosingText(false))
-			thinkTagOpened = false
-			thinkTagClosed = true
-			state = &displayResponseState{}
-		}
-		// purposefully not putting thinking blocks in the response, which would
-		// only be needed if we later added tool calling to the cli (they get
-		// filtered out anyway since current models don't expect them unless you're
-		// about to finish some tool calls)
 		fullResponse.WriteString(content)

-		if response.Message.ToolCalls != nil {
-			toolCalls := response.Message.ToolCalls
-			if len(toolCalls) > 0 {
-				fmt.Print(renderToolCalls(toolCalls, false))
-			}
-		}
-
 		displayResponse(content, opts.WordWrap, state)

 		return nil
@@ -1261,7 +982,6 @@ func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
 		Messages: opts.Messages,
 		Format:   json.RawMessage(opts.Format),
 		Options:  opts.Options,
-		Think:    opts.Think,
 	}

 	if opts.KeepAlive != nil {
@@ -1272,14 +992,6 @@ func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
 		if errors.Is(err, context.Canceled) {
 			return nil, nil
 		}
-
-		// this error should ideally be wrapped properly by the client
-		if strings.Contains(err.Error(), "upstream error") {
-			p.StopAndClear()
-			fmt.Println("An error occurred while processing your message. Please try again.")
-			fmt.Println()
-			return nil, nil
-		}
 		return nil, err
 	}

@@ -1331,49 +1043,15 @@ func generate(cmd *cobra.Command, opts runOptions) error {
 	}()

 	var state *displayResponseState = &displayResponseState{}
-	var thinkingContent strings.Builder
-	var thinkTagOpened bool = false
-	var thinkTagClosed bool = false
-
-	plainText := !term.IsTerminal(int(os.Stdout.Fd()))

 	fn := func(response api.GenerateResponse) error {
+		p.StopAndClear()
+
 		latest = response
 		content := response.Response

-		if response.Response != "" || !opts.HideThinking {
-			p.StopAndClear()
-		}
-
-		if response.Thinking != "" && !opts.HideThinking {
-			if !thinkTagOpened {
-				fmt.Print(thinkingOutputOpeningText(plainText))
-				thinkTagOpened = true
-				thinkTagClosed = false
-			}
-			thinkingContent.WriteString(response.Thinking)
-			displayResponse(response.Thinking, opts.WordWrap, state)
-		}
-
-		if thinkTagOpened && !thinkTagClosed && (content != "" || len(response.ToolCalls) > 0) {
-			if !strings.HasSuffix(thinkingContent.String(), "\n") {
-				fmt.Println()
-			}
-			fmt.Print(thinkingOutputClosingText(plainText))
-			thinkTagOpened = false
-			thinkTagClosed = true
-			state = &displayResponseState{}
-		}
-
 		displayResponse(content, opts.WordWrap, state)

-		if response.ToolCalls != nil {
-			toolCalls := response.ToolCalls
-			if len(toolCalls) > 0 {
-				fmt.Print(renderToolCalls(toolCalls, plainText))
-			}
-		}
-
 		return nil
 	}

@@ -1397,7 +1075,6 @@ func generate(cmd *cobra.Command, opts runOptions) error {
 		System:    opts.System,
 		Options:   opts.Options,
 		KeepAlive: opts.KeepAlive,
-		Think:     opts.Think,
 	}

 	if err := client.Generate(ctx, &request, fn); err != nil {
@@ -1501,11 +1178,11 @@ func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
 		return err
 	}
 	if err := client.Heartbeat(cmd.Context()); err != nil {
-		if !(strings.Contains(err.Error(), " refused") || strings.Contains(err.Error(), "could not connect")) {
+		if !strings.Contains(err.Error(), " refused") {
 			return err
 		}
 		if err := startApp(cmd.Context(), client); err != nil {
-			return fmt.Errorf("ollama server not responding - %w", err)
+			return errors.New("could not connect to ollama app, is it running?")
 		}
 	}
 	return nil
@@ -1576,14 +1253,14 @@ func NewCLI() *cobra.Command {

 	createCmd := &cobra.Command{
 		Use:     "create MODEL",
-		Short:   "Create a model",
+		Short:   "Create a model from a Modelfile",
 		Args:    cobra.ExactArgs(1),
 		PreRunE: checkServerHeartbeat,
 		RunE:    CreateHandler,
 	}

-	createCmd.Flags().StringP("file", "f", "", "Name of the Modelfile (default \"Modelfile\")")
-	createCmd.Flags().StringP("quantize", "q", "", "Quantize model to this level (e.g. q4_K_M)")
+	createCmd.Flags().StringP("file", "f", "", "Name of the Modelfile (default \"Modelfile\"")
+	createCmd.Flags().StringP("quantize", "q", "", "Quantize model to this level (e.g. q4_0)")

 	showCmd := &cobra.Command{
 		Use:     "show MODEL",
@@ -1613,9 +1290,6 @@ func NewCLI() *cobra.Command {
 	runCmd.Flags().Bool("insecure", false, "Use an insecure registry")
 	runCmd.Flags().Bool("nowordwrap", false, "Don't wrap words to the next line automatically")
 	runCmd.Flags().String("format", "", "Response format (e.g. json)")
-	runCmd.Flags().String("think", "", "Enable thinking mode: true/false or high/medium/low for supported models")
-	runCmd.Flags().Lookup("think").NoOptDefVal = "true"
-	runCmd.Flags().Bool("hidethinking", false, "Hide thinking output (if provided)")

 	stopCmd := &cobra.Command{
 		Use:     "stop MODEL",
@@ -1653,22 +1327,6 @@ func NewCLI() *cobra.Command {

 	pushCmd.Flags().Bool("insecure", false, "Use an insecure registry")

-	signinCmd := &cobra.Command{
-		Use:     "signin",
-		Short:   "Sign in to ollama.com",
-		Args:    cobra.ExactArgs(0),
-		PreRunE: checkServerHeartbeat,
-		RunE:    SigninHandler,
-	}
-
-	signoutCmd := &cobra.Command{
-		Use:     "signout",
-		Short:   "Sign out from ollama.com",
-		Args:    cobra.ExactArgs(0),
-		PreRunE: checkServerHeartbeat,
-		RunE:    SignoutHandler,
-	}
-
 	listCmd := &cobra.Command{
 		Use:     "list",
 		Aliases: []string{"ls"},
@@ -1683,6 +1341,7 @@ func NewCLI() *cobra.Command {
 		PreRunE: checkServerHeartbeat,
 		RunE:    ListRunningHandler,
 	}
+
 	copyCmd := &cobra.Command{
 		Use:     "cp SOURCE DESTINATION",
 		Short:   "Copy a model",
@@ -1735,7 +1394,6 @@ func NewCLI() *cobra.Command {
 			appendEnvDocs(cmd, []envconfig.EnvVar{
 				envVars["OLLAMA_DEBUG"],
 				envVars["OLLAMA_HOST"],
-				envVars["OLLAMA_CONTEXT_LENGTH"],
 				envVars["OLLAMA_KEEP_ALIVE"],
 				envVars["OLLAMA_MAX_LOADED_MODELS"],
 				envVars["OLLAMA_MAX_QUEUE"],
@@ -1749,6 +1407,7 @@ func NewCLI() *cobra.Command {
 				envVars["OLLAMA_LLM_LIBRARY"],
 				envVars["OLLAMA_GPU_OVERHEAD"],
 				envVars["OLLAMA_LOAD_TIMEOUT"],
+				envVars["OLLAMA_CONTEXT_LENGTH"],
 			})
 		default:
 			appendEnvDocs(cmd, envs)
@@ -1763,8 +1422,6 @@ func NewCLI() *cobra.Command {
 		stopCmd,
 		pullCmd,
 		pushCmd,
-		signinCmd,
-		signoutCmd,
 		listCmd,
 		psCmd,
 		copyCmd,
@@ -1774,70 +1431,3 @@ func NewCLI() *cobra.Command {

 	return rootCmd
 }
-
-// If the user has explicitly set thinking options, either through the CLI or
-// through the `/set think` or `set nothink` interactive options, then we
-// respect them. Otherwise, we check model capabilities to see if the model
-// supports thinking. If the model does support thinking, we enable it.
-// Otherwise, we unset the thinking option (which is different than setting it
-// to false).
-//
-// If capabilities are not provided, we fetch them from the server.
-func inferThinkingOption(caps *[]model.Capability, runOpts *runOptions, explicitlySetByUser bool) (*api.ThinkValue, error) {
-	if explicitlySetByUser {
-		return runOpts.Think, nil
-	}
-
-	if caps == nil {
-		client, err := api.ClientFromEnvironment()
-		if err != nil {
-			return nil, err
-		}
-		ret, err := client.Show(context.Background(), &api.ShowRequest{
-			Model: runOpts.Model,
-		})
-		if err != nil {
-			return nil, err
-		}
-		caps = &ret.Capabilities
-	}
-
-	thinkingSupported := false
-	for _, cap := range *caps {
-		if cap == model.CapabilityThinking {
-			thinkingSupported = true
-		}
-	}
-
-	if thinkingSupported {
-		return &api.ThinkValue{Value: true}, nil
-	}
-
-	return nil, nil
-}
-
-func renderToolCalls(toolCalls []api.ToolCall, plainText bool) string {
-	out := ""
-	formatExplanation := ""
-	formatValues := ""
-	if !plainText {
-		formatExplanation = readline.ColorGrey + readline.ColorBold
-		formatValues = readline.ColorDefault
-		out += formatExplanation
-	}
-	for i, toolCall := range toolCalls {
-		argsAsJSON, err := json.Marshal(toolCall.Function.Arguments)
-		if err != nil {
-			return ""
-		}
-		if i > 0 {
-			out += "\n"
-		}
-		// all tool calls are unexpected since we don't currently support registering any in the CLI
-		out += fmt.Sprintf("  Model called a non-existent function '%s()' with arguments: %s", formatValues+toolCall.Function.Name+formatExplanation, formatValues+string(argsAsJSON)+formatExplanation)
-	}
-	if !plainText {
-		out += readline.ColorDefault
-	}
-	return out
-}
--- a/cmd/cmd_test.go
+++ b/cmd/cmd_test.go
@@ -2,8 +2,8 @@ package cmd

 import (
 	"bytes"
+	"context"
 	"encoding/json"
-	"fmt"
 	"io"
 	"net/http"
 	"net/http/httptest"
@@ -226,7 +226,6 @@ Weigh anchor!
  System
    You are a pirate!    
    Ahoy, matey!         
-    ...                  

 `
 		if diff := cmp.Diff(expect, b.String()); diff != "" {
@@ -305,8 +304,6 @@ func TestDeleteHandler(t *testing.T) {
 				w.WriteHeader(http.StatusOK)
 			} else {
 				w.WriteHeader(http.StatusNotFound)
-				errPayload := `{"error":"model '%s' not found"}`
-				w.Write([]byte(fmt.Sprintf(errPayload, req.Name)))
 			}
 			return
 		}
@@ -340,7 +337,7 @@ func TestDeleteHandler(t *testing.T) {
 	t.Cleanup(mockServer.Close)

 	cmd := &cobra.Command{}
-	cmd.SetContext(t.Context())
+	cmd.SetContext(context.TODO())
 	if err := DeleteHandler(cmd, []string{"test-model"}); err != nil {
 		t.Fatalf("DeleteHandler failed: %v", err)
 	}
@@ -349,7 +346,7 @@ func TestDeleteHandler(t *testing.T) {
 	}

 	err := DeleteHandler(cmd, []string{"test-model-not-found"})
-	if err == nil || !strings.Contains(err.Error(), "model 'test-model-not-found' not found") {
+	if err == nil || !strings.Contains(err.Error(), "unable to stop existing running model \"test-model-not-found\"") {
 		t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err)
 	}
 }
@@ -402,6 +399,11 @@ func TestGetModelfileName(t *testing.T) {
 			var expectedFilename string

 			if tt.fileExists {
+				tempDir, err := os.MkdirTemp("", "modelfiledir")
+				defer os.RemoveAll(tempDir)
+				if err != nil {
+					t.Fatalf("temp modelfile dir creation failed: %v", err)
+				}
 				var fn string
 				if tt.modelfileName != "" {
 					fn = tt.modelfileName
@@ -409,7 +411,7 @@ func TestGetModelfileName(t *testing.T) {
 					fn = "Modelfile"
 				}

-				tempFile, err := os.CreateTemp(t.TempDir(), fn)
+				tempFile, err := os.CreateTemp(tempDir, fn)
 				if err != nil {
 					t.Fatalf("temp modelfile creation failed: %v", err)
 				}
@@ -502,7 +504,7 @@ func TestPushHandler(t *testing.T) {
 					w.Header().Set("Content-Type", "application/json")
 					w.WriteHeader(http.StatusUnauthorized)
 					err := json.NewEncoder(w).Encode(map[string]string{
-						"error": "403: {\"errors\":[{\"code\":\"ACCESS DENIED\", \"message\":\"access denied\"}]}",
+						"error": "access denied",
 					})
 					if err != nil {
 						t.Fatal(err)
@@ -525,14 +527,10 @@ func TestPushHandler(t *testing.T) {
 			defer mockServer.Close()

 			t.Setenv("OLLAMA_HOST", mockServer.URL)
-			tmpDir := t.TempDir()
-			t.Setenv("HOME", tmpDir)
-			t.Setenv("USERPROFILE", tmpDir)
-			initializeKeypair()

 			cmd := &cobra.Command{}
 			cmd.Flags().Bool("insecure", false, "")
-			cmd.SetContext(t.Context())
+			cmd.SetContext(context.TODO())

 			// Redirect stderr to capture progress output
 			oldStderr := os.Stderr
@@ -637,7 +635,7 @@ func TestListHandler(t *testing.T) {
 			t.Setenv("OLLAMA_HOST", mockServer.URL)

 			cmd := &cobra.Command{}
-			cmd.SetContext(t.Context())
+			cmd.SetContext(context.TODO())

 			// Capture stdout
 			oldStdout := os.Stdout
@@ -692,7 +690,7 @@ func TestCreateHandler(t *testing.T) {
 						return
 					}

-					if req.Model != "test-model" {
+					if req.Name != "test-model" {
 						t.Errorf("expected model name 'test-model', got %s", req.Name)
 					}

@@ -732,7 +730,7 @@ func TestCreateHandler(t *testing.T) {
 			}))
 			t.Setenv("OLLAMA_HOST", mockServer.URL)
 			t.Cleanup(mockServer.Close)
-			tempFile, err := os.CreateTemp(t.TempDir(), "modelfile")
+			tempFile, err := os.CreateTemp("", "modelfile")
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -752,7 +750,7 @@ func TestCreateHandler(t *testing.T) {
 			}

 			cmd.Flags().Bool("insecure", false, "")
-			cmd.SetContext(t.Context())
+			cmd.SetContext(context.TODO())

 			// Redirect stderr to capture progress output
 			oldStderr := os.Stderr
--- a/cmd/interactive.go
+++ b/cmd/interactive.go
@@ -44,7 +44,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "Use \"\"\" to begin a multi-line message.")

 		if opts.MultiModal {
-			fmt.Fprintf(os.Stderr, "Use %s to include .jpg, .png, or .webp images.\n", filepath.FromSlash("/path/to/file"))
+			fmt.Fprintf(os.Stderr, "Use %s to include .jpg or .png images.\n", filepath.FromSlash("/path/to/file"))
 		}

 		fmt.Fprintln(os.Stderr, "")
@@ -62,8 +62,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "  /set noformat          Disable formatting")
 		fmt.Fprintln(os.Stderr, "  /set verbose           Show LLM stats")
 		fmt.Fprintln(os.Stderr, "  /set quiet             Disable LLM stats")
-		fmt.Fprintln(os.Stderr, "  /set think             Enable thinking")
-		fmt.Fprintln(os.Stderr, "  /set nothink           Disable thinking")
 		fmt.Fprintln(os.Stderr, "")
 	}

@@ -130,7 +128,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {

 	var sb strings.Builder
 	var multiline MultilineState
-	var thinkExplicitlySet bool = opts.Think != nil

 	for {
 		line, err := scanner.Readline()
@@ -198,19 +195,11 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 			opts.Model = args[1]
 			opts.Messages = []api.Message{}
 			fmt.Printf("Loading model '%s'\n", opts.Model)
-			opts.Think, err = inferThinkingOption(nil, &opts, thinkExplicitlySet)
-			if err != nil {
-				return err
-			}
 			if err := loadOrUnloadModel(cmd, &opts); err != nil {
 				if strings.Contains(err.Error(), "not found") {
 					fmt.Printf("error: %v\n", err)
 					continue
 				}
-				if strings.Contains(err.Error(), "does not support thinking") {
-					fmt.Printf("error: %v\n", err)
-					continue
-				}
 				return err
 			}
 			continue
@@ -271,35 +260,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						return err
 					}
 					fmt.Println("Set 'quiet' mode.")
-				case "think":
-					thinkValue := api.ThinkValue{Value: true}
-					var maybeLevel string
-					if len(args) > 2 {
-						maybeLevel = args[2]
-					}
-					if maybeLevel != "" {
-						// TODO(drifkin): validate the level, could be model dependent
-						// though... It will also be validated on the server once a call is
-						// made.
-						thinkValue.Value = maybeLevel
-					}
-					opts.Think = &thinkValue
-					thinkExplicitlySet = true
-					if client, err := api.ClientFromEnvironment(); err == nil {
-						ensureThinkingSupport(cmd.Context(), client, opts.Model)
-					}
-					if maybeLevel != "" {
-						fmt.Printf("Set 'think' mode to '%s'.\n", maybeLevel)
-					} else {
-						fmt.Println("Set 'think' mode.")
-					}
-				case "nothink":
-					opts.Think = &api.ThinkValue{Value: false}
-					thinkExplicitlySet = true
-					if client, err := api.ClientFromEnvironment(); err == nil {
-						ensureThinkingSupport(cmd.Context(), client, opts.Model)
-					}
-					fmt.Println("Set 'nothink' mode.")
 				case "format":
 					if len(args) < 3 || args[2] != "json" {
 						fmt.Println("Invalid or missing format. For 'json' mode use '/set format json'")
@@ -398,21 +358,18 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 				case "modelfile":
 					fmt.Println(resp.Modelfile)
 				case "parameters":
-					fmt.Println("Model defined parameters:")
 					if resp.Parameters == "" {
-						fmt.Println("  No additional parameters were specified for this model.")
+						fmt.Println("No parameters were specified for this model.")
 					} else {
-						for _, l := range strings.Split(resp.Parameters, "\n") {
-							fmt.Printf("  %s\n", l)
+						if len(opts.Options) > 0 {
+							fmt.Println("User defined parameters:")
+							for k, v := range opts.Options {
+								fmt.Printf("%-*s %v\n", 30, k, v)
+							}
+							fmt.Println()
 						}
-					}
-					fmt.Println()
-					if len(opts.Options) > 0 {
-						fmt.Println("User defined parameters:")
-						for k, v := range opts.Options {
-							fmt.Printf("  %-*s %v\n", 30, k, v)
-						}
-						fmt.Println()
+						fmt.Println("Model defined parameters:")
+						fmt.Println(resp.Parameters)
 					}
 				case "system":
 					switch {
@@ -491,12 +448,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {

 			assistant, err := chat(cmd, opts)
 			if err != nil {
-				if strings.Contains(err.Error(), "does not support thinking") ||
-					strings.Contains(err.Error(), "invalid think value") {
-					fmt.Printf("error: %v\n", err)
-					sb.Reset()
-					continue
-				}
 				return err
 			}
 			if assistant != nil {
@@ -560,7 +511,7 @@ func extractFileNames(input string) []string {
 	// Regex to match file paths starting with optional drive letter, / ./ \ or .\ and include escaped or unescaped spaces (\ or %20)
 	// and followed by more characters and a file extension
 	// This will capture non filename strings, but we'll check for file existence to remove mismatches
-	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png|webp)\b`
+	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png)\b`
 	re := regexp.MustCompile(regexPattern)

 	return re.FindAllString(input, -1)
@@ -580,8 +531,6 @@ func extractFileData(input string) (string, []api.ImageData, error) {
 			return "", imgs, err
 		}
 		fmt.Fprintf(os.Stderr, "Added image '%s'\n", nfp)
-		input = strings.ReplaceAll(input, "'"+nfp+"'", "")
-		input = strings.ReplaceAll(input, "'"+fp+"'", "")
 		input = strings.ReplaceAll(input, fp, "")
 		imgs = append(imgs, data)
 	}
@@ -602,7 +551,7 @@ func getImageData(filePath string) ([]byte, error) {
 	}

 	contentType := http.DetectContentType(buf)
-	allowedTypes := []string{"image/jpeg", "image/jpg", "image/png", "image/webp"}
+	allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
 	if !slices.Contains(allowedTypes, contentType) {
 		return nil, fmt.Errorf("invalid image type: %s", contentType)
 	}
--- a/cmd/interactive_test.go
+++ b/cmd/interactive_test.go
@@ -1,8 +1,6 @@
 package cmd

 import (
-	"os"
-	"path/filepath"
 	"testing"

 	"github.com/stretchr/testify/assert"
@@ -12,17 +10,14 @@ func TestExtractFilenames(t *testing.T) {
 	// Unix style paths
 	input := ` some preamble 
 ./relative\ path/one.png inbetween1 ./not a valid two.jpg inbetween2 ./1.svg
-/unescaped space /three.jpeg inbetween3 /valid\ path/dir/four.png "./quoted with spaces/five.JPG
-/unescaped space /six.webp inbetween6 /valid\ path/dir/seven.WEBP`
+/unescaped space /three.jpeg inbetween3 /valid\ path/dir/four.png "./quoted with spaces/five.JPG`
 	res := extractFileNames(input)
-	assert.Len(t, res, 7)
+	assert.Len(t, res, 5)
 	assert.Contains(t, res[0], "one.png")
 	assert.Contains(t, res[1], "two.jpg")
 	assert.Contains(t, res[2], "three.jpeg")
 	assert.Contains(t, res[3], "four.png")
 	assert.Contains(t, res[4], "five.JPG")
-	assert.Contains(t, res[5], "six.webp")
-	assert.Contains(t, res[6], "seven.WEBP")
 	assert.NotContains(t, res[4], '"')
 	assert.NotContains(t, res, "inbetween1")
 	assert.NotContains(t, res, "./1.svg")
@@ -33,12 +28,10 @@ func TestExtractFilenames(t *testing.T) {
 /absolute/nospace/three.jpeg inbetween3 /absolute/with space/four.png inbetween4
 ./relative\ path/five.JPG inbetween5 "./relative with/spaces/six.png inbetween6
 d:\path with\spaces\seven.JPEG inbetween7 c:\users\jdoe\eight.png inbetween8 
- d:\program files\someplace\nine.png inbetween9 "E:\program files\someplace\ten.PNG
-c:/users/jdoe/eleven.webp inbetween11 c:/program files/someplace/twelve.WebP inbetween12
-d:\path with\spaces\thirteen.WEBP some ending
+ d:\program files\someplace\nine.png inbetween9 "E:\program files\someplace\ten.PNG some ending
 `
 	res = extractFileNames(input)
-	assert.Len(t, res, 13)
+	assert.Len(t, res, 10)
 	assert.NotContains(t, res, "inbetween2")
 	assert.Contains(t, res[0], "one.png")
 	assert.Contains(t, res[0], "c:")
@@ -56,31 +49,4 @@ d:\path with\spaces\thirteen.WEBP some ending
 	assert.Contains(t, res[8], "d:")
 	assert.Contains(t, res[9], "ten.PNG")
 	assert.Contains(t, res[9], "E:")
-	assert.Contains(t, res[10], "eleven.webp")
-	assert.Contains(t, res[10], "c:")
-	assert.Contains(t, res[11], "twelve.WebP")
-	assert.Contains(t, res[11], "c:")
-	assert.Contains(t, res[12], "thirteen.WEBP")
-	assert.Contains(t, res[12], "d:")
-}
-
-// Ensure that file paths wrapped in single quotes are removed with the quotes.
-func TestExtractFileDataRemovesQuotedFilepath(t *testing.T) {
-	dir := t.TempDir()
-	fp := filepath.Join(dir, "img.jpg")
-	data := make([]byte, 600)
-	copy(data, []byte{
-		0xff, 0xd8, 0xff, 0xe0, 0x00, 0x10, 'J', 'F', 'I', 'F',
-		0x00, 0x01, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-		0xff, 0xd9,
-	})
-	if err := os.WriteFile(fp, data, 0o600); err != nil {
-		t.Fatalf("failed to write test image: %v", err)
-	}
-
-	input := "before '" + fp + "' after"
-	cleaned, imgs, err := extractFileData(input)
-	assert.NoError(t, err)
-	assert.Len(t, imgs, 1)
-	assert.Equal(t, cleaned, "before  after")
 }
--- a/cmd/start_darwin.go
+++ b/cmd/start_darwin.go
@@ -5,7 +5,7 @@ import (
 	"errors"
 	"os"
 	"os/exec"
-	"regexp"
+	"strings"

 	"github.com/ollama/ollama/api"
 )
@@ -19,12 +19,11 @@ func startApp(ctx context.Context, client *api.Client) error {
 	if err != nil {
 		return err
 	}
-	r := regexp.MustCompile(`^.*/Ollama\s?\d*.app`)
-	m := r.FindStringSubmatch(link)
-	if len(m) != 1 {
+	if !strings.Contains(link, "Ollama.app") {
 		return errors.New("could not find ollama app")
 	}
-	if err := exec.Command("/usr/bin/open", "-j", "-a", m[0], "--args", "--fast-startup").Run(); err != nil {
+	path := strings.Split(link, "Ollama.app")
+	if err := exec.Command("/usr/bin/open", "-a", path[0]+"Ollama.app").Run(); err != nil {
 		return err
 	}
 	return waitForServer(ctx, client)
--- a/cmd/start_windows.go
+++ b/cmd/start_windows.go
@@ -4,27 +4,17 @@ import (
 	"context"
 	"errors"
 	"fmt"
-	"log/slog"
 	"os"
 	"os/exec"
-	"path"
 	"path/filepath"
 	"strings"
 	"syscall"
-	"unsafe"

 	"github.com/ollama/ollama/api"
-	"golang.org/x/sys/windows"
-)
-
-const (
-	Installer = "OllamaSetup.exe"
 )

 func startApp(ctx context.Context, client *api.Client) error {
-	if len(isProcRunning(Installer)) > 0 {
-		return fmt.Errorf("upgrade in progress...")
-	}
+	// log.Printf("XXX Attempting to find and start ollama app")
 	AppName := "ollama app.exe"
 	exe, err := os.Executable()
 	if err != nil {
@@ -45,11 +35,14 @@ func startApp(ctx context.Context, client *api.Client) error {
 			}
 		}
 	}
+	// log.Printf("XXX attempting to start app %s", appExe)

 	cmd_path := "c:\\Windows\\system32\\cmd.exe"
-	cmd := exec.Command(cmd_path, "/c", appExe, "--hide", "--fast-startup")
+	cmd := exec.Command(cmd_path, "/c", appExe)
+	// TODO - these hide flags aren't working - still pops up a command window for some reason
 	cmd.SysProcAttr = &syscall.SysProcAttr{CreationFlags: 0x08000000, HideWindow: true}

+	// TODO this didn't help either...
 	cmd.Stdin = strings.NewReader("")
 	cmd.Stdout = os.Stdout
 	cmd.Stderr = os.Stderr
@@ -63,50 +56,3 @@ func startApp(ctx context.Context, client *api.Client) error {
 	}
 	return waitForServer(ctx, client)
 }
-
-func isProcRunning(procName string) []uint32 {
-	pids := make([]uint32, 2048)
-	var ret uint32
-	if err := windows.EnumProcesses(pids, &ret); err != nil || ret == 0 {
-		slog.Debug("failed to check for running installers", "error", err)
-		return nil
-	}
-	if ret > uint32(len(pids)) {
-		pids = make([]uint32, ret+10)
-		if err := windows.EnumProcesses(pids, &ret); err != nil || ret == 0 {
-			slog.Debug("failed to check for running installers", "error", err)
-			return nil
-		}
-	}
-	if ret < uint32(len(pids)) {
-		pids = pids[:ret]
-	}
-	var matches []uint32
-	for _, pid := range pids {
-		if pid == 0 {
-			continue
-		}
-		hProcess, err := windows.OpenProcess(windows.PROCESS_QUERY_INFORMATION|windows.PROCESS_VM_READ, false, pid)
-		if err != nil {
-			continue
-		}
-		defer windows.CloseHandle(hProcess)
-		var module windows.Handle
-		var cbNeeded uint32
-		cb := (uint32)(unsafe.Sizeof(module))
-		if err := windows.EnumProcessModules(hProcess, &module, cb, &cbNeeded); err != nil {
-			continue
-		}
-		var sz uint32 = 1024 * 8
-		moduleName := make([]uint16, sz)
-		cb = uint32(len(moduleName)) * (uint32)(unsafe.Sizeof(uint16(0)))
-		if err := windows.GetModuleBaseName(hProcess, module, &moduleName[0], cb); err != nil && err != syscall.ERROR_INSUFFICIENT_BUFFER {
-			continue
-		}
-		exeFile := path.Base(strings.ToLower(syscall.UTF16ToString(moduleName)))
-		if strings.EqualFold(exeFile, procName) {
-			matches = append(matches, pid)
-		}
-	}
-	return matches
-}
--- a/cmd/warn_thinking_test.go
+++ b/cmd/warn_thinking_test.go
@@ -1,63 +0,0 @@
-package cmd
-
-import (
-	"encoding/json"
-	"io"
-	"net/http"
-	"net/http/httptest"
-	"os"
-	"strings"
-	"testing"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/types/model"
-)
-
-// Test that a warning is printed when thinking is requested but not supported.
-func TestWarnMissingThinking(t *testing.T) {
-	cases := []struct {
-		capabilities []model.Capability
-		expectWarn   bool
-	}{
-		{capabilities: []model.Capability{model.CapabilityThinking}, expectWarn: false},
-		{capabilities: []model.Capability{}, expectWarn: true},
-	}
-
-	for _, tc := range cases {
-		srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-			if r.URL.Path != "/api/show" || r.Method != http.MethodPost {
-				t.Fatalf("unexpected request to %s %s", r.URL.Path, r.Method)
-			}
-			var req api.ShowRequest
-			if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-				t.Fatalf("decode request: %v", err)
-			}
-			resp := api.ShowResponse{Capabilities: tc.capabilities}
-			if err := json.NewEncoder(w).Encode(resp); err != nil {
-				t.Fatalf("encode response: %v", err)
-			}
-		}))
-		defer srv.Close()
-
-		t.Setenv("OLLAMA_HOST", srv.URL)
-		client, err := api.ClientFromEnvironment()
-		if err != nil {
-			t.Fatal(err)
-		}
-		oldStderr := os.Stderr
-		r, w, _ := os.Pipe()
-		os.Stderr = w
-		ensureThinkingSupport(t.Context(), client, "m")
-		w.Close()
-		os.Stderr = oldStderr
-		out, _ := io.ReadAll(r)
-
-		warned := strings.Contains(string(out), "warning:")
-		if tc.expectWarn && !warned {
-			t.Errorf("expected warning, got none")
-		}
-		if !tc.expectWarn && warned {
-			t.Errorf("did not expect warning, got: %s", string(out))
-		}
-	}
-}
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -1,13 +1,12 @@
 package convert

 import (
-	"cmp"
 	"encoding/json"
 	"errors"
 	"fmt"
+	"io"
 	"io/fs"
 	"log/slog"
-	"os"
 	"slices"
 	"strings"

@@ -15,12 +14,13 @@ import (
 )

 type ModelParameters struct {
-	Architectures []string `json:"architectures"`
-	VocabSize     uint32   `json:"vocab_size"`
+	Architectures []string       `json:"architectures"`
+	VocabSize     uint32         `json:"vocab_size"`
+	TextModel     TextParameters `json:"text_config"`
+}

-	TextModel struct {
-		VocabSize uint32 `json:"vocab_size"`
-	} `json:"text_config"`
+type TextParameters struct {
+	VocabSize uint32 `json:"vocab_size"`
 }

 type AdapterParameters struct {
@@ -53,11 +53,8 @@ func (ModelParameters) KV(t *Tokenizer) ggml.KV {
 	}

 	for _, sv := range t.SpecialVocabulary {
-		kv[fmt.Sprintf("tokenizer.ggml.add_%s_token", sv.Key())] = sv.AddToken
 		kv[fmt.Sprintf("tokenizer.ggml.%s_token_id", sv.Key())] = uint32(sv.ID)
-		if len(sv.IDs) > 0 {
-			kv[fmt.Sprintf("tokenizer.ggml.%s_token_ids", sv.Key())] = sv.IDs
-		}
+		kv[fmt.Sprintf("tokenizer.ggml.add_%s_token", sv.Key())] = sv.AddToken
 	}

 	return kv
@@ -92,7 +89,7 @@ type ModelConverter interface {
 	// KV maps parameters to LLM key-values
 	KV(*Tokenizer) ggml.KV
 	// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
-	Tensors([]Tensor) []*ggml.Tensor
+	Tensors([]Tensor) []ggml.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
 	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
 	Replacements() []string
@@ -109,13 +106,13 @@ type AdapterConverter interface {
 	// KV maps parameters to LLM key-values
 	KV(ggml.KV) ggml.KV
 	// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
-	Tensors([]Tensor) []*ggml.Tensor
+	Tensors([]Tensor) []ggml.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
 	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
 	Replacements() []string
 }

-func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ggml.KV) error {
+func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV ggml.KV) error {
 	bts, err := fs.ReadFile(fsys, "adapter_config.json")
 	if err != nil {
 		return err
@@ -150,14 +147,14 @@ func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ggml.KV) error {
 		return err
 	}

-	return writeFile(f, conv.KV(baseKV), conv.Tensors(ts))
+	return writeFile(ws, conv.KV(baseKV), conv.Tensors(ts))
 }

 // Convert writes an Ollama compatible model to the provided io.WriteSeeker based on configurations
 // and files it finds in the input path.
 // Supported input model formats include safetensors.
 // Supported input tokenizers files include tokenizer.json (preferred) and tokenizer.model.
-func ConvertModel(fsys fs.FS, f *os.File) error {
+func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	bts, err := fs.ReadFile(fsys, "config.json")
 	if err != nil {
 		return err
@@ -176,8 +173,6 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 	switch p.Architectures[0] {
 	case "LlamaForCausalLM":
 		conv = &llamaModel{}
-	case "MllamaForConditionalGeneration":
-		conv = &mllamaModel{}
 	case "Llama4ForConditionalGeneration":
 		conv = &llama4Model{}
 	case "Mistral3ForConditionalGeneration":
@@ -190,20 +185,14 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 		conv = &gemma2Model{}
 	case "Gemma3ForCausalLM", "Gemma3ForConditionalGeneration":
 		conv = &gemma3Model{Architecture: p.Architectures[0]}
-	case "Gemma3nForConditionalGeneration":
-		conv = &gemma3nModel{}
 	case "Phi3ForCausalLM":
 		conv = &phi3Model{}
 	case "Qwen2ForCausalLM":
 		conv = &qwen2Model{}
-	case "Qwen2_5_VLForConditionalGeneration":
-		conv = &qwen25VLModel{}
 	case "BertModel":
 		conv = &bertModel{}
 	case "CohereForCausalLM":
 		conv = &commandrModel{}
-	case "GptOssForCausalLM":
-		conv = &gptossModel{}
 	default:
 		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
 	}
@@ -223,22 +212,24 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 		return err
 	}

-	vocabSize := int(cmp.Or(p.VocabSize, p.TextModel.VocabSize))
+	vocabSize := int(p.VocabSize)
+	if vocabSize == 0 {
+		tVocabSize := int(p.TextModel.VocabSize)
+		vocabSize = tVocabSize
+	}

 	switch {
 	case vocabSize == 0:
-		slog.Debug("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
+		slog.Warn("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
 	case vocabSize > len(t.Vocabulary.Tokens):
-		slog.Debug("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
+		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
 		for i := range vocabSize - len(t.Vocabulary.Tokens) {
 			t.Vocabulary.Tokens = append(t.Vocabulary.Tokens, fmt.Sprintf("[PAD%d]", i))
 			t.Vocabulary.Scores = append(t.Vocabulary.Scores, -1)
 			t.Vocabulary.Types = append(t.Vocabulary.Types, tokenTypeUserDefined)
 		}
 	case vocabSize < len(t.Vocabulary.Tokens):
-		slog.Debug("vocabulary is larger than expected", "want", vocabSize, "got", len(t.Vocabulary.Tokens))
-		p.VocabSize = uint32(len(t.Vocabulary.Tokens))
-		p.TextModel.VocabSize = uint32(len(t.Vocabulary.Tokens))
+		return fmt.Errorf("vocabulary is larger than expected '%d' instead of '%d'", len(t.Vocabulary.Tokens), vocabSize)
 	default:
 		slog.Debug("vocabulary", "size", len(t.Vocabulary.Tokens))
 	}
@@ -248,13 +239,13 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 		return err
 	}

-	return writeFile(f, conv.KV(t), conv.Tensors(ts))
+	return writeFile(ws, conv.KV(t), conv.Tensors(ts))
 }

-func writeFile(f *os.File, kv ggml.KV, ts []*ggml.Tensor) error {
+func writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
 	for i := range ts {
 		ts[i].Shape = slices.Clone(ts[i].Shape)
 		slices.Reverse(ts[i].Shape)
 	}
-	return ggml.WriteGGUF(f, kv, ts)
+	return ggml.WriteGGUF(ws, kv, ts)
 }
--- a/convert/convert_bert.go
+++ b/convert/convert_bert.go
@@ -28,7 +28,6 @@ type bertModel struct {
 	LayerNormEPS          float32 `json:"layer_norm_eps"`
 	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
 	NormEpsilon           float32 `json:"norm_epsilon"`
-	normalizeEmbeddings   bool

 	PoolingType uint32
 }
@@ -55,11 +54,9 @@ func (p *bertModel) parseMore(fsys fs.FS) error {

 	var pooling string
 	for _, m := range modules {
-		switch m.Type {
-		case "sentence_transformers.models.Pooling":
+		if m.Type == "sentence_transformers.models.Pooling" {
 			pooling = m.Path
-		case "sentence_transformers.models.Normalize":
-			p.normalizeEmbeddings = true
+			break
 		}
 	}

@@ -93,7 +90,6 @@ func (p *bertModel) KV(t *Tokenizer) ggml.KV {
 	kv["general.architecture"] = "bert"
 	kv["bert.attention.causal"] = false
 	kv["bert.pooling_type"] = p.PoolingType
-	kv["bert.normalize_embeddings"] = p.normalizeEmbeddings

 	kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)

@@ -136,8 +132,8 @@ func (p *bertModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *bertModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *bertModel) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
 		if slices.Contains([]string{
 			"embeddings.position_ids",
@@ -147,7 +143,7 @@ func (p *bertModel) Tensors(ts []Tensor) []*ggml.Tensor {
 			continue
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_commandr.go
+++ b/convert/convert_commandr.go
@@ -43,10 +43,10 @@ func (p *commandrModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *commandrModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *commandrModel) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_gemma.go
+++ b/convert/convert_gemma.go
@@ -42,14 +42,14 @@ func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *gemmaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *gemmaModel) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
 		if !strings.HasPrefix(t.Name(), "v.") && strings.HasSuffix(t.Name(), "_norm.weight") {
 			t.SetRepacker(p.addOne)
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_gemma2_adapter.go
+++ b/convert/convert_gemma2_adapter.go
@@ -21,8 +21,8 @@ func (p *gemma2Adapter) KV(baseKV ggml.KV) ggml.KV {
 	return kv
 }

-func (p *gemma2Adapter) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *gemma2Adapter) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
 		shape := t.Shape()
 		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@@ -31,7 +31,7 @@ func (p *gemma2Adapter) Tensors(ts []Tensor) []*ggml.Tensor {
 			t.SetRepacker(p.repack)
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_gemma3n.go
+++ b/convert/convert_gemma3n.go
@@ -1,165 +0,0 @@
-package convert
-
-import (
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-	"gonum.org/v1/gonum/stat/distuv"
-)
-
-type gemma3nModel struct {
-	ModelParameters
-
-	TextModel struct {
-		ActivationSparsityPattern []float32 `json:"activation_sparsity_pattern"`
-		AltupActiveIdx            uint32    `json:"altup_active_idx"`
-		AltupCoefClip             float32   `json:"altup_coef_clip"`
-		AltupCorrectScale         bool      `json:"altup_correct_scale"`
-		AltupLRMultiplier         float32   `json:"altup_lr_multiplier"`
-		AltupNumInputs            uint32    `json:"altup_num_inputs"`
-		HeadDim                   uint32    `json:"head_dim"`
-		HiddenSize                uint32    `json:"hidden_size"`
-		HiddenSizePerLayerInput   uint32    `json:"hidden_size_per_layer_input"`
-		IntermediateSize          uint32    `json:"intermediate_size"`
-		MaxPositionEmbeddings     uint32    `json:"max_position_embeddings"`
-		NumAttentionHeads         uint32    `json:"num_attention_heads"`
-		NumHiddenLayers           uint32    `json:"num_hidden_layers"`
-		NumKeyValueHeads          uint32    `json:"num_key_value_heads"`
-		NumKVSharedLayers         uint32    `json:"num_kv_shared_layers"`
-		RMSNormEPS                float32   `json:"rms_norm_eps"`
-		RopeLocalBaseFreq         float32   `json:"rope_local_base_freq"`
-		RopeTheta                 float32   `json:"rope_theta"`
-		SlidingWindow             uint32    `json:"sliding_window"`
-		LayerTypes                []string  `json:"layer_types"`
-	} `json:"text_config"`
-	VisionModel struct{} `json:"vision_config"`
-}
-
-func (m *gemma3nModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "gemma3n"
-	kv["gemma3n.activation_sparsity_scale"] = slices.Collect(func(yield func(float32) bool) {
-		norm := distuv.Normal{Mu: 0, Sigma: 1}
-		for _, v := range m.TextModel.ActivationSparsityPattern {
-			if !yield(float32(norm.Quantile(float64(v)))) {
-				break
-			}
-		}
-	})
-	kv["gemma3n.altup.active_idx"] = m.TextModel.AltupActiveIdx
-	kv["gemma3n.altup.correct_scale"] = m.TextModel.AltupCorrectScale
-	kv["gemma3n.altup.lr_multiplier"] = m.TextModel.AltupLRMultiplier
-	kv["gemma3n.altup.num_inputs"] = m.TextModel.AltupNumInputs
-	kv["gemma3n.attention.head_count_kv"] = m.TextModel.NumKeyValueHeads
-	kv["gemma3n.attention.head_count"] = m.TextModel.NumAttentionHeads
-	kv["gemma3n.attention.layer_norm_rms_epsilon"] = m.TextModel.RMSNormEPS
-	kv["gemma3n.attention.sliding_window"] = m.TextModel.SlidingWindow
-	kv["gemma3n.attention.sliding_window_pattern"] = slices.Collect(func(yield func(bool) bool) {
-		for _, t := range m.TextModel.LayerTypes {
-			if !yield(t == "sliding_attention") {
-				break
-			}
-		}
-	})
-	kv["gemma3n.attention.shared_kv_layers"] = m.TextModel.NumKVSharedLayers
-	kv["gemma3n.block_count"] = m.TextModel.NumHiddenLayers
-	kv["gemma3n.context_length"] = m.TextModel.MaxPositionEmbeddings
-	kv["gemma3n.embedding_length_per_layer_input"] = m.TextModel.HiddenSizePerLayerInput
-	kv["gemma3n.embedding_length"] = m.TextModel.HiddenSize
-	kv["gemma3n.feed_forward_length"] = m.TextModel.IntermediateSize
-	kv["gemma3n.head_dim"] = m.TextModel.HeadDim
-	kv["gemma3n.rope.freq_base_local"] = m.TextModel.RopeLocalBaseFreq
-	kv["gemma3n.rope.freq_base"] = m.TextModel.RopeTheta
-	return kv
-}
-
-func (m *gemma3nModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	out, ts := mergeTensors(ts,
-		merge{"altup_proj.*.weight", "altup_proj.weight"},
-		merge{"altup_unembd_proj.*.weight", "altup_unembd_proj.weight"},
-	)
-
-	for _, t := range ts {
-		switch {
-		case strings.Contains(t.Name(), "audio_tower"),
-			strings.Contains(t.Name(), "embed_audio"),
-			strings.Contains(t.Name(), "vision_tower"),
-			strings.Contains(t.Name(), "embed_vision"):
-			// TODO: handle audio and vision towers
-			continue
-		case strings.Contains(t.Name(), "altup_predict_coef"),
-			strings.Contains(t.Name(), "altup_correct_coef"):
-			if m.TextModel.AltupCoefClip > 0 {
-				t.SetRepacker(func(name string, data []float32, shape []uint64) (_ []float32, err error) {
-					dims := make([]int, len(shape))
-					for i := range shape {
-						dims[i] = int(shape[i])
-					}
-
-					var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-					t, err = tensor.Clamp(t, -m.TextModel.AltupCoefClip, m.TextModel.AltupCoefClip)
-					if err != nil {
-						return nil, err
-					}
-
-					if err := t.Reshape(t.Shape().TotalSize()); err != nil {
-						return nil, err
-					}
-
-					return native.VectorF32(t.(*tensor.Dense))
-				})
-			}
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (m *gemma3nModel) Replacements() []string {
-	return []string{
-		"model.language_model.embed_tokens_per_layer", "per_layer_token_embd",
-		"model.language_model.embed_tokens", "token_embd",
-		"model.language_model.per_layer_model_projection", "per_layer_model_proj",
-		"model.language_model.per_layer_projection_norm", "per_layer_proj_norm", "model.language_model.altup_projections", "altup_proj",
-		"model.language_model.altup_unembed_projections", "altup_unembd_proj",
-		"model.language_model.norm", "output_norm",
-		"model.language_model.layers", "blk",
-
-		"input_layernorm", "attn_norm",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.q_norm", "attn_q_norm",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.k_norm", "attn_k_norm",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"post_attention_layernorm", "post_attention_norm",
-		"pre_feedforward_layernorm", "ffn_norm",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"mlp.down_proj", "ffn_down",
-		"post_feedforward_layernorm", "post_ffw_norm",
-		"per_layer_input_gate", "inp_gate",
-		"per_layer_projection", "proj",
-		"post_per_layer_input_norm", "post_norm",
-		"altup.", "altup_",
-		"modality_router", "router",
-		"prediction_coefs", "predict_coef",
-		"correction_coefs", "correct_coef",
-		"correct_output_scale", "correct_scale.weight",
-		"laurel.", "laurel_",
-		"linear_left", "l",
-		"linear_right", "r",
-		"post_laurel_norm", "post_norm",
-	}
-}
--- a/convert/convert_gptoss.go
+++ b/convert/convert_gptoss.go
@@ -1,223 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"cmp"
-	"encoding/binary"
-	"io"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-)
-
-type gptossModel struct {
-	ModelParameters
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	AttentionHeads        uint32  `json:"num_attention_heads"`
-	KeyValueHeads         uint32  `json:"num_key_value_heads"`
-	HeadDim               uint32  `json:"head_dim"`
-	Experts               uint32  `json:"num_experts"`
-	LocalExperts          uint32  `json:"num_local_experts"`
-	ExpertsPerToken       uint32  `json:"experts_per_token"`
-	RMSNormEpsilon        float32 `json:"rms_norm_eps"`
-	InitialContextLength  uint32  `json:"initial_context_length"`
-	RopeTheta             float32 `json:"rope_theta"`
-	RopeScalingFactor     float32 `json:"rope_scaling_factor"`
-	RopeScaling           struct {
-		Factor float32 `json:"factor"`
-	} `json:"rope_scaling"`
-	SlidingWindow uint32 `json:"sliding_window"`
-}
-
-var _ ModelConverter = (*gptossModel)(nil)
-
-func (m *gptossModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "gptoss"
-	kv["general.file_type"] = uint32(4)
-	kv["gptoss.context_length"] = cmp.Or(m.MaxPositionEmbeddings, uint32(m.RopeScalingFactor*float32(m.InitialContextLength)))
-	kv["gptoss.block_count"] = m.HiddenLayers
-	kv["gptoss.embedding_length"] = m.HiddenSize
-	kv["gptoss.feed_forward_length"] = m.IntermediateSize
-	kv["gptoss.expert_count"] = cmp.Or(m.Experts, m.LocalExperts)
-	kv["gptoss.expert_used_count"] = m.ExpertsPerToken
-	kv["gptoss.attention.head_count"] = m.AttentionHeads
-	kv["gptoss.attention.head_count_kv"] = m.KeyValueHeads
-	kv["gptoss.attention.key_length"] = m.HeadDim
-	kv["gptoss.attention.value_length"] = m.HeadDim
-	kv["gptoss.attention.layer_norm_rms_epsilon"] = cmp.Or(m.RMSNormEpsilon, 1e-5)
-	kv["gptoss.attention.sliding_window"] = m.SlidingWindow
-	kv["gptoss.rope.freq_base"] = m.RopeTheta
-	kv["gptoss.rope.scaling.factor"] = cmp.Or(m.RopeScalingFactor, m.RopeScaling.Factor)
-	kv["gptoss.rope.scaling.original_context_length"] = m.InitialContextLength
-	kv["tokenizer.ggml.bos_token_id"] = uint32(199998) // <|startoftext|>
-	kv["tokenizer.ggml.add_bos_token"] = false
-	kv["tokenizer.ggml.eos_token_id"] = uint32(199999) // <|endoftext|>
-	kv["tokenizer.ggml.eos_token_ids"] = []int32{
-		199999, /* <|endoftext|> */
-		200002, /* <|return|> */
-		200012, /* <|call|> */
-	}
-	kv["tokenizer.ggml.add_eos_token"] = false
-	return kv
-}
-
-func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	mxfp4s := make(map[string]*mxfp4)
-	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), ".blocks") || strings.HasSuffix(t.Name(), ".scales") {
-			dot := strings.LastIndex(t.Name(), ".")
-			name, suffix := t.Name()[:dot], t.Name()[dot+1:]
-			if _, ok := mxfp4s[name]; !ok {
-				mxfp4s[name] = &mxfp4{}
-			}
-
-			switch suffix {
-			case "blocks":
-				mxfp4s[name].blocks = t
-			case "scales":
-				mxfp4s[name].scales = t
-			}
-		} else {
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	for name, mxfp4 := range mxfp4s {
-		dims := mxfp4.blocks.Shape()
-
-		if !strings.HasSuffix(name, ".weight") {
-			name += ".weight"
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     name,
-			Kind:     uint32(ggml.TensorTypeMXFP4),
-			Shape:    []uint64{dims[0], dims[1], dims[2] * dims[3] * 2},
-			WriterTo: mxfp4,
-		})
-	}
-
-	return out
-}
-
-func (m *gptossModel) Replacements() []string {
-	var replacements []string
-	if m.MaxPositionEmbeddings > 0 {
-		// hf flavored model
-		replacements = []string{
-			"lm_head", "output",
-			"model.embed_tokens", "token_embd",
-			"model.layers", "blk",
-			"input_layernorm", "attn_norm",
-			"self_attn.q_proj", "attn_q",
-			"self_attn.k_proj", "attn_k",
-			"self_attn.v_proj", "attn_v",
-			"self_attn.o_proj", "attn_out",
-			"self_attn.sinks", "attn_sinks",
-			"post_attention_layernorm", "ffn_norm",
-			"mlp.router", "ffn_gate_inp",
-			"mlp.experts.gate_up_proj_", "ffn_gate_up_exps.",
-			"mlp.experts.down_proj_", "ffn_down_exps.",
-			"model.norm", "output_norm",
-		}
-	} else {
-		replacements = []string{
-			// noop replacements so other replacements will not be applied
-			".blocks", ".blocks",
-			".scales", ".scales",
-			// real replacements
-			"block", "blk",
-			"attn.norm", "attn_norm",
-			"attn.qkv", "attn_qkv",
-			"attn.sinks", "attn_sinks",
-			"attn.out", "attn_out",
-			"mlp.norm", "ffn_norm",
-			"mlp.gate", "ffn_gate_inp",
-			"mlp.mlp1_", "ffn_gate_up_exps.",
-			"mlp.mlp2_", "ffn_down_exps.",
-			"embedding", "token_embd",
-			"norm", "output_norm",
-			"unembedding", "output",
-			"scale", "weight",
-		}
-	}
-	return replacements
-}
-
-type mxfp4 struct {
-	blocks, scales Tensor
-}
-
-func (m *mxfp4) WriteTo(w io.Writer) (int64, error) {
-	var b bytes.Buffer
-	if _, err := m.blocks.WriteTo(&b); err != nil {
-		return 0, err
-	}
-
-	blocksDims := make([]int, len(m.blocks.Shape()))
-	for i, d := range m.blocks.Shape() {
-		blocksDims[i] = int(d)
-	}
-
-	bts := b.Bytes()
-	var tmp [16]byte
-	for i := 0; i < b.Len(); i += 16 {
-		for j := range 8 {
-			// transform a1b2c3 ... x7y8z9 -> 71xa82yb93zc
-			a, b := bts[i+j], bts[i+j+8]
-			tmp[2*j+0] = (a & 0x0F) | (b << 4)
-			tmp[2*j+1] = (a >> 4) | (b & 0xF0)
-		}
-
-		copy(bts[i:i+16], tmp[:])
-	}
-
-	var blocks tensor.Tensor = tensor.New(tensor.WithShape(blocksDims...), tensor.WithBacking(bts))
-
-	var s bytes.Buffer
-	if _, err := m.scales.WriteTo(&s); err != nil {
-		return 0, err
-	}
-
-	scalesDims := slices.Repeat([]int{1}, len(m.blocks.Shape()))
-	for i, d := range m.scales.Shape() {
-		scalesDims[i] = int(d)
-	}
-
-	var scales tensor.Tensor = tensor.New(tensor.WithShape(scalesDims...), tensor.WithBacking(s.Bytes()))
-
-	out, err := tensor.Concat(3, scales, blocks)
-	if err != nil {
-		return 0, err
-	}
-
-	out = tensor.Materialize(out)
-
-	if err := out.Reshape(out.Shape().TotalSize()); err != nil {
-		return 0, err
-	}
-
-	u8s, err := native.VectorU8(out.(*tensor.Dense))
-	if err != nil {
-		return 0, err
-	}
-
-	if err := binary.Write(w, binary.LittleEndian, u8s); err != nil {
-		return 0, err
-	}
-
-	return int64(len(u8s)), nil
-}
--- a/convert/convert_llama.go
+++ b/convert/convert_llama.go
@@ -126,11 +126,11 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *llamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *llamaModel) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor

 	if p.RopeScaling.factors != nil {
-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     "rope_freqs.weight",
 			Kind:     0,
 			Shape:    []uint64{uint64(len(p.RopeScaling.factors))},
@@ -139,14 +139,13 @@ func (p *llamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
 	}

 	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), "attn_q.weight") || strings.HasSuffix(t.Name(), "attn_k.weight") ||
-			strings.HasSuffix(t.Name(), "attn_q_proj.weight") || strings.HasSuffix(t.Name(), "attn_k_proj.weight") {
+		if strings.HasSuffix(t.Name(), "attn_q.weight") || strings.HasSuffix(t.Name(), "attn_k.weight") {
 			if !p.skipRepack {
 				t.SetRepacker(p.repack)
 			}
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
@@ -182,9 +181,9 @@ func (p *llamaModel) repack(name string, data []float32, shape []uint64) ([]floa
 	}

 	var heads uint32
-	if strings.HasSuffix(name, "attn_q.weight") || strings.HasSuffix(name, "attn_q_proj.weight") {
+	if strings.HasSuffix(name, "attn_q.weight") {
 		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, "attn_k.weight") || strings.HasSuffix(name, "attn_k_proj.weight") {
+	} else if strings.HasSuffix(name, "attn_k.weight") {
 		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
 	} else {
 		return nil, fmt.Errorf("unknown tensor for repack: %s", name)
--- a/convert/convert_llama4.go
+++ b/convert/convert_llama4.go
@@ -88,13 +88,13 @@ func (p *llama4Model) Replacements() []string {
 }

 // Tensors implements ModelConverter.
-func (p *llama4Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *llama4Model) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor

 	var textTensors []Tensor
 	for _, t := range ts {
 		if strings.HasPrefix(t.Name(), "v.") || strings.HasPrefix(t.Name(), "mm.") {
-			out = append(out, &ggml.Tensor{
+			out = append(out, ggml.Tensor{
 				Name:     t.Name(),
 				Kind:     t.Kind(),
 				Shape:    t.Shape(),
@@ -112,7 +112,7 @@ func (p *llama4Model) Tensors(ts []Tensor) []*ggml.Tensor {
 				// clone tensor since we need separate repackers
 				tt := t.Clone()
 				tt.SetRepacker(p.repack(nil, nil, tensor.S(i*halfDim, (i+1)*halfDim)))
-				out = append(out, &ggml.Tensor{
+				out = append(out, ggml.Tensor{
 					Name:     strings.ReplaceAll(tt.Name(), "ffn_gate_up_exps", name),
 					Kind:     tt.Kind(),
 					Shape:    newShape,
@@ -125,7 +125,7 @@ func (p *llama4Model) Tensors(ts []Tensor) []*ggml.Tensor {
 			t.SetRepacker(p.repack())
 			newShape := slices.Clone(t.Shape())
 			newShape[1], newShape[2] = newShape[2], newShape[1]
-			out = append(out, &ggml.Tensor{
+			out = append(out, ggml.Tensor{
 				Name:     t.Name(),
 				Kind:     t.Kind(),
 				Shape:    newShape,
--- a/convert/convert_llama_adapter.go
+++ b/convert/convert_llama_adapter.go
@@ -29,8 +29,8 @@ func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
 	return kv
 }

-func (p *llamaAdapter) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *llamaAdapter) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
 		shape := t.Shape()
 		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@@ -41,7 +41,7 @@ func (p *llamaAdapter) Tensors(ts []Tensor) []*ggml.Tensor {
 			t.SetRepacker(p.repack)
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    shape,
--- a/convert/convert_mistral.go
+++ b/convert/convert_mistral.go
@@ -89,8 +89,8 @@ func (p *mistral3Model) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *mistral3Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *mistral3Model) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor

 	for _, t := range ts {
 		if !strings.HasPrefix(t.Name(), "v.") {
@@ -100,7 +100,7 @@ func (p *mistral3Model) Tensors(ts []Tensor) []*ggml.Tensor {
 			}
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_mixtral.go
+++ b/convert/convert_mixtral.go
@@ -2,6 +2,9 @@ package convert

 import (
 	"fmt"
+	"io"
+	"slices"
+	"strings"

 	"github.com/ollama/ollama/fs/ggml"
 )
@@ -26,39 +29,66 @@ func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *mixtralModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	merges := make([]merge, 0, p.NumHiddenLayers*6)
-	for i := range p.NumHiddenLayers {
-		merges = append(merges, merge{
-			fmt.Sprintf("blk.%d.*.w1.weight", i),
-			fmt.Sprintf("blk.%d.ffn_gate_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w1.bias", i),
-			fmt.Sprintf("blk.%d.ffn_gate_exps.bias", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w2.weight", i),
-			fmt.Sprintf("blk.%d.ffn_up_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w2.bias", i),
-			fmt.Sprintf("blk.%d.ffn_up_exps.bias", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w3.weight", i),
-			fmt.Sprintf("blk.%d.ffn_down_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w3.bias", i),
-			fmt.Sprintf("blk.%d.ffn_down_exps.bias", i),
+func (p *mixtralModel) Tensors(ts []Tensor) []ggml.Tensor {
+	oldnew := []string{
+		"model.layers", "blk",
+		"w1", "ffn_gate_exps",
+		"w2", "ffn_down_exps",
+		"w3", "ffn_up_exps",
+	}
+
+	for i := range p.NumLocalExperts {
+		oldnew = append(oldnew, fmt.Sprintf(".block_sparse_moe.experts.%d.", i), ".")
+	}
+
+	// group experts of the same layer (model.layers.%d) and type (w[123]) into a single tensor
+	namer := strings.NewReplacer(oldnew...)
+	experts := make(map[string]experts)
+
+	// merge experts into a single tensor while removing them from ts
+	ts = slices.DeleteFunc(ts, func(t Tensor) bool {
+		if !strings.Contains(t.Name(), ".block_sparse_moe.experts.") {
+			return false
+		}
+
+		name := namer.Replace(t.Name())
+		experts[name] = append(experts[name], t)
+		return true
+	})
+
+	var out []ggml.Tensor
+	for n, e := range experts {
+		// TODO(mxyng): sanity check experts
+		out = append(out, ggml.Tensor{
+			Name:     n,
+			Kind:     e[0].Kind(),
+			Shape:    append([]uint64{uint64(len(e))}, e[0].Shape()...),
+			WriterTo: e,
 		})
 	}

-	out, ts := mergeTensors(ts, merges...)
 	return append(out, p.llamaModel.Tensors(ts)...)
 }

 func (p *mixtralModel) Replacements() []string {
 	return append(
 		p.llamaModel.Replacements(),
-		"model.layers", "blk",
 		"block_sparse_moe.gate", "ffn_gate_inp",
-		"block_sparse_moe.experts.", ".",
 	)
 }
+
+type experts []Tensor
+
+func (e experts) WriteTo(w io.Writer) (int64, error) {
+	// TODO(mxyng): experts _should_ be numerically sorted by expert but this should check
+	for _, t := range e {
+		// the canonical merged experts tensor stacks all experts along a new, 0 axis,
+		// e.g. `tensor.Stack(0, e[0], e[1:]...)`, which requires allocating temporary buffers
+		// this accomplishes the same thing by writing each expert tensor in sequence
+		if _, err := t.WriteTo(w); err != nil {
+			return 0, err
+		}
+	}
+
+	return 0, nil
+}
--- a/convert/convert_mllama.go
+++ b/convert/convert_mllama.go
@@ -1,179 +0,0 @@
-package convert
-
-import (
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-)
-
-type mllamaModel struct {
-	ModelParameters
-	TextModel struct {
-		llamaModel
-
-		CrossAttentionLayers []int32 `json:"cross_attention_layers"`
-	} `json:"text_config"`
-	VisionModel struct {
-		NumHiddenLayers           uint32  `json:"num_hidden_layers"`
-		NumGlobalLayers           uint32  `json:"num_global_layers"`
-		IntermediateLayersIndices []int32 `json:"intermediate_layers_indices"`
-
-		HiddenSize       uint32 `json:"hidden_size"`
-		IntermediateSize uint32 `json:"intermediate_size"`
-
-		AttentionHeads uint32 `json:"attention_heads"`
-
-		ImageSize   uint32  `json:"image_size"`
-		PatchSize   uint32  `json:"patch_size"`
-		NumChannels uint32  `json:"num_channels"`
-		MaxNumTiles uint32  `json:"max_num_tiles"`
-		NormEpsilon float32 `json:"norm_eps"`
-		RopeTheta   float32 `json:"rope.freq_base"`
-	} `json:"vision_config"`
-}
-
-func (m *mllamaModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "mllama"
-
-	for k, v := range m.TextModel.KV(t) {
-		if strings.HasPrefix(k, "llama.") {
-			kv[strings.ReplaceAll(k, "llama.", "mllama.")] = v
-		}
-	}
-
-	kv["mllama.attention.cross_attention_layers"] = m.TextModel.CrossAttentionLayers
-
-	kv["mllama.vision.block_count"] = m.VisionModel.NumHiddenLayers
-	kv["mllama.vision.global.block_count"] = m.VisionModel.NumGlobalLayers
-	kv["mllama.vision.intermediate_layers_indices"] = m.VisionModel.IntermediateLayersIndices
-
-	kv["mllama.vision.embedding_length"] = m.VisionModel.HiddenSize
-	kv["mllama.vision.feed_forward_length"] = m.VisionModel.IntermediateSize
-
-	kv["mllama.vision.attention.head_count"] = m.VisionModel.AttentionHeads
-	kv["mllama.vision.attention.layer_norm_epsilon"] = m.VisionModel.NormEpsilon
-
-	kv["mllama.vision.image_size"] = m.VisionModel.ImageSize
-	kv["mllama.vision.patch_size"] = m.VisionModel.PatchSize
-	kv["mllama.vision.max_num_tiles"] = m.VisionModel.MaxNumTiles
-	kv["mllama.vision.num_channels"] = m.VisionModel.NumChannels
-
-	return kv
-}
-
-func (m *mllamaModel) Replacements() []string {
-	return append(
-		m.TextModel.Replacements(),
-		"language_model.", "",
-		"gate_attn", "attn_gate",
-		"gate_ffn", "ffn_gate",
-		"cross_attn.", "cross_attn_",
-		"vision_model", "v",
-		"class_embedding", "class_embd",
-		"patch_embedding", "patch_embd",
-		"gated_positional_embedding.tile_embedding", "tile_position_embd",
-		"gated_positional_embedding.embedding", "position_embd.weight",
-		"gated_positional_embedding", "position_embd",
-		"embedding.weight", "weight",
-		"pre_tile_positional_embedding", "pre_tile_position_embd",
-		"post_tile_positional_embedding", "post_tile_position_embd",
-		"layernorm_pre", "pre_ln",
-		"layernorm_post", "post_ln",
-		"global_transformer.layers", "global.blk",
-		"transformer.layers", "blk",
-		"mlp.fc1", "ffn_up",
-		"mlp.fc2", "ffn_down",
-		"multi_modal_projector", "mm.0",
-	)
-}
-
-func (m *mllamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	var text []Tensor
-	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") && !strings.HasPrefix(t.Name(), "mm.") {
-			text = append(text, t)
-		} else if t.Name() == "v.position_embd.gate" {
-			for _, name := range []string{"v.position_embd.gate", "v.tile_position_embd.gate"} {
-				tt := t.Clone()
-				tt.SetRepacker(m.repack(name))
-				out = append(out, &ggml.Tensor{
-					Name:     name,
-					Kind:     t.Kind(),
-					Shape:    t.Shape(),
-					WriterTo: tt,
-				})
-			}
-		} else {
-			if t.Name() == "v.pre_tile_position_embd.gate" || t.Name() == "v.post_tile_position_embd.gate" {
-				t.SetRepacker(m.repack(t.Name()))
-			} else if strings.HasSuffix(t.Name(), "attn_q.weight") || strings.HasSuffix(t.Name(), "attn_k.weight") {
-				t.SetRepacker(m.repack(t.Name()))
-			} else if strings.HasSuffix(t.Name(), "attn_gate") || strings.HasSuffix(t.Name(), "ffn_gate") {
-				t.SetRepacker(m.repack(t.Name()))
-			}
-
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	return append(out, m.TextModel.Tensors(text)...)
-}
-
-func (m *mllamaModel) repack(name string) Repacker {
-	return func(_ string, data []float32, shape []uint64) (_ []float32, err error) {
-		dims := make([]int, len(shape))
-		for i, dim := range shape {
-			dims[i] = int(dim)
-		}
-
-		var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-		if strings.HasSuffix(name, "attn_q.weight") || strings.HasSuffix(name, "attn_k.weight") {
-			heads := m.VisionModel.AttentionHeads
-			if err := t.Reshape(append([]int{int(heads), 2, dims[0] / int(heads) / 2}, dims[1:]...)...); err != nil {
-				return nil, err
-			}
-
-			if err := t.T(0, 2, 1, 3); err != nil {
-				return nil, err
-			}
-
-			if err := t.Reshape(dims...); err != nil {
-				return nil, err
-			}
-
-			if err := t.Transpose(); err != nil {
-				return nil, err
-			}
-		} else {
-			t, err = tensor.Tanh(t)
-			if err != nil {
-				return nil, err
-			}
-
-			if name == "v.position_embd.gate" {
-				t, err = tensor.Sub(float32(1), t)
-				if err != nil {
-					return nil, err
-				}
-			}
-		}
-
-		t = tensor.Materialize(t)
-		// flatten tensor so it can be return as a vector
-		if err := t.Reshape(t.Shape().TotalSize()); err != nil {
-			return nil, err
-		}
-
-		return native.VectorF32(t.(*tensor.Dense))
-	}
-}
--- a/convert/convert_phi3.go
+++ b/convert/convert_phi3.go
@@ -68,19 +68,19 @@ func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
 	return kv
 }

-func (p *phi3Model) Tensors(ts []Tensor) []*ggml.Tensor {
+func (p *phi3Model) Tensors(ts []Tensor) []ggml.Tensor {
 	var addRopeFactors sync.Once

-	out := make([]*ggml.Tensor, 0, len(ts)+2)
+	out := make([]ggml.Tensor, 0, len(ts)+2)
 	for _, t := range ts {
 		if strings.HasPrefix(t.Name(), "blk.0.") {
 			addRopeFactors.Do(func() {
-				out = append(out, &ggml.Tensor{
+				out = append(out, ggml.Tensor{
 					Name:     "rope_factors_long.weight",
 					Kind:     0,
 					Shape:    []uint64{uint64(len(p.RopeScaling.LongFactor))},
 					WriterTo: p.RopeScaling.LongFactor,
-				}, &ggml.Tensor{
+				}, ggml.Tensor{
 					Name:     "rope_factors_short.weight",
 					Kind:     0,
 					Shape:    []uint64{uint64(len(p.RopeScaling.ShortFactor))},
@@ -89,7 +89,7 @@ func (p *phi3Model) Tensors(ts []Tensor) []*ggml.Tensor {
 			})
 		}

-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_qwen2.go
+++ b/convert/convert_qwen2.go
@@ -15,7 +15,6 @@ type qwen2Model struct {
 		Type                          string     `json:"type"`
 		Factor                        ropeFactor `json:"factor"`
 		OriginalMaxPositionEmbeddings uint32     `json:"original_max_position_embeddings"`
-		MropeSection                  []int32    `json:"mrope_section"`
 	} `json:"rope_scaling"`
 	RMSNormEPS float32 `json:"rms_norm_eps"`
 }
@@ -40,18 +39,16 @@ func (q *qwen2Model) KV(t *Tokenizer) ggml.KV {
 	case "yarn":
 		kv["qwen2.rope.scaling.type"] = q.RopeScaling.Type
 		kv["qwen2.rope.scaling.factor"] = q.RopeScaling.Factor
-	case "mrope", "default":
-		kv["qwen2.rope.mrope_section"] = q.RopeScaling.MropeSection
 	default:
 		panic("unknown rope scaling type")
 	}
 	return kv
 }

-func (q *qwen2Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (q *qwen2Model) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
 	for _, t := range ts {
-		out = append(out, &ggml.Tensor{
+		out = append(out, ggml.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
--- a/convert/convert_qwen25vl.go
+++ b/convert/convert_qwen25vl.go
@@ -1,102 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type qwen25VLModel struct {
-	qwen2Model
-
-	VisionModel struct {
-		Depth               uint32  `json:"depth"`
-		HiddenSize          uint32  `json:"hidden_size"`
-		NumHeads            uint32  `json:"num_heads"`
-		InChannels          uint32  `json:"in_chans"`
-		PatchSize           uint32  `json:"patch_size"`
-		SpatialMergeSize    uint32  `json:"spatial_merge_size"`
-		SpatialPatchSize    uint32  `json:"spatial_patch_size"`
-		WindowSize          uint32  `json:"window_size"`
-		RMSNormEps          float32 `json:"layer_norm_epsilon"`
-		RopeTheta           float32 `json:"rope_theta"`
-		FullAttentionBlocks []int32 `json:"fullatt_block_indexes"`
-		TemporalPatchSize   uint32  `json:"temporal_patch_size"`
-	} `json:"vision_config"`
-}
-
-var _ ModelConverter = (*qwen25VLModel)(nil)
-
-func (q *qwen25VLModel) KV(t *Tokenizer) ggml.KV {
-	kv := q.ModelParameters.KV(t)
-	kv["general.architecture"] = "qwen25vl"
-
-	for k, v := range q.qwen2Model.KV(t) {
-		if strings.HasPrefix(k, "qwen2.") {
-			kv[strings.Replace(k, "qwen2.", "qwen25vl.", 1)] = v
-		}
-	}
-
-	if q.VisionModel.FullAttentionBlocks == nil {
-		kv["qwen25vl.vision.fullatt_block_indexes"] = []int32{7, 15, 23, 31}
-	}
-
-	kv["qwen25vl.vision.block_count"] = cmp.Or(q.VisionModel.Depth, 32)
-	kv["qwen25vl.vision.embedding_length"] = q.VisionModel.HiddenSize
-	kv["qwen25vl.vision.attention.head_count"] = cmp.Or(q.VisionModel.NumHeads, 16)
-	kv["qwen25vl.vision.num_channels"] = q.VisionModel.InChannels
-	kv["qwen25vl.vision.patch_size"] = cmp.Or(q.VisionModel.PatchSize, 14)
-	kv["qwen25vl.vision.spatial_merge_size"] = cmp.Or(q.VisionModel.SpatialMergeSize, 2)
-	kv["qwen25vl.vision.spatial_patch_size"] = q.VisionModel.SpatialPatchSize
-	kv["qwen25vl.vision.window_size"] = cmp.Or(q.VisionModel.WindowSize, 112)
-	kv["qwen25vl.vision.attention.layer_norm_epsilon"] = cmp.Or(q.VisionModel.RMSNormEps, 1e-6)
-	kv["qwen25vl.vision.rope.freq_base"] = cmp.Or(q.VisionModel.RopeTheta, 1e4)
-	kv["qwen25vl.vision.fullatt_block_indexes"] = q.VisionModel.FullAttentionBlocks
-	kv["qwen25vl.vision.temporal_patch_size"] = cmp.Or(q.VisionModel.TemporalPatchSize, 2)
-
-	return kv
-}
-
-func (q *qwen25VLModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-
-	for _, t := range ts {
-		if strings.Contains(t.Name(), "patch_embed.proj") {
-			for t := range splitDim(t, 2,
-				split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_0")},
-				split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_1")},
-			) {
-				t.Shape = slices.DeleteFunc(t.Shape, func(i uint64) bool { return i == 1 })
-				out = append(out, t)
-			}
-		} else if strings.Contains(t.Name(), "attn.qkv") {
-			out = append(out, slices.Collect(splitDim(t, 0,
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_q")},
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_k")},
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_v")},
-			))...)
-		} else {
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	return out
-}
-
-func (p *qwen25VLModel) Replacements() []string {
-	return append(
-		p.qwen2Model.Replacements(),
-		"visual", "v",
-		"blocks", "blk",
-		"attn.proj", "attn_out",
-		"norm1", "ln1",
-		"norm2", "ln2",
-	)
-}
--- a/convert/convert_test.go
+++ b/convert/convert_test.go
@@ -11,13 +11,14 @@ import (
 	"io"
 	"io/fs"
 	"log/slog"
-	"maps"
 	"os"
 	"path/filepath"
 	"slices"
 	"strings"
 	"testing"

+	"golang.org/x/exp/maps"
+
 	"github.com/ollama/ollama/fs/ggml"
 )

@@ -46,7 +47,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	}
 	t.Cleanup(func() { r.Close() })

-	m, err := ggml.Decode(r, -1)
+	m, _, err := ggml.Decode(r, -1)
 	if err != nil {
 		t.Fatal(err)
 	}
@@ -129,14 +130,15 @@ func TestConvertModel(t *testing.T) {
 			if err != nil {
 				t.Fatal(err)
 			}
-			defer expectFile.Close()

 			var expect map[string]string
 			if err := json.NewDecoder(expectFile).Decode(&expect); err != nil {
 				t.Fatal(err)
 			}

-			for _, k := range slices.Sorted(maps.Keys(expect)) {
+			keys := maps.Keys(expect)
+			slices.Sort(keys)
+			for _, k := range keys {
 				if v, ok := actual[k]; !ok {
 					t.Errorf("missing %s", k)
 				} else if v != expect[k] {
@@ -329,7 +331,7 @@ func TestConvertAdapter(t *testing.T) {
 			}
 			defer r.Close()

-			m, err := ggml.Decode(r, -1)
+			m, _, err := ggml.Decode(r, -1)
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -340,7 +342,9 @@ func TestConvertAdapter(t *testing.T) {

 			actual := generateResultsJSON(t, r, m.KV(), m.Tensors())

-			for _, k := range slices.Sorted(maps.Keys(c.Expected)) {
+			keys := maps.Keys(c.Expected)
+			slices.Sort(keys)
+			for _, k := range keys {
 				if v, ok := actual[k]; !ok {
 					t.Errorf("missing %s", k)
 				} else if v != c.Expected[k] {
--- a/convert/fs.go
+++ b/convert/fs.go
@@ -0,0 +1,58 @@
+package convert
+
+import (
+	"archive/zip"
+	"errors"
+	"io"
+	"io/fs"
+	"os"
+	"path/filepath"
+)
+
+type ZipReader struct {
+	r *zip.Reader
+	p string
+
+	// limit is the maximum size of a file that can be read directly
+	// from the zip archive. Files larger than this size will be extracted
+	limit int64
+}
+
+func NewZipReader(r *zip.Reader, p string, limit int64) fs.FS {
+	return &ZipReader{r, p, limit}
+}
+
+func (z *ZipReader) Open(name string) (fs.File, error) {
+	r, err := z.r.Open(name)
+	if err != nil {
+		return nil, err
+	}
+	defer r.Close()
+
+	if fi, err := r.Stat(); err != nil {
+		return nil, err
+	} else if fi.Size() < z.limit {
+		return r, nil
+	}
+
+	if !filepath.IsLocal(name) {
+		return nil, zip.ErrInsecurePath
+	}
+
+	n := filepath.Join(z.p, name)
+	if _, err := os.Stat(n); errors.Is(err, os.ErrNotExist) {
+		w, err := os.Create(n)
+		if err != nil {
+			return nil, err
+		}
+		defer w.Close()
+
+		if _, err := io.Copy(w, r); err != nil {
+			return nil, err
+		}
+	} else if err != nil {
+		return nil, err
+	}
+
+	return os.Open(n)
+}
--- a/convert/reader.go
+++ b/convert/reader.go
@@ -31,31 +31,25 @@ func (t tensorBase) Shape() []uint64 {
 }

 const (
-	tensorKindFP32 uint32 = iota
-	tensorKindFP16
-	tensorKindBF16  = 30
-	tensorKindMXFP4 = 39
+	tensorKindF32 uint32 = iota
+	tensorKindF16
 )

 func (t tensorBase) Kind() uint32 {
 	if strings.HasSuffix(t.name, ".ffn_gate_inp.weight") ||
-		strings.HasSuffix(t.name, ".bias") ||
 		t.name == "token_types.weight" ||
-		t.name == "v.positional_embedding_vlm" ||
-		t.name == "v.tile_position_embd.weight" ||
-		t.name == "v.pre_tile_position_embd.weight" ||
-		t.name == "v.post_tile_position_embd.weight" {
+		t.name == "v.positional_embedding_vlm" {
 		// these tensors are always F32
-		return tensorKindFP32
+		return 0
 	}

 	switch len(t.shape) {
 	case 0:
 		panic("invalid tensor shape")
 	case 1:
-		return tensorKindFP32
+		return tensorKindF32
 	default:
-		return tensorKindFP16
+		return tensorKindF16
 	}
 }

--- a/convert/reader_safetensors.go
+++ b/convert/reader_safetensors.go
@@ -1,7 +1,6 @@
 package convert

 import (
-	"bufio"
 	"bytes"
 	"encoding/binary"
 	"encoding/json"
@@ -9,12 +8,12 @@ import (
 	"fmt"
 	"io"
 	"io/fs"
-	"maps"
 	"slices"
 	"strings"

 	"github.com/d4l3k/go-bfloat16"
 	"github.com/x448/float16"
+	"golang.org/x/exp/maps"
 )

 type safetensorMetadata struct {
@@ -47,7 +46,8 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
 			return nil, err
 		}

-		keys := slices.Sorted(maps.Keys(headers))
+		keys := maps.Keys(headers)
+		slices.Sort(keys)

 		names := make(map[string]struct{}, len(keys))

@@ -94,15 +94,6 @@ type safetensor struct {
 	*tensorBase
 }

-func (st safetensor) Kind() uint32 {
-	kind := st.tensorBase.Kind()
-	if !strings.HasPrefix(st.name, "v.") && st.dtype == "BF16" && kind != tensorKindFP32 {
-		kind = tensorKindBF16
-	}
-
-	return kind
-}
-
 func (st safetensor) Clone() Tensor {
 	return &safetensor{
 		fs:     st.fs,
@@ -125,41 +116,26 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	}
 	defer f.Close()

-	r, err := func() (io.Reader, error) {
-		if readerAt, ok := f.(io.ReaderAt); ok {
-			return io.NewSectionReader(readerAt, st.offset, st.size), nil
-		} else if seeker, ok := f.(io.Seeker); ok {
-			_, err := seeker.Seek(st.offset, io.SeekStart)
-			return f, err
-		} else {
-			_, err := io.CopyN(io.Discard, f, st.offset)
-			return f, err
+	if seeker, ok := f.(io.Seeker); ok {
+		if _, err := seeker.Seek(st.offset, io.SeekStart); err != nil {
+			return 0, err
+		}
+	} else {
+		if _, err := io.CopyN(io.Discard, f, st.offset); err != nil {
+			return 0, err
 		}
-	}()
-	if err != nil {
-		return 0, err
-	}
-
-	br := bufio.NewReaderSize(r, min(32<<10, int(st.size)))
-	// special case when input and output are same type and the
-	// tensor doesn't need repacking
-	if (st.repacker == nil) &&
-		((st.dtype == "F32" && st.Kind() == tensorKindFP32) ||
-			(st.dtype == "F16" && st.Kind() == tensorKindFP16) ||
-			(st.dtype == "U8")) {
-		return io.CopyN(w, br, st.size)
 	}

 	var f32s []float32
 	switch st.dtype {
 	case "F32":
 		f32s = make([]float32, st.size/4)
-		if err = binary.Read(br, binary.LittleEndian, f32s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, f32s); err != nil {
 			return 0, err
 		}
 	case "F16":
 		u16s := make([]uint16, st.size/2)
-		if err = binary.Read(br, binary.LittleEndian, u16s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, u16s); err != nil {
 			return 0, err
 		}

@@ -170,7 +146,7 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {

 	case "BF16":
 		u8s := make([]uint8, st.size)
-		if err = binary.Read(br, binary.LittleEndian, u8s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, u8s); err != nil {
 			return 0, err
 		}

@@ -187,18 +163,15 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	}

 	switch st.Kind() {
-	case tensorKindFP32:
-		return int64(len(f32s) * 4), binary.Write(w, binary.LittleEndian, f32s)
-	case tensorKindFP16:
+	case tensorKindF32:
+		return 0, binary.Write(w, binary.LittleEndian, f32s)
+	case tensorKindF16:
 		f16s := make([]uint16, len(f32s))
 		for i := range f32s {
 			f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
 		}

-		return int64(len(f16s) * 2), binary.Write(w, binary.LittleEndian, f16s)
-	case tensorKindBF16:
-		u8s := bfloat16.EncodeFloat32(f32s)
-		return int64(len(u8s)), binary.Write(w, binary.LittleEndian, u8s)
+		return 0, binary.Write(w, binary.LittleEndian, f16s)
 	default:
 		return 0, fmt.Errorf("unknown storage type: %d", st.Kind())
 	}
--- a/convert/reader_test.go
+++ b/convert/reader_test.go
@@ -1,294 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"encoding/binary"
-	"os"
-	"path/filepath"
-	"testing"
-
-	"github.com/d4l3k/go-bfloat16"
-	"github.com/google/go-cmp/cmp"
-	"github.com/x448/float16"
-)
-
-func TestSafetensors(t *testing.T) {
-	t.Parallel()
-
-	root, err := os.OpenRoot(t.TempDir())
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer root.Close()
-
-	cases := []struct {
-		name,
-		dtype string
-		offset,
-		size int64
-		shape []uint64
-		setup func(*testing.T, *os.File)
-		want  []byte
-	}{
-		{
-			name:  "fp32-fp32",
-			dtype: "F32",
-			size:  32 * 4, // 32 floats, each 4 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, f32s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "fp32-fp16",
-			dtype: "F32",
-			size:  32 * 4, // 32 floats, each 4 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, f32s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x3c, 0x00, 0x40, 0x00, 0x42, 0x00, 0x44, 0x00, 0x45, 0x00, 0x46, 0x00, 0x47,
-				0x00, 0x48, 0x80, 0x48, 0x00, 0x49, 0x80, 0x49, 0x00, 0x4a, 0x80, 0x4a, 0x00, 0x4b, 0x80, 0x4b,
-				0x00, 0x4c, 0x40, 0x4c, 0x80, 0x4c, 0xc0, 0x4c, 0x00, 0x4d, 0x40, 0x4d, 0x80, 0x4d, 0xc0, 0x4d,
-				0x00, 0x4e, 0x40, 0x4e, 0x80, 0x4e, 0xc0, 0x4e, 0x00, 0x4f, 0x40, 0x4f, 0x80, 0x4f, 0xc0, 0x4f,
-			},
-		},
-		{
-			name:  "fp16-fp16",
-			dtype: "F16",
-			size:  32 * 2, // 32 floats, each 2 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				u16s := make([]uint16, 32)
-				for i := range u16s {
-					u16s[i] = float16.Fromfloat32(float32(i)).Bits()
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u16s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x3c, 0x00, 0x40, 0x00, 0x42, 0x00, 0x44, 0x00, 0x45, 0x00, 0x46, 0x00, 0x47,
-				0x00, 0x48, 0x80, 0x48, 0x00, 0x49, 0x80, 0x49, 0x00, 0x4a, 0x80, 0x4a, 0x00, 0x4b, 0x80, 0x4b,
-				0x00, 0x4c, 0x40, 0x4c, 0x80, 0x4c, 0xc0, 0x4c, 0x00, 0x4d, 0x40, 0x4d, 0x80, 0x4d, 0xc0, 0x4d,
-				0x00, 0x4e, 0x40, 0x4e, 0x80, 0x4e, 0xc0, 0x4e, 0x00, 0x4f, 0x40, 0x4f, 0x80, 0x4f, 0xc0, 0x4f,
-			},
-		},
-		{
-			name:  "fp16-fp32",
-			dtype: "F16",
-			size:  32 * 2, // 32 floats, each 2 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				u16s := make([]uint16, 32)
-				for i := range u16s {
-					u16s[i] = float16.Fromfloat32(float32(i)).Bits()
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u16s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "bf16-bf16",
-			dtype: "BF16",
-			size:  32 * 2, // 32 brain floats, each 2 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, bfloat16.EncodeFloat32(f32s)); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x80, 0x3f, 0x00, 0x40, 0x40, 0x40, 0x80, 0x40, 0xa0, 0x40, 0xc0, 0x40, 0xe0, 0x40,
-				0x00, 0x41, 0x10, 0x41, 0x20, 0x41, 0x30, 0x41, 0x40, 0x41, 0x50, 0x41, 0x60, 0x41, 0x70, 0x41,
-				0x80, 0x41, 0x88, 0x41, 0x90, 0x41, 0x98, 0x41, 0xa0, 0x41, 0xa8, 0x41, 0xb0, 0x41, 0xb8, 0x41,
-				0xc0, 0x41, 0xc8, 0x41, 0xd0, 0x41, 0xd8, 0x41, 0xe0, 0x41, 0xe8, 0x41, 0xf0, 0x41, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "bf16-fp32",
-			dtype: "BF16",
-			size:  32 * 2, // 32 brain floats, each 2 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, bfloat16.EncodeFloat32(f32s)); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "u8-u8",
-			dtype: "U8",
-			size:  32, // 32 brain floats, each 1 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				u8s := make([]uint8, 32)
-				for i := range u8s {
-					u8s[i] = uint8(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u8s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
-				0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
-			},
-		},
-	}
-
-	for _, tt := range cases {
-		t.Run(tt.name, func(t *testing.T) {
-			path := filepath.Base(t.Name())
-			st := safetensor{
-				fs:     root.FS(),
-				path:   path,
-				dtype:  tt.dtype,
-				offset: tt.offset,
-				size:   tt.size,
-				tensorBase: &tensorBase{
-					name:  tt.name,
-					shape: tt.shape,
-				},
-			}
-
-			f, err := root.Create(path)
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer f.Close()
-
-			tt.setup(t, f)
-
-			var b bytes.Buffer
-			if _, err := st.WriteTo(&b); err != nil {
-				t.Fatal(err)
-			}
-
-			if diff := cmp.Diff(tt.want, b.Bytes()); diff != "" {
-				t.Errorf("safetensor.WriteTo() mismatch (-want +got):\n%s", diff)
-			}
-		})
-	}
-}
-
-func TestSafetensorKind(t *testing.T) {
-	tests := []struct {
-		name     string
-		st       safetensor
-		expected uint32
-	}{
-		{
-			name: "BF16 dtype with non-v. prefix and non-FP32 base kind should return BF16",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindBF16,
-		},
-		{
-			name: "BF16 dtype with v. prefix should return base kind",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "v.weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindFP16,
-		},
-		{
-			name: "BF16 dtype with FP32 base kind should return FP32",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10}, // will default to FP32
-				},
-				dtype: "BF16",
-			},
-			expected: tensorKindFP32,
-		},
-		{
-			name: "Non-BF16 dtype should return base kind",
-			st: safetensor{
-				tensorBase: &tensorBase{
-					name:  "weight.matrix",
-					shape: []uint64{10, 10}, // will default to FP16
-				},
-				dtype: "FP16",
-			},
-			expected: tensorKindFP16,
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			result := tt.st.Kind()
-			if result != tt.expected {
-				t.Errorf("Kind() = %d, expected %d", result, tt.expected)
-			}
-		})
-	}
-}
--- a/convert/tensor.go
+++ b/convert/tensor.go
@@ -1,129 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"io"
-	"iter"
-	"path"
-	"slices"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type split struct {
-	*strings.Replacer
-	dim int
-
-	// fn is an optional function to apply to the tensor after slicing
-	fn func(tensor.Tensor) (tensor.Tensor, error)
-}
-
-// splitDim splits a tensor along a specified dimension into multiple tensors. The dimension
-// is split evenly based on the number of replacers provided unless a specific count is given.
-func splitDim(t Tensor, dim int, splits ...split) iter.Seq[*ggml.Tensor] {
-	return func(yield func(*ggml.Tensor) bool) {
-		var offset int
-		for _, split := range splits {
-			t := t.Clone()
-			shape := slices.Clone(t.Shape())
-			shape[dim] = cmp.Or(uint64(split.dim), shape[dim]/uint64(len(splits)))
-
-			slice := slices.Repeat([]tensor.Slice{nil}, len(shape))
-			slice[dim] = tensor.S(offset, offset+int(shape[dim]))
-			offset += int(shape[dim])
-
-			t.SetRepacker(func(_ string, data []float32, shape []uint64) ([]float32, error) {
-				dims := make([]int, len(shape))
-				for i := range shape {
-					dims[i] = int(shape[i])
-				}
-
-				var tt tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-				tt, err := tt.Slice(slice...)
-				if err != nil {
-					return nil, err
-				}
-
-				tt = tensor.Materialize(tt)
-
-				if split.fn != nil {
-					tt, err = split.fn(tt)
-					if err != nil {
-						return nil, err
-					}
-				}
-
-				// flatten tensor so it can be written as a vector
-				if err := tt.Reshape(tt.Shape().TotalSize()); err != nil {
-					return nil, err
-				}
-
-				return native.VectorF32(tt.(*tensor.Dense))
-			})
-
-			if !yield(&ggml.Tensor{
-				Name:     split.Replace(t.Name()),
-				Kind:     t.Kind(),
-				Shape:    shape,
-				WriterTo: t,
-			}) {
-				break
-			}
-		}
-	}
-}
-
-type merge struct {
-	pattern, name string
-}
-
-// mergeTensors merges tensors that match a given pattern into a single tensor.
-func mergeTensors(unmatched []Tensor, merges ...merge) (out []*ggml.Tensor, _ []Tensor) {
-	var matched []Tensor
-	for i := range merges {
-		matched, unmatched = slicesSplitFunc(unmatched, func(t Tensor) bool {
-			matched, _ := path.Match(merges[i].pattern, t.Name())
-			return matched
-		})
-
-		if len(matched) > 0 {
-			out = append(out, &ggml.Tensor{
-				Name:     merges[i].name,
-				Kind:     matched[0].Kind(),
-				Shape:    append([]uint64{uint64(len(matched))}, matched[0].Shape()...),
-				WriterTo: mergeGroup(matched),
-			})
-		}
-	}
-
-	return out, unmatched
-}
-
-// slicesSplitFunc splits a slice into two slices based on a predicate function.
-func slicesSplitFunc[S ~[]E, E comparable](s S, fn func(e E) bool) (matched, unmatched S) {
-	for _, e := range s {
-		if fn(e) {
-			matched = append(matched, e)
-		} else {
-			unmatched = append(unmatched, e)
-		}
-	}
-
-	return matched, unmatched
-}
-
-type mergeGroup []Tensor
-
-func (g mergeGroup) WriteTo(w io.Writer) (int64, error) {
-	for _, t := range g {
-		if _, err := t.WriteTo(w); err != nil {
-			return 0, err
-		}
-	}
-
-	return 0, nil
-}
--- a/convert/tensor_test.go
+++ b/convert/tensor_test.go
@@ -1,953 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"encoding/binary"
-	"io"
-	"iter"
-	"slices"
-	"strings"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-)
-
-type fakeTensor struct {
-	name  string
-	shape []uint64
-	data  []float32
-
-	repacker Repacker
-}
-
-func (f fakeTensor) Name() string {
-	return f.name
-}
-
-func (f fakeTensor) Shape() []uint64 {
-	return f.shape
-}
-
-func (f fakeTensor) Kind() uint32 {
-	return 0
-}
-
-func (f *fakeTensor) SetRepacker(fn Repacker) {
-	f.repacker = fn
-}
-
-func (f fakeTensor) Clone() Tensor {
-	return &fakeTensor{
-		name:     f.name,
-		shape:    slices.Clone(f.shape),
-		data:     slices.Clone(f.data),
-		repacker: f.repacker,
-	}
-}
-
-func (f fakeTensor) WriteTo(w io.Writer) (n int64, err error) {
-	data := f.data
-	if f.repacker != nil {
-		data, err = f.repacker(f.name, data, f.shape)
-		if err != nil {
-			return 0, err
-		}
-	}
-
-	if err := binary.Write(w, binary.LittleEndian, data); err != nil {
-		return 0, err
-	}
-
-	return int64(len(data) * 4), nil
-}
-
-func mul(shape []uint64) int {
-	n := 1
-	for _, dim := range shape {
-		n *= int(dim)
-	}
-	return n
-}
-
-func TestSplitDim(t *testing.T) {
-	t.Run("2d", func(t *testing.T) {
-		r := fakeTensor{
-			name:  "a.b",
-			shape: []uint64{3, 4},
-			data:  []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11},
-		}
-
-		t.Run("no split", func(t *testing.T) {
-			for tt := range splitDim(&r, 0, split{Replacer: strings.NewReplacer("a", "x")}) {
-				if tt.Name != "x.b" {
-					t.Fatalf("expected name 'x', got '%s'", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("even split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y")},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 3, 6, 7, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{2, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 6, 10}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{3, 7, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("split with transpose", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y"), fn: func(tt tensor.Tensor) (tensor.Tensor, error) {
-					return tensor.Transpose(tt, 1, 0)
-				}},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 6, 10, 3, 7, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-	})
-	t.Run("3d", func(t *testing.T) {
-		r := fakeTensor{
-			name:  "a.b",
-			shape: []uint64{3, 4, 2},
-			data:  []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
-		}
-
-		t.Run("no split", func(t *testing.T) {
-			for tt := range splitDim(&r, 0, split{Replacer: strings.NewReplacer("a", "x")}) {
-				if tt.Name != "x.b" {
-					t.Fatalf("expected name 'x', got '%s'", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("even split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y")},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{2, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11, 12, 13, 14, 15}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 12, 13, 20, 21}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{6, 7, 14, 15, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-	})
-}
-
-func TestMerge(t *testing.T) {
-	unmatched := []Tensor{
-		&fakeTensor{
-			name:  "a.0.b",
-			shape: []uint64{5, 2},
-			data:  []float32{10, 11, 12, 13, 14, 15, 16, 17, 18, 19},
-		},
-		&fakeTensor{
-			name:  "a.1.b",
-			shape: []uint64{5, 2},
-			data:  []float32{20, 21, 22, 23, 24, 25, 26, 27, 28, 29},
-		},
-		&fakeTensor{
-			name:  "c.0.d",
-			shape: []uint64{5, 2},
-			data:  []float32{30, 31, 32, 33, 34, 35, 36, 37, 38, 39},
-		},
-		&fakeTensor{
-			name:  "c.1.d",
-			shape: []uint64{5, 2},
-			data:  []float32{40, 41, 42, 43, 44, 45, 46, 47, 48, 49},
-		},
-		&fakeTensor{
-			name:  "e.0.f",
-			shape: []uint64{5, 2},
-			data:  []float32{50, 51, 52, 53, 54, 55, 56, 57, 58, 59},
-		},
-	}
-
-	checkMatched := func(t *testing.T, n int, matched []*ggml.Tensor) {
-		for i := range n {
-			got := matched[i]
-			if diff := cmp.Diff([]uint64{2, 5, 2}, got.Shape); diff != "" {
-				t.Errorf("unexpected (-want +got):\n%s", diff)
-			}
-
-			var b bytes.Buffer
-			if _, err := got.WriteTo(&b); err != nil {
-				t.Fatal(err)
-			}
-
-			f32s := make([]float32, 20)
-			if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-				t.Fatal(err)
-			}
-
-			offset := 10 + (i * 20)
-			want := make([]float32, 20)
-			for j := range 20 {
-				want[j] = float32(offset + j)
-			}
-
-			if diff := cmp.Diff(want, f32s); diff != "" {
-				t.Errorf("unexpected data (-want +got):\n%s", diff)
-			}
-		}
-	}
-
-	t.Run("single merge", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"a.*.b", "a.b"})
-		if len(unmatched) != 3 {
-			t.Error("expected 3 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 1 {
-			t.Error("expected 1 merged tensor, got", len(matched))
-		}
-
-		checkMatched(t, 1, matched)
-	})
-
-	t.Run("multiple merges", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"a.*.b", "a.b"}, merge{"c.*.d", "c.d"})
-		if len(unmatched) != 1 {
-			t.Error("expected 1 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 2 {
-			t.Error("expected 2 merged tensor, got", len(matched))
-		}
-
-		checkMatched(t, 2, matched)
-	})
-
-	t.Run("no match", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"x.*.y", "x.y"})
-		if len(unmatched) != 5 {
-			t.Error("expected 5 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 0 {
-			t.Error("expected no merged tensors, got", len(matched))
-		}
-	})
-}
--- a/convert/tokenizer.go
+++ b/convert/tokenizer.go
@@ -8,10 +8,11 @@ import (
 	"fmt"
 	"io/fs"
 	"log/slog"
-	"maps"
 	"os"
 	"slices"
 	"strings"
+
+	"golang.org/x/exp/maps"
 )

 const (
@@ -109,7 +110,6 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 	}

 	if f, err := fsys.Open("tokenizer_config.json"); errors.Is(err, os.ErrNotExist) {
-		// noop
 	} else if err != nil {
 		return nil, err
 	} else {
@@ -171,34 +171,6 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 		}
 	}

-	if f, err := fsys.Open("generation_config.json"); errors.Is(err, os.ErrNotExist) {
-	} else if err != nil {
-		return nil, err
-	} else {
-		defer f.Close()
-
-		var p map[string]json.RawMessage
-		if err := json.NewDecoder(f).Decode(&p); err != nil {
-			return nil, err
-		}
-
-		for _, st := range specialTokenTypes {
-			if bts, ok := p[fmt.Sprintf("%s_token_id", st)]; ok {
-				var ids []int32
-				if err := json.Unmarshal(bts, &ids); err != nil {
-					// value is not a list so the existing ID is used
-					continue
-				}
-
-				if i := slices.IndexFunc(t.SpecialVocabulary, func(sv *SpecialVocabulary) bool {
-					return sv.Type == st
-				}); i >= 0 {
-					t.SpecialVocabulary[i].IDs = ids
-				}
-			}
-		}
-	}
-
 	return t, nil
 }

@@ -259,8 +231,11 @@ func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
 		tokens[token.ID] = token
 	}

+	keys := maps.Keys(tokens)
+	slices.Sort(keys)
+
 	v := Vocabulary{Model: "gpt2"}
-	for _, k := range slices.Sorted(maps.Keys(tokens)) {
+	for _, k := range keys {
 		token := tokens[k]
 		v.Tokens = append(v.Tokens, token.Content)
 		v.Scores = append(v.Scores, float32(token.ID))
@@ -305,9 +280,6 @@ type SpecialVocabulary struct {
 	ID       int
 	Content  string
 	AddToken bool
-
-	// IDs is populated by generation_config.json
-	IDs []int32
 }

 func (sv SpecialVocabulary) Key() string {
--- a/convert/tokenizer_test.go
+++ b/convert/tokenizer_test.go
@@ -247,67 +247,6 @@ func TestParseTokenizer(t *testing.T) {
 				Pre: "default",
 			},
 		},
-		{
-			name: "generation config eos token ids",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"added_tokens": [
-						{
-							"id": 0,
-							"content": "<bos>",
-							"special": true
-						},
-						{
-							"id": 1,
-							"content": "<eos>",
-							"special": true
-						},
-						{
-							"id": 2,
-							"content": "<eot>",
-							"special": true
-						},
-						{
-							"id": 3,
-							"content": "<eom>",
-							"special": true
-						}
-					],
-					"model": {
-						"vocab": {
-							"<bos>": 0,
-							"<eos>": 1,
-							"<eot>": 2,
-							"<eom>": 3
-						}
-					}
-				}`),
-				"tokenizer_config.json": strings.NewReader(`{
-					"add_bos_token": true,
-					"add_eos_token": false,
-					"bos_token": "<bos>",
-					"eos_token": "<eos>"
-				}`),
-				"generation_config.json": strings.NewReader(`{
-					"bos_token_id": 0,
-					"eos_token_id": [1, 2, 3]
-				}`),
-			}),
-			specialTokenTypes: []string{"pad", "eos", "bos", "unk"},
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model:  "gpt2",
-					Tokens: []string{"<bos>", "<eos>", "<eot>", "<eom>"},
-					Scores: []float32{0, 1, 2, 3},
-					Types:  []int32{3, 3, 3, 3},
-				},
-				SpecialVocabulary: []*SpecialVocabulary{
-					{Type: "eos", Content: "<eos>", ID: 1, IDs: []int32{1, 2, 3}, AddToken: false},
-					{Type: "bos", Content: "<bos>", ID: 0, AddToken: true},
-				},
-				Pre: "default",
-			},
-		},
 	}

 	for _, tt := range cases {
--- a/discover/amd_linux.go
+++ b/discover/amd_linux.go
@@ -58,7 +58,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 	driverMajor, driverMinor, err := AMDDriverVersion()
 	if err != nil {
 		// TODO - if we see users crash and burn with the upstreamed kernel this can be adjusted to hard-fail rocm support and fallback to CPU
-		slog.Warn("ollama recommends running the https://www.amd.com/en/support/download/linux-drivers.html", "error", err)
+		slog.Warn("ollama recommends running the https://www.amd.com/en/support/linux-drivers", "error", err)
 	}

 	// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
@@ -97,7 +97,6 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		return a < b
 	})
 	gpuCount := 0
-	gpuOrdinalID := 0
 	for _, match := range matches {
 		slog.Debug("evaluating amdgpu node " + match)
 		fp, err := os.Open(match)
@@ -188,6 +187,10 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 			continue
 		}

+		// Keep track of numeric IDs based on valid GPUs
+		gpuID := gpuCount
+		gpuCount += 1
+
 		// Look up the memory for the current node
 		totalMemory := uint64(0)
 		usedMemory := uint64(0)
@@ -266,7 +269,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		if uniqueID != 0 {
 			ID = fmt.Sprintf("GPU-%016x", uniqueID)
 		} else {
-			ID = strconv.Itoa(gpuOrdinalID)
+			ID = strconv.Itoa(gpuID)
 		}

 		gpuInfo := RocmGPUInfo{
@@ -277,7 +280,6 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 					FreeMemory:  (totalMemory - usedMemory),
 				},
 				ID:            ID,
-				filterID:      gpuOrdinalID,
 				Name:          name,
 				Compute:       fmt.Sprintf("gfx%d%x%x", major, minor, patch),
 				MinimumMemory: rocmMinimumMemory,
@@ -285,40 +287,13 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 				DriverMinor:   driverMinor,
 			},
 			usedFilepath: usedFile,
-			index:        gpuCount,
+			index:        gpuID,
 		}

-		// Keep track of numeric IDs based on valid GPUs
-		gpuCount += 1
-
-		// If the user wants to filter to a subset of devices, filter out if we aren't a match
-		if len(visibleDevices) > 0 {
-			include := false
-			for _, visible := range visibleDevices {
-				if (uniqueID != 0 && visible == gpuInfo.ID) || visible == strconv.Itoa(gpuInfo.index) {
-					include = true
-					break
-				}
-			}
-			if !include {
-				reason := "filtering out device per user request"
-				slog.Info(reason, "id", gpuInfo.ID, "index", gpuInfo.index, "visible_devices", visibleDevices)
-				unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
-					GpuInfo: gpuInfo.GpuInfo,
-					Reason:  reason,
-				})
-
-				continue
-			}
-		}
-
-		// Ordinal IDs are based on the visible GPUs
-		gpuOrdinalID += 1
-
 		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
 		if totalMemory < IGPUMemLimit {
 			reason := "unsupported Radeon iGPU detected skipping"
-			slog.Info(reason, "id", gpuInfo.ID, "total", format.HumanBytes2(totalMemory))
+			slog.Info(reason, "id", gpuID, "total", format.HumanBytes2(totalMemory))
 			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
 				GpuInfo: gpuInfo.GpuInfo,
 				Reason:  reason,
@@ -331,7 +306,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		}
 		if int(major) < minVer {
 			reason := fmt.Sprintf("amdgpu too old gfx%d%x%x", major, minor, patch)
-			slog.Warn(reason, "gpu", gpuInfo.ID)
+			slog.Warn(reason, "gpu", gpuID)
 			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
 				GpuInfo: gpuInfo.GpuInfo,
 				Reason:  reason,
@@ -340,8 +315,29 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 			continue
 		}

-		slog.Debug("amdgpu memory", "gpu", gpuInfo.ID, "total", format.HumanBytes2(totalMemory))
-		slog.Debug("amdgpu memory", "gpu", gpuInfo.ID, "available", format.HumanBytes2(totalMemory-usedMemory))
+		slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
+		slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
+
+		// If the user wants to filter to a subset of devices, filter out if we aren't a match
+		if len(visibleDevices) > 0 {
+			include := false
+			for _, visible := range visibleDevices {
+				if visible == gpuInfo.ID || visible == strconv.Itoa(gpuInfo.index) {
+					include = true
+					break
+				}
+			}
+			if !include {
+				reason := "filtering out device per user request"
+				slog.Info(reason, "id", gpuInfo.ID, "visible_devices", visibleDevices)
+				unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
+					GpuInfo: gpuInfo.GpuInfo,
+					Reason:  reason,
+				})
+
+				continue
+			}
+		}

 		// Final validation is gfx compatibility - load the library if we haven't already loaded it
 		// even if the user overrides, we still need to validate the library
@@ -395,7 +391,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {

 		// Check for env var workarounds
 		if name == "1002:687f" { // Vega RX 56
-			gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, "HSA_ENABLE_SDMA=0")
+			gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
 		}

 		// The GPU has passed all the verification steps and is supported
@@ -524,26 +520,19 @@ func verifyKFDDriverAccess() error {
 	return nil
 }

-func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) string {
+func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
 	ids := []string{}
 	for _, info := range gpuInfo {
 		if info.Library != "rocm" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
 			continue
 		}
-		// If the devices requires a numeric ID, for filtering purposes, we use the unfiltered ID number
-		if _, err := strconv.Atoi(info.ID); err == nil {
-			ids = append(ids, fmt.Sprintf("%d", info.filterID))
-		} else {
-			ids = append(ids, info.ID)
-		}
+		ids = append(ids, info.ID)
 	}
-	if len(ids) == 0 {
-		return ""
-	}
-
 	// There are 3 potential env vars to use to select GPUs.
 	// ROCR_VISIBLE_DEVICES supports UUID or numeric so is our preferred on linux
 	// GPU_DEVICE_ORDINAL supports numeric IDs only
 	// HIP_VISIBLE_DEVICES supports numeric IDs only
-	return "ROCR_VISIBLE_DEVICES=" + strings.Join(ids, ",")
+	return "ROCR_VISIBLE_DEVICES", strings.Join(ids, ",")
 }
--- a/discover/amd_windows.go
+++ b/discover/amd_windows.go
@@ -111,7 +111,6 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 				UnreliableFreeMemory: true,

 				ID:             strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
-				filterID:       i,
 				DependencyPath: []string{libDir},
 				MinimumMemory:  rocmMinimumMemory,
 				Name:           name,
@@ -201,26 +200,19 @@ func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
 	return nil
 }

-func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) string {
+func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
 	ids := []string{}
 	for _, info := range gpuInfo {
 		if info.Library != "rocm" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
 			continue
 		}
-		// If the devices requires a numeric ID, for filtering purposes, we use the unfiltered ID number
-		if _, err := strconv.Atoi(info.ID); err == nil {
-			ids = append(ids, fmt.Sprintf("%d", info.filterID))
-		} else {
-			ids = append(ids, info.ID)
-		}
+		ids = append(ids, info.ID)
 	}
-	if len(ids) == 0 {
-		return ""
-	}
-
 	// There are 3 potential env vars to use to select GPUs.
 	// ROCR_VISIBLE_DEVICES supports UUID or numeric but does not work on Windows
 	// HIP_VISIBLE_DEVICES supports numeric IDs only
 	// GPU_DEVICE_ORDINAL supports numeric IDs only
-	return "HIP_VISIBLE_DEVICES=" + strings.Join(ids, ",")
+	return "HIP_VISIBLE_DEVICES", strings.Join(ids, ",")
 }
--- a/discover/cuda_common.go
+++ b/discover/cuda_common.go
@@ -3,7 +3,6 @@
 package discover

 import (
-	"fmt"
 	"log/slog"
 	"os"
 	"regexp"
@@ -16,7 +15,20 @@ import (
 // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
 var CudaTegra string = os.Getenv("JETSON_JETPACK")

-func cudaVariant(gpuInfos []CudaGPUInfo) string {
+func cudaGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "cuda" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("cudaGetVisibleDevicesEnv skipping over non-cuda device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "CUDA_VISIBLE_DEVICES", strings.Join(ids, ",")
+}
+
+func cudaVariant(gpuInfo CudaGPUInfo) string {
 	if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" {
 		if CudaTegra != "" {
 			ver := strings.Split(CudaTegra, ".")
@@ -45,20 +57,9 @@ func cudaVariant(gpuInfos []CudaGPUInfo) string {
 		}
 	}

-	// Check GPU compute capability FIRST, lowest common denominator if multi-gpu
-	for _, gpuInfo := range gpuInfos {
-		if gpuInfo.computeMajor < 7 || (gpuInfo.computeMajor == 7 && gpuInfo.computeMinor < 5) {
-			// GPU is Pascal or older (CC <= 7.4) - use CUDA v12 (supports CC 6.1)
-			return "v12"
-		}
+	// driver 12.0 has problems with the cuda v12 library, so run v11 on those older drivers
+	if gpuInfo.DriverMajor < 12 || (gpuInfo.DriverMajor == 12 && gpuInfo.DriverMinor == 0) {
+		return "v11"
 	}
-
-	// GPU is Turing or newer (CC >= 7.5) - can use newer CUDA
-	if len(gpuInfos) > 0 && gpuInfos[0].DriverMajor < 13 {
-		// The detected driver is older than 580 (Aug 2025)
-		// Warn if their CC is compatible with v13 and they should upgrade their driver to get better performance
-		slog.Warn("old CUDA driver detected - please upgrade to a newer driver for best performance", "version", fmt.Sprintf("%d.%d", gpuInfos[0].DriverMajor, gpuInfos[0].DriverMinor))
-		return "v12"
-	}
-	return "v13"
+	return "v12"
 }
--- a/discover/gpu.go
+++ b/discover/gpu.go
@@ -263,8 +263,6 @@ func GetGPUInfo() GpuInfoList {
 				var driverMinor int
 				if cHandles.cudart != nil {
 					C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
-					driverMajor = int(cHandles.cudart.driver_major)
-					driverMinor = int(cHandles.cudart.driver_minor)
 				} else {
 					C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
 					driverMajor = int(cHandles.nvcuda.driver_major)
@@ -284,8 +282,18 @@ func GetGPUInfo() GpuInfoList {
 				gpuInfo.MinimumMemory = cudaMinimumMemory
 				gpuInfo.DriverMajor = driverMajor
 				gpuInfo.DriverMinor = driverMinor
+				variant := cudaVariant(gpuInfo)

+				// Start with our bundled libraries
+				if variant != "" {
+					variantPath := filepath.Join(LibOllamaPath, "cuda_"+variant)
+					if _, err := os.Stat(variantPath); err == nil {
+						// Put the variant directory first in the search path to avoid runtime linking to the wrong library
+						gpuInfo.DependencyPath = append([]string{variantPath}, gpuInfo.DependencyPath...)
+					}
+				}
 				gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
+				gpuInfo.Variant = variant

 				if int(memInfo.major) < cudaComputeMajorMin || (int(memInfo.major) == cudaComputeMajorMin && int(memInfo.minor) < cudaComputeMinorMin) {
 					unsupportedGPUs = append(unsupportedGPUs,
@@ -323,24 +331,6 @@ func GetGPUInfo() GpuInfoList {
 				// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
 				cudaGPUs = append(cudaGPUs, gpuInfo)
 			}
-			// Second pass on NVIDIA GPUs to set lowest common denominator variant and DependencyPaths
-			variant := cudaVariant(cudaGPUs)
-			var variantPath string
-			// Start with our bundled libraries
-			if variant != "" {
-				variantPath = filepath.Join(LibOllamaPath, "cuda_"+variant)
-				if _, err := os.Stat(variantPath); err != nil {
-					variantPath = ""
-				}
-			}
-
-			for i := range cudaGPUs {
-				cudaGPUs[i].Variant = variant
-				if variantPath != "" {
-					// Put the variant directory first in the search path to avoid runtime linking to the wrong library
-					cudaGPUs[i].DependencyPath = append([]string{variantPath}, cudaGPUs[i].DependencyPath...)
-				}
-			}
 		}

 		// Intel
@@ -379,15 +369,6 @@ func GetGPUInfo() GpuInfoList {
 		}

 		rocmGPUs, err = AMDGetGPUInfo()
-
-		// The ID field is used in context of the filtered set of GPUS
-		// so we have to replace any of these numeric IDs with their
-		// placement in this set of GPUs
-		for i := range rocmGPUs {
-			if _, err := strconv.Atoi(rocmGPUs[i].ID); err == nil {
-				rocmGPUs[i].ID = strconv.Itoa(i)
-			}
-		}
 		if err != nil {
 			bootstrapErrors = append(bootstrapErrors, err)
 		}
@@ -689,7 +670,7 @@ func loadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string, e
 }

 func getVerboseState() C.uint16_t {
-	if envconfig.LogLevel() < slog.LevelInfo {
+	if envconfig.Debug() {
 		return C.uint16_t(1)
 	}
 	return C.uint16_t(0)
@@ -697,16 +678,23 @@ func getVerboseState() C.uint16_t {

 // Given the list of GPUs this instantiation is targeted for,
 // figure out the visible devices environment variable
-func (l GpuInfoList) GetVisibleDevicesEnv() []string {
+//
+// If different libraries are detected, the first one is what we use
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
 	if len(l) == 0 {
-		return nil
+		return "", ""
 	}
-	vd := []string{}
-	// Only filter the AMD GPUs at this level, let all NVIDIA devices through
-	if tmp := rocmGetVisibleDevicesEnv(l); tmp != "" {
-		vd = append(vd, tmp)
+	switch l[0].Library {
+	case "cuda":
+		return cudaGetVisibleDevicesEnv(l)
+	case "rocm":
+		return rocmGetVisibleDevicesEnv(l)
+	case "oneapi":
+		return oneapiGetVisibleDevicesEnv(l)
+	default:
+		slog.Debug("no filter required for library " + l[0].Library)
+		return "", ""
 	}
-	return vd
 }

 func GetSystemInfo() SystemInfo {
--- a/discover/gpu_darwin.go
+++ b/discover/gpu_darwin.go
@@ -62,9 +62,9 @@ func GetCPUMem() (memInfo, error) {
 	}, nil
 }

-func (l GpuInfoList) GetVisibleDevicesEnv() []string {
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
 	// No-op on darwin
-	return nil
+	return "", ""
 }

 func GetSystemInfo() SystemInfo {
--- a/discover/gpu_info.h
+++ b/discover/gpu_info.h
@@ -27,14 +27,12 @@

 #endif

-#ifndef LOG
 #define LOG(verbose, ...) \
  do { \
    if (verbose) { \
      fprintf(stderr, __VA_ARGS__); \
    } \
  } while (0)
-#endif

 #ifdef __cplusplus
 extern "C" {
--- a/discover/gpu_info_cudart.c
+++ b/discover/gpu_info_cudart.c
@@ -1,7 +1,6 @@
 #ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?

 #include <string.h>
-#include <inttypes.h>
 #include "gpu_info_cudart.h"

 void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
@@ -59,7 +58,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
    LOG(resp->ch.verbose, "cudaSetDevice err: %d\n", ret);
    UNLOAD_LIBRARY(resp->ch.handle);
    resp->ch.handle = NULL;
-    if (ret == CUDART_ERROR_INSUFFICIENT_DRIVER) {
+    if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
      resp->err = strdup("your nvidia driver is too old or missing.  If you have a CUDA GPU please upgrade to run ollama");
      return;
    }
@@ -69,15 +68,18 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
  }

  int version = 0;
+  cudartDriverVersion_t driverVersion;
+  driverVersion.major = 0;
+  driverVersion.minor = 0;

  // Report driver version if we're in verbose mode, ignore errors
  ret = (*resp->ch.cudaDriverGetVersion)(&version);
  if (ret != CUDART_SUCCESS) {
    LOG(resp->ch.verbose, "cudaDriverGetVersion failed: %d\n", ret);
  } else {
-    resp->ch.driver_major = version / 1000;
-    resp->ch.driver_minor = (version - (resp->ch.driver_major * 1000)) / 10;
-    LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", resp->ch.driver_major, resp->ch.driver_minor);
+    driverVersion.major = version / 1000;
+    driverVersion.minor = (version - (driverVersion.major * 1000)) / 10;
+    LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", driverVersion.major, driverVersion.minor);
  }

  ret = (*resp->ch.cudaGetDeviceCount)(&resp->num_devices);
@@ -166,9 +168,9 @@ void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
  resp->free = memInfo.free;
  resp->used = memInfo.used;

-  LOG(h.verbose, "[%s] CUDA totalMem %" PRId64 "\n", resp->gpu_id, resp->total);
-  LOG(h.verbose, "[%s] CUDA freeMem %" PRId64 "\n", resp->gpu_id, resp->free);
-  LOG(h.verbose, "[%s] CUDA usedMem %" PRId64 "\n", resp->gpu_id, resp->used);
+  LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
+  LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
+  LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
  LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
 }

@@ -178,4 +180,4 @@ void cudart_release(cudart_handle_t h) {
  h.handle = NULL;
 }

-#endif  // __APPLE__
+#endif  // __APPLE__
--- a/discover/gpu_info_cudart.h
+++ b/discover/gpu_info_cudart.h
@@ -29,6 +29,11 @@ typedef struct cudartMemory_st {
  size_t used;
 } cudartMemory_t;

+typedef struct cudartDriverVersion {
+  int major;
+  int minor;
+} cudartDriverVersion_t;
+
 typedef struct cudaUUID {
    unsigned char bytes[16];
 } cudaUUID_t;
@@ -118,8 +123,6 @@ typedef struct cudaDeviceProp {
 typedef struct cudart_handle {
  void *handle;
  uint16_t verbose;
-  int driver_major;
-  int driver_minor;
  cudartReturn_t (*cudaSetDevice)(int device);
  cudartReturn_t (*cudaDeviceSynchronize)(void);
  cudartReturn_t (*cudaDeviceReset)(void);
--- a/discover/gpu_info_nvcuda.c
+++ b/discover/gpu_info_nvcuda.c
@@ -1,7 +1,6 @@
 #ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?

 #include <string.h>
-#include <inttypes.h>
 #include "gpu_info_nvcuda.h"

 void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
@@ -194,8 +193,8 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
  resp->total = memInfo.total;
  resp->free = memInfo.free;

-  LOG(h.verbose, "[%s] CUDA totalMem %" PRId64 "mb\n", resp->gpu_id, resp->total / 1024 / 1024);
-  LOG(h.verbose, "[%s] CUDA freeMem %" PRId64 "mb\n", resp->gpu_id, resp->free / 1024 / 1024);
+  LOG(h.verbose, "[%s] CUDA totalMem %lu mb\n", resp->gpu_id, resp->total / 1024 / 1024);
+  LOG(h.verbose, "[%s] CUDA freeMem %lu mb\n", resp->gpu_id, resp->free / 1024 / 1024);
  LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);

  
@@ -248,4 +247,4 @@ void nvcuda_release(nvcuda_handle_t h) {
  h.handle = NULL;
 }

-#endif  // __APPLE__
+#endif  // __APPLE__
--- a/discover/gpu_oneapi.go
+++ b/discover/gpu_oneapi.go
@@ -0,0 +1,21 @@
+//go:build linux || windows
+
+package discover
+
+import (
+	"log/slog"
+	"strings"
+)
+
+func oneapiGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "oneapi" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("oneapiGetVisibleDevicesEnv skipping over non-sycl device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "ONEAPI_DEVICE_SELECTOR", "level_zero:" + strings.Join(ids, ",")
+}
--- a/discover/path.go
+++ b/discover/path.go
@@ -12,7 +12,7 @@ import (
 // '../lib/ollama' on Linux and the executable's directory on macOS
 // note: distribution builds, additional GPU-specific libraries are
 // found in subdirectories of the returned path, such as
-// 'cuda_v12', 'rocm', etc.
+// 'cuda_v11', 'cuda_v12', 'rocm', etc.
 var LibOllamaPath string = func() string {
 	exe, err := os.Executable()
 	if err != nil {
--- a/discover/types.go
+++ b/discover/types.go
@@ -27,8 +27,8 @@ type GpuInfo struct { // TODO better name maybe "InferenceProcessor"?
 	// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
 	DependencyPath []string `json:"lib_path,omitempty"`

-	// Extra environment variables specific to the GPU as list of [key=value]
-	EnvWorkarounds []string `json:"envs,omitempty"`
+	// Extra environment variables specific to the GPU as list of [key,value]
+	EnvWorkarounds [][2]string `json:"envs,omitempty"`

 	// Set to true if we can NOT reliably discover FreeMemory.  A value of true indicates
 	// the FreeMemory is best effort, and may over or under report actual memory usage
@@ -36,10 +36,9 @@ type GpuInfo struct { // TODO better name maybe "InferenceProcessor"?
 	UnreliableFreeMemory bool

 	// GPU information
-	ID       string `json:"gpu_id"` // string to use for selection of this specific GPU
-	filterID int    //nolint:unused,nolintlint // AMD Workaround: The numeric ID of the device used to filter out other devices
-	Name     string `json:"name"`    // user friendly name if available
-	Compute  string `json:"compute"` // Compute Capability or gfx
+	ID      string `json:"gpu_id"`  // string to use for selection of this specific GPU
+	Name    string `json:"name"`    // user friendly name if available
+	Compute string `json:"compute"` // Compute Capability or gfx

 	// Driver Information - TODO no need to put this on each GPU
 	DriverMajor int `json:"driver_major,omitempty"`
@@ -172,8 +171,7 @@ func (si SystemInfo) GetOptimalThreadCount() int {
 // For each GPU, check if it does NOT support flash attention
 func (l GpuInfoList) FlashAttentionSupported() bool {
 	for _, gpu := range l {
-		supportsFA := gpu.Library == "cpu" ||
-			gpu.Library == "metal" ||
+		supportsFA := gpu.Library == "metal" ||
 			(gpu.Library == "cuda" && gpu.DriverMajor >= 7) ||
 			gpu.Library == "rocm"

--- a/docs/README.md
+++ b/docs/README.md
@@ -4,7 +4,6 @@
 * [Quickstart](../README.md#quickstart)
 * [Examples](./examples.md)
 * [Importing models](./import.md)
-* [MacOS Documentation](./macos.md)
 * [Linux Documentation](./linux.md)
 * [Windows Documentation](./windows.md)
 * [Docker Documentation](./docker.md)
--- a/docs/api.md
+++ b/docs/api.md
@@ -19,7 +19,7 @@

 ### Model names

-Model names follow a `model:tag` format, where `model` can have an optional namespace such as `example/model`. Some examples are `orca-mini:3b-q8_0` and `llama3:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version.
+Model names follow a `model:tag` format, where `model` can have an optional namespace such as `example/model`. Some examples are `orca-mini:3b-q4_1` and `llama3:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version.

 ### Durations

@@ -43,7 +43,6 @@ Generate a response for a given prompt with a provided model. This is a streamin
 - `prompt`: the prompt to generate a response for
 - `suffix`: the text after the model response
 - `images`: (optional) a list of base64-encoded images (for multimodal models such as `llava`)
- `think`: (for thinking models) should the model think before responding?

 Advanced parameters (optional):

@@ -395,6 +394,9 @@ curl http://localhost:11434/api/generate -d '{
    "repeat_penalty": 1.2,
    "presence_penalty": 1.5,
    "frequency_penalty": 1.0,
+    "mirostat": 1,
+    "mirostat_tau": 0.8,
+    "mirostat_eta": 0.6,
    "penalize_newline": true,
    "stop": ["\n", "user:"],
    "numa": false,
@@ -402,7 +404,10 @@ curl http://localhost:11434/api/generate -d '{
    "num_batch": 2,
    "num_gpu": 1,
    "main_gpu": 0,
+    "low_vram": false,
+    "vocab_only": false,
    "use_mmap": true,
+    "use_mlock": false,
    "num_thread": 8
  }
 }'
@@ -491,39 +496,28 @@ Generate the next message in a chat with a provided model. This is a streaming e
 - `model`: (required) the [model name](#model-names)
 - `messages`: the messages of the chat, this can be used to keep a chat memory
 - `tools`: list of tools in JSON for the model to use if supported
- `think`: (for thinking models) should the model think before responding?

 The `message` object has the following fields:

 - `role`: the role of the message, either `system`, `user`, `assistant`, or `tool`
 - `content`: the content of the message
- `thinking`: (for thinking models) the model's thinking process
 - `images` (optional): a list of images to include in the message (for multimodal models such as `llava`)
 - `tool_calls` (optional): a list of tools in JSON that the model wants to use
- `tool_name` (optional): add the name of the tool that was executed to inform the model of the result

 Advanced parameters (optional):

- `format`: the format to return a response in. Format can be `json` or a JSON schema.
+- `format`: the format to return a response in. Format can be `json` or a JSON schema. 
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)

-### Tool calling
-
-Tool calling is supported by providing a list of tools in the `tools` parameter. The model will generate a response that includes a list of tool calls. See the [Chat request (Streaming with tools)](#chat-request-streaming-with-tools) example below.
-
-Models can also explain the result of the tool call in the response. See the [Chat request (With history, with tools)](#chat-request-with-history-with-tools) example below.
-
-[See models with tool calling capabilities](https://ollama.com/search?c=tool).
-
 ### Structured outputs

 Structured outputs are supported by providing a JSON schema in the `format` parameter. The model will generate a response that matches the schema. See the [Chat request (Structured outputs)](#chat-request-structured-outputs) example below.

 ### Examples

-#### Chat request (Streaming)
+#### Chat Request (Streaming)

 ##### Request

@@ -578,88 +572,6 @@ Final response:
 }
 ```

-#### Chat request (Streaming with tools)
-
-##### Request
-
-```shell
-curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.2",
-  "messages": [
-    {
-      "role": "user",
-      "content": "what is the weather in tokyo?"
-    }
-  ],
-  "tools": [
-    {
-      "type": "function",
-      "function": {
-        "name": "get_weather",
-        "description": "Get the weather in a given city",
-        "parameters": {
-          "type": "object",
-          "properties": {
-            "city": {
-              "type": "string",
-              "description": "The city to get the weather for"
-            }
-          },
-          "required": ["city"]
-        }
-      }
-    }
-  ],
-  "stream": true
-}'
-```
-
-##### Response
-
-A stream of JSON objects is returned:
-```json
-{
-    "model": "llama3.2",
-    "created_at": "2025-07-07T20:22:19.184789Z",
-    "message": {
-        "role": "assistant",
-        "content": "",
-        "tool_calls": [
-            {
-                "function": {
-                    "name": "get_weather",
-                    "arguments": {
-                        "city": "Tokyo"
-                    }
-                },
-            }
-        ]
-    },
-    "done": false
-}
-```
-
-Final response:
-
-```json
-{
-  "model":"llama3.2",
-  "created_at":"2025-07-07T20:22:19.19314Z",
-  "message": {
-    "role": "assistant",
-    "content": ""
-  },
-  "done_reason": "stop",
-  "done": true,
-  "total_duration": 182242375,
-  "load_duration": 41295167,
-  "prompt_eval_count": 169,
-  "prompt_eval_duration": 24573166,
-  "eval_count": 15,
-  "eval_duration": 115959084
-}
-```
-
 #### Chat request (No streaming)

 ##### Request
@@ -697,74 +609,6 @@ curl http://localhost:11434/api/chat -d '{
 }
 ```

-#### Chat request (No streaming, with tools)
-
-##### Request
-
-
-```shell
-curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.2",
-  "messages": [
-    {
-      "role": "user",
-      "content": "what is the weather in tokyo?"
-    }
-  ],
-  "tools": [
-    {
-      "type": "function",
-      "function": {
-        "name": "get_weather",
-        "description": "Get the weather in a given city",
-        "parameters": {
-          "type": "object",
-          "properties": {
-            "city": {
-              "type": "string",
-              "description": "The city to get the weather for"
-            }
-          },
-          "required": ["city"]
-        }
-      }
-    }
-  ],
-  "stream": false 
-}'
-```
-
-##### Response
-
-```json
-{
-  "model": "llama3.2",
-  "created_at": "2025-07-07T20:32:53.844124Z",
-  "message": {
-    "role": "assistant",
-    "content": "",
-    "tool_calls": [
-      {
-        "function": {
-          "name": "get_weather",
-          "arguments": {
-            "city": "Tokyo"
-          }
-        },
-      }
-    ]
-  },
-  "done_reason": "stop",
-  "done": true,
-  "total_duration": 3244883583,
-  "load_duration": 2969184542,
-  "prompt_eval_count": 169,
-  "prompt_eval_duration": 141656333,
-  "eval_count": 18,
-  "eval_duration": 133293625
-}
-```
-
 #### Chat request (Structured outputs)

 ##### Request
@@ -871,87 +715,6 @@ Final response:
 }
 ```

-
-#### Chat request (With history, with tools)
-
-##### Request
-
-```shell
-curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.2",
-  "messages": [
-    {
-      "role": "user",
-      "content": "what is the weather in Toronto?"
-    },
-    // the message from the model appended to history
-    {
-      "role": "assistant",
-      "content": "",
-      "tool_calls": [
-        {
-          "function": {
-            "name": "get_temperature",
-            "arguments": {
-              "city": "Toronto"
-            }
-          },
-        }
-      ]
-    },
-    // the tool call result appended to history
-    {
-      "role": "tool",
-      "content": "11 degrees celsius",
-      "tool_name": "get_temperature",
-    }
-  ],
-  "stream": false,
-  "tools": [
-    {
-      "type": "function",
-      "function": {
-        "name": "get_weather",
-        "description": "Get the weather in a given city",
-        "parameters": {
-          "type": "object",
-          "properties": {
-            "city": {
-              "type": "string",
-              "description": "The city to get the weather for"
-            }
-          },
-          "required": ["city"]
-        }
-      }
-    }
-  ]
-}'
-```
-
-##### Response
-
-```json
-{
-  "model": "llama3.2",
-  "created_at": "2025-07-07T20:43:37.688511Z",
-  "message": {
-    "role": "assistant",
-    "content": "The current temperature in Toronto is 11°C."
-  },
-  "done_reason": "stop",
-  "done": true,
-  "total_duration": 890771750,
-  "load_duration": 707634750,
-  "prompt_eval_count": 94,
-  "prompt_eval_duration": 91703208,
-  "eval_count": 11,
-  "eval_duration": 90282125
-}
-
-```
-
-
 #### Chat request (with images)

 ##### Request
@@ -1195,8 +958,19 @@ If you are creating a model from a safetensors directory or from a GGUF file, yo

 | Type | Recommended |
 | --- | :-: |
+| q2_K | |
+| q3_K_L | |
+| q3_K_M | |
+| q3_K_S | |
+| q4_0 | |
+| q4_1 | |
 | q4_K_M | * |
 | q4_K_S | |
+| q5_0 | |
+| q5_1 | |
+| q5_K_M | |
+| q5_K_S | |
+| q6_K | |
 | q8_0 | * |

 ### Examples
@@ -1241,8 +1015,8 @@ Quantize a non-quantized model.

 ```shell
 curl http://localhost:11434/api/create -d '{
-  "model": "llama3.2:quantized",
-  "from": "llama3.2:3b-instruct-fp16",
+  "model": "llama3.1:quantized",
+  "from": "llama3.1:8b-instruct-fp16",
  "quantize": "q4_K_M"
 }'
 ```
@@ -1252,14 +1026,12 @@ curl http://localhost:11434/api/create -d '{
 A stream of JSON objects is returned:

 ```json
-{"status":"quantizing F16 model to Q4_K_M","digest":"0","total":6433687776,"completed":12302}
-{"status":"quantizing F16 model to Q4_K_M","digest":"0","total":6433687776,"completed":6433687552}
-{"status":"verifying conversion"}
-{"status":"creating new layer sha256:fb7f4f211b89c6c4928ff4ddb73db9f9c0cfca3e000c3e40d6cf27ddc6ca72eb"}
-{"status":"using existing layer sha256:966de95ca8a62200913e3f8bfbf84c8494536f1b94b49166851e76644e966396"}
-{"status":"using existing layer sha256:fcc5a6bec9daf9b561a68827b67ab6088e1dba9d1fa2a50d7bbcc8384e0a265d"}
-{"status":"using existing layer sha256:a70ff7e570d97baaf4e62ac6e6ad9975e04caa6d900d3742d37698494479e0cd"}
+{"status":"quantizing F16 model to Q4_K_M"}
+{"status":"creating new layer sha256:667b0c1932bc6ffc593ed1d03f895bf2dc8dc6df21db3042284a6f4416b06a29"}
+{"status":"using existing layer sha256:11ce4ee3e170f6adebac9a991c22e22ab3f8530e154ee669954c4bc73061c258"}
+{"status":"using existing layer sha256:0ba8f0e314b4264dfd19df045cde9d4c394a52474bf92ed6a3de22a4ca31a177"}
 {"status":"using existing layer sha256:56bb8bd477a519ffa694fc449c2413c6f0e1d3b1c88fa7e3c9d88d3ae49d4dcb"}
+{"status":"creating new layer sha256:455f34728c9b5dd3376378bfb809ee166c145b0b4c1f1a6feca069055066ef9a"}
 {"status":"writing manifest"}
 {"status":"success"}
 ```
@@ -1397,37 +1169,29 @@ A single JSON object will be returned.
 {
  "models": [
    {
-      "name": "deepseek-r1:latest",
-      "model": "deepseek-r1:latest",
-      "modified_at": "2025-05-10T08:06:48.639712648-07:00",
-      "size": 4683075271,
-      "digest": "0a8c266910232fd3291e71e5ba1e058cc5af9d411192cf88b6d30e92b6e73163",
+      "name": "codellama:13b",
+      "modified_at": "2023-11-04T14:56:49.277302595-07:00",
+      "size": 7365960935,
+      "digest": "9f438cb9cd581fc025612d27f7c1a6669ff83a8bb0ed86c94fcf4c5440555697",
      "details": {
-        "parent_model": "",
        "format": "gguf",
-        "family": "qwen2",
-        "families": [
-          "qwen2"
-        ],
-        "parameter_size": "7.6B",
-        "quantization_level": "Q4_K_M"
+        "family": "llama",
+        "families": null,
+        "parameter_size": "13B",
+        "quantization_level": "Q4_0"
      }
    },
    {
-      "name": "llama3.2:latest",
-      "model": "llama3.2:latest",
-      "modified_at": "2025-05-04T17:37:44.706015396-07:00",
-      "size": 2019393189,
-      "digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72",
+      "name": "llama3:latest",
+      "modified_at": "2023-12-07T09:32:18.757212583-08:00",
+      "size": 3825819519,
+      "digest": "fe938a131f40e6f6d40083c9f0f430a515233eb2edaa6d72eb85c50d64f2300e",
      "details": {
-        "parent_model": "",
        "format": "gguf",
        "family": "llama",
-        "families": [
-          "llama"
-        ],
-        "parameter_size": "3.2B",
-        "quantization_level": "Q4_K_M"
+        "families": null,
+        "parameter_size": "7B",
+        "quantization_level": "Q4_0"
      }
    }
  ]
@@ -1593,7 +1357,7 @@ Then there is a series of downloading responses. Until any of the download is co

 ```json
 {
-  "status": "pulling digestname",
+  "status": "downloading digestname",
  "digest": "digestname",
  "total": 2142590208,
  "completed": 241970
@@ -1708,7 +1472,6 @@ Advanced parameters:
 - `truncate`: truncates the end of each input to fit within context length. Returns error if `false` and context length is exceeded. Defaults to `true`
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
- `dimensions`: number of dimensions for the embedding

 ### Examples

--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -0,0 +1,59 @@
+# Benchmark
+
+Go benchmark tests that measure end-to-end performance of a running Ollama server. Run these tests to evaluate model inference performance on your hardware and measure the impact of code changes.
+
+## When to use
+
+Run these benchmarks when:
+- Making changes to the model inference engine
+- Modifying model loading/unloading logic
+- Changing prompt processing or token generation code
+- Implementing a new model architecture
+- Testing performance across different hardware setups
+
+## Prerequisites
+- Ollama server running locally with `ollama serve` on `127.0.0.1:11434`
+## Usage and Examples
+
+>[!NOTE]
+>All commands must be run from the root directory of the Ollama project.
+
+Basic syntax:
+```bash
+go test -bench=. ./benchmark/... -m $MODEL_NAME
+```
+
+Required flags:
+- `-bench=.`: Run all benchmarks
+- `-m`: Model name to benchmark
+
+Optional flags:
+- `-count N`: Number of times to run the benchmark (useful for statistical analysis)
+- `-timeout T`: Maximum time for the benchmark to run (e.g. "10m" for 10 minutes)
+
+Common usage patterns:
+
+Single benchmark run with a model specified:
+```bash
+go test -bench=. ./benchmark/... -m llama3.3
+```
+
+## Output metrics
+
+The benchmark reports several key metrics:
+
+- `gen_tok/s`: Generated tokens per second
+- `prompt_tok/s`: Prompt processing tokens per second
+- `ttft_ms`: Time to first token in milliseconds
+- `load_ms`: Model load time in milliseconds
+- `gen_tokens`: Total tokens generated
+- `prompt_tokens`: Total prompt tokens processed
+
+Each benchmark runs two scenarios:
+- Cold start: Model is loaded from disk for each test
+- Warm start: Model is pre-loaded in memory
+
+Three prompt lengths are tested for each scenario:
+- Short prompt (100 tokens)
+- Medium prompt (500 tokens)
+- Long prompt (1000 tokens)
--- a/docs/cloud.md
+++ b/docs/cloud.md
@@ -1,40 +0,0 @@
-# Cloud
-
-| Ollama's cloud is currently in preview. For full documentation, see [Ollama's documentation](https://docs.ollama.com/cloud).
-
-## Cloud Models
-
-[Cloud models](https://ollama.com/cloud) are a new kind of model in Ollama that can run without a powerful GPU. Instead, cloud models are automatically offloaded to Ollama's cloud while offering the same capabilities as local models, making it possible to keep using your local tools while running larger models that wouldn’t fit on a personal computer.
-
-Ollama currently supports the following cloud models, with more coming soon:
-
- `gpt-oss:20b-cloud`
- `gpt-oss:120b-cloud`
- `deepseek-v3.1:671b-cloud`
- `qwen3-coder:480b-cloud`
-
-### Get started
-
-To run a cloud model, open the terminal and run:
-
-```
-ollama run gpt-oss:120b-cloud
-```
-
-To run cloud models with integrations that work with Ollama, first download the cloud model:
-
-```
-ollama pull qwen3-coder:480b-cloud
-```
-
-Then sign in to Ollama:
-
-```
-ollama signin
-```
-
-Finally, access the model using the model name `qwen3-coder:480b-cloud` via Ollama's local API or tooling.
-
-## Cloud API access
-
-Cloud models can also be accessed directly on ollama.com's API. For more information, see the [docs](https://docs.ollama.com/cloud).
--- a/docs/development.md
+++ b/docs/development.md
@@ -11,10 +11,6 @@ Then build and run Ollama from the root directory of the repository:
 go run . serve
 ```

-> [!NOTE]
-> Ollama includes native code compiled with CGO.  From time to time these data structures can change and CGO can get out of sync resulting in unexpected crashes.  You can force a full build of the native code by running `go clean -cache` first. 
-
-
 ## macOS (Apple Silicon)

 macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required.
@@ -122,7 +118,7 @@ To run tests, use `go test`:
 go test ./...
 ```

-> NOTE: In rare circumstances, you may need to change a package using the new
+> NOTE: In rare cirumstances, you may nedd to change a package using the new
 > "synctest" package in go1.24.
 >
 > If you do not have the "synctest" package enabled, you will not see build or
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -20,9 +20,9 @@ Please refer to the [GPU docs](./gpu.md).

 ## How can I specify the context window size?

-By default, Ollama uses a context window size of 4096 tokens for most models. The `gpt-oss` model has a default context window size of 8192 tokens.
+By default, Ollama uses a context window size of 4096 tokens, unless you have a single GPU with <= 4 GB of VRAM, in which case it will default to 2048 tokens. 

-This can be overridden in Settings in the Windows and macOS App, or with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use:
+This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use: 

 ```shell
 OLLAMA_CONTEXT_LENGTH=8192 ollama serve
@@ -31,7 +31,7 @@ OLLAMA_CONTEXT_LENGTH=8192 ollama serve
 To change this when using `ollama run`, use `/set parameter`:

 ```shell
-/set parameter num_ctx 4096
+/set parameter num_ctx 8192
 ```

 When using the API, specify the `num_ctx` parameter:
@@ -41,13 +41,11 @@ curl http://localhost:11434/api/generate -d '{
  "model": "llama3.2",
  "prompt": "Why is the sky blue?",
  "options": {
-    "num_ctx": 4096
+    "num_ctx": 8192
  }
 }'
 ```

-Setting the context length higher may cause the model to not be able to fit onto the GPU which make the model run more slowly.
-
 ## How can I tell if my model was loaded onto the GPU?

 Use the `ollama ps` command to see what models are currently loaded into memory.
@@ -59,8 +57,8 @@ ollama ps
 > **Output**:
 >
 > ```
-> NAME           ID              SIZE     PROCESSOR    CONTEXT    UNTIL
-> gpt-oss:20b    05afbac4bad6    16 GB    100% GPU     8192       4 minutes from now
+> NAME      	ID          	SIZE 	PROCESSOR	UNTIL
+> llama3:70b	bcfb190ca3a7	42 GB	100% GPU 	4 minutes from now
 > ```

 The `Processor` column will show which memory the model was loaded in to:
@@ -150,11 +148,9 @@ docker build -t ollama-with-ca .
 docker run -d -e HTTPS_PROXY=https://my.proxy.example.com -p 11434:11434 ollama-with-ca
 ```

-## Does Ollama send my prompts and responses back to ollama.com?
+## Does Ollama send my prompts and answers back to ollama.com?

-If you're running a model locally, your prompts and responses will always stay on your machine. Ollama Turbo in the App allows you to run your queries on Ollama's servers if you don't have a powerful enough GPU. Web search lets a model query the web, giving you more accurate and up-to-date information. Both Turbo and web search require sending your prompts and responses to Ollama.com. This data is neither logged nor stored.
-
-If you don't want to see the Turbo and web search options in the app, you can disable them in Settings by turning on Airplane mode. In Airplane mode, all models will run locally, and your prompts and responses will stay on your machine.
+No. Ollama runs locally, and conversation data does not leave your machine.

 ## How can I expose Ollama on my network?

@@ -296,7 +292,7 @@ If too many requests are sent to the server, it will respond with a 503 error in

 ## How does Ollama handle concurrent requests?

-Ollama supports two levels of concurrent processing.  If your system has sufficient available memory (system memory when using CPU inference, or VRAM for GPU inference) then multiple models can be loaded at the same time.  For a given model, if there is sufficient available memory when the model is loaded, it can be configured to allow parallel request processing.
+Ollama supports two levels of concurrent processing.  If your system has sufficient available memory (system memory when using CPU inference, or VRAM for GPU inference) then multiple models can be loaded at the same time.  For a given model, if there is sufficient available memory when the model is loaded, it is configured to allow parallel request processing.

 If there is insufficient available memory to load a new model request while one or more models are already loaded, all new requests will be queued until the new model can be loaded.  As prior models become idle, one or more will be unloaded to make room for the new model.  Queued requests will be processed in order.  When using GPU inference new models must be able to completely fit in VRAM to allow concurrent model loads.

@@ -305,7 +301,7 @@ Parallel request processing for a given model results in increasing the context
 The following server settings may be used to adjust how Ollama handles concurrent requests on most platforms:

 - `OLLAMA_MAX_LOADED_MODELS` - The maximum number of models that can be loaded concurrently provided they fit in available memory.  The default is 3 * the number of GPUs or 3 for CPU inference.
- `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time.  The default is 1, and will handle 1 request per model at a time.
+- `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time.  The default will auto-select either 4 or 1 based on available memory.
 - `OLLAMA_MAX_QUEUE` - The maximum number of requests Ollama will queue when busy before rejecting additional requests. The default is 512

 Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting.  Once ROCm v6.2 is available, Windows Radeon will follow the defaults above.  You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.
@@ -337,16 +333,3 @@ The currently available K/V cache quantization types are:
 How much the cache quantization impacts the model's response quality will depend on the model and the task.  Models that have a high GQA count (e.g. Qwen2) may see a larger impact on precision from quantization than models with a low GQA count.

 You may need to experiment with different quantization types to find the best balance between memory usage and quality.
-
-## How can I stop Ollama from starting when I login to my computer
-
-Ollama for Windows and macOS register as a login item during installation.  You can disable this if you prefer not to have Ollama automatically start.  Ollama will respect this setting across upgrades, unless you uninstall the application.
-
-**Windows**
- Remove `%APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\Ollama.lnk`
-
-**MacOS Monterey (v12)**
- Open `Settings` -> `Users & Groups` -> `Login Items` and find the `Ollama` entry, then click the `-` (minus) to remove
-
-**MacOS Ventura (v13) and later**
- Open `Settings` and search for "Login Items", find the `Ollama` entry under "Allow in the Background`, then click the slider to disable.
--- a/docs/gpu.md
+++ b/docs/gpu.md
@@ -1,14 +1,12 @@
 # GPU
 ## Nvidia
-Ollama supports Nvidia GPUs with compute capability 5.0+ and driver version 531 and newer.
+Ollama supports Nvidia GPUs with compute capability 5.0+.

 Check your compute compatibility to see if your card is supported:
 [https://developer.nvidia.com/cuda-gpus](https://developer.nvidia.com/cuda-gpus)

 | Compute Capability | Family              | Cards                                                                                                       |
 | ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
-| 12.0               | GeForce RTX 50xx    | `RTX 5060` `RTX 5060 Ti` `RTX 5070` `RTX 5070 Ti` `RTX 5080` `RTX 5090`                                     |
-|                    | NVIDIA Professioal  | `RTX PRO 4000 Blackwell` `RTX PRO 4500 Blackwell` `RTX PRO 5000 Blackwell` `RTX PRO 6000 Blackwell`         |
 | 9.0                | NVIDIA              | `H200` `H100`                                                                                               |
 | 8.9                | GeForce RTX 40xx    | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060`  |
 |                    | NVIDIA Professional | `L4` `L40` `RTX 6000`                                                                                       |
--- a/docs/import.md
+++ b/docs/import.md
@@ -53,8 +53,6 @@ FROM /path/to/safetensors/directory

 If you create the Modelfile in the same directory as the weights, you can use the command `FROM .`.

-If you do not create the Modelfile, ollama will act as if there was a Modelfile with the command `FROM .`.
-
 Now run the `ollama create` command from the directory where you created the `Modelfile`:

 ```shell
@@ -134,12 +132,22 @@ success

 ### Supported Quantizations

+- `q4_0`
+- `q4_1`
+- `q5_0`
+- `q5_1`
 - `q8_0`

 #### K-means Quantizations

+- `q3_K_S`
+- `q3_K_M`
+- `q3_K_L`
 - `q4_K_S`
 - `q4_K_M`
+- `q5_K_S`
+- `q5_K_M`
+- `q6_K`


 ## Sharing your model on ollama.com
--- a/docs/linux.md
+++ b/docs/linux.md
@@ -11,13 +11,12 @@ curl -fsSL https://ollama.com/install.sh | sh
 ## Manual install

 > [!NOTE]
-> If you are upgrading from a prior version, you **MUST** remove the old libraries with `sudo rm -rf /usr/lib/ollama` first.
+> If you are upgrading from a prior version, you should remove the old libraries with `sudo rm -rf /usr/lib/ollama` first.

 Download and extract the package:

 ```shell
-curl -LO https://ollama.com/download/ollama-linux-amd64.tgz
-sudo rm -rf /usr/lib/ollama
+curl -L https://ollama.com/download/ollama-linux-amd64.tgz -o ollama-linux-amd64.tgz
 sudo tar -C /usr -xzf ollama-linux-amd64.tgz
 ```

@@ -35,11 +34,7 @@ ollama -v

 ### AMD GPU install

-If you have an AMD GPU, **also** download and extract the additional ROCm package:
-
-> [!IMPORTANT]
-> The ROCm tgz contains only AMD dependent libraries.  You must extract **both** `ollama-linux-amd64.tgz` and `ollama-linux-amd64-rocm.tgz` into the same location.
-
+If you have an AMD GPU, also download and extract the additional ROCm package:

 ```shell
 curl -L https://ollama.com/download/ollama-linux-amd64-rocm.tgz -o ollama-linux-amd64-rocm.tgz
@@ -117,8 +112,8 @@ sudo systemctl status ollama
 > While AMD has contributed the `amdgpu` driver upstream to the official linux
 > kernel source, the version is older and may not support all ROCm features. We
 > recommend you install the latest driver from
-> [AMD](https://www.amd.com/en/support/download/linux-drivers.html) for best support
-> of your Radeon GPU.
+> https://www.amd.com/en/support/linux-drivers for best support of your Radeon
+> GPU.

 ## Customizing

--- a/docs/macos.md
+++ b/docs/macos.md
@@ -1,42 +0,0 @@
-# Ollama for macOS
-
-## System Requirements
-
-* MacOS Monterey (v12) or newer
-* Apple M series (CPU and GPU support) or x86 (CPU only)
-
-
-## Filesystem Requirements
-
-The preferred method of installation is to mount the `ollama.dmg` and drag-and-drop the Ollama application to the system-wide `Applications` folder.  Upon startup, the Ollama app will verify the `ollama` CLI is present in your PATH, and if not detected, will prompt for permission to create a link in `/usr/local/bin`
-
-Once you've installed Ollama, you'll need additional space for storing the Large Language models, which can be tens to hundreds of GB in size.  If your home directory doesn't have enough space, you can change where the binaries are installed, and where the models are stored.
-
-### Changing Install Location
-
-To install the Ollama application somewhere other than `Applications`, place the Ollama application in the desired location, and ensure the CLI `Ollama.app/Contents/Resources/ollama` or a sym-link to the CLI can be found in your path.  Upon first start decline the "Move to Applications?" request.
-
-
-## Troubleshooting
-
-Ollama on MacOS stores files in a few different locations.
- `~/.ollama` contains models and configuration
- `~/.ollama/logs` contains logs
-    - *app.log* contains most recent logs from the GUI application
-    - *server.log* contains the most recent server logs
- `<install location>/Ollama.app/Contents/Resources/ollama` the CLI binary
-
-## Uninstall
-
-To fully remove Ollama from your system, remove the following files and folders:
-
-```
-sudo rm -rf /Applications/Ollama.app
-sudo rm /usr/local/bin/ollama
-rm -rf "~/Library/Application Support/Ollama"
-rm -rf "~/Library/Saved Application State/com.electron.ollama.savedState"
-rm -rf ~/Library/Caches/com.electron.ollama/
-rm -rf ~/Library/Caches/ollama
-rm -rf ~/Library/WebKit/com.electron.ollama
-rm -rf ~/.ollama
-```
--- a/docs/modelfile.md
+++ b/docs/modelfile.md
@@ -150,7 +150,10 @@ PARAMETER <parameter> <parametervalue>

 | Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage        |
 | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
-| num_ctx        | Sets the size of the context window used to generate the next token. (Default: 4096)                                                                                                                                                                    | int        | num_ctx 4096         |
+| mirostat       | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)                                                                                                                                         | int        | mirostat 0           |
+| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                        | float      | mirostat_eta 0.1     |
+| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                         | float      | mirostat_tau 5.0     |
+| num_ctx        | Sets the size of the context window used to generate the next token. (Default: 2048)                                                                                                                                                                    | int        | num_ctx 4096         |
 | repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)                                                                                                                                           | int        | repeat_last_n 64     |
 | repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                     | float      | repeat_penalty 1.1   |
 | temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                     | float      | temperature 0.7      |
--- a/docs/openai.md
+++ b/docs/openai.md
@@ -72,7 +72,7 @@ client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")
 # Define the schema for the response
 class FriendInfo(BaseModel):
    name: str
-    age: int
+    age: int 
    is_available: bool

 class FriendList(BaseModel):
--- a/docs/troubleshooting.md
+++ b/docs/troubleshooting.md
@@ -9,7 +9,7 @@ cat ~/.ollama/logs/server.log
 On **Linux** systems with systemd, the logs can be found with this command:

 ```shell
-journalctl -u ollama --no-pager --follow --pager-end
+journalctl -u ollama --no-pager --follow --pager-end 
 ```

 When you run Ollama in a **container**, the logs go to stdout/stderr in the container:
@@ -23,7 +23,7 @@ docker logs <container-name>
 If manually running `ollama serve` in a terminal, the logs will be on that terminal.

 When you run Ollama on **Windows**, there are a few different locations. You can view them in the explorer window by hitting `<cmd>+R` and type in:
- `explorer %LOCALAPPDATA%\Ollama` to view logs.  The most recent server logs will be in `server.log` and older logs will be in `server-#.log`
+- `explorer %LOCALAPPDATA%\Ollama` to view logs.  The most recent server logs will be in `server.log` and older logs will be in `server-#.log` 
 - `explorer %LOCALAPPDATA%\Programs\Ollama` to browse the binaries (The installer adds this to your user PATH)
 - `explorer %HOMEPATH%\.ollama` to browse where models and configuration is stored

@@ -38,12 +38,12 @@ Join the [Discord](https://discord.gg/ollama) for help interpreting the logs.

 ## LLM libraries

-Ollama includes multiple LLM libraries compiled for different GPUs and CPU vector features. Ollama tries to pick the best one based on the capabilities of your system. If this autodetection has problems, or you run into other problems (e.g. crashes in your GPU) you can workaround this by forcing a specific LLM library. `cpu_avx2` will perform the best, followed by `cpu_avx` and the slowest but most compatible is `cpu`. Rosetta emulation under MacOS will work with the `cpu` library.
+Ollama includes multiple LLM libraries compiled for different GPUs and CPU vector features. Ollama tries to pick the best one based on the capabilities of your system. If this autodetection has problems, or you run into other problems (e.g. crashes in your GPU) you can workaround this by forcing a specific LLM library. `cpu_avx2` will perform the best, followed by `cpu_avx` an the slowest but most compatible is `cpu`. Rosetta emulation under MacOS will work with the `cpu` library. 

 In the server log, you will see a message that looks something like this (varies from release to release):

 ```
-Dynamic LLM libraries [rocm_v6 cpu cpu_avx cpu_avx2 cuda_v12 rocm_v5]
+Dynamic LLM libraries [rocm_v6 cpu cpu_avx cpu_avx2 cuda_v11 rocm_v5]
 ```

 **Experimental LLM Library Override**
@@ -92,15 +92,12 @@ If none of those resolve the problem, gather additional information and file an
 - Set `CUDA_ERROR_LEVEL=50` and try again to get more diagnostic logs
 - Check dmesg for any errors `sudo dmesg | grep -i nvrm` and `sudo dmesg | grep -i nvidia`

-You may get more details for initialization failures by enabling debug prints in the uvm driver.  You should only use this temporarily while troubleshooting
- `sudo rmmod nvidia_uvm` then `sudo modprobe nvidia_uvm uvm_debug_prints=1`
-

 ## AMD GPU Discovery

 On linux, AMD GPU access typically requires `video` and/or `render` group membership to access the `/dev/kfd` device.  If permissions are not set up correctly, Ollama will detect this and report an error in the server log.

-When running in a container, in some Linux distributions and container runtimes, the ollama process may be unable to access the GPU.  Use `ls -lnd /dev/kfd /dev/dri /dev/dri/*` on the host system to determine the **numeric** group IDs on your system, and pass additional `--group-add ...` arguments to the container so it can access the required devices.   For example, in the following output `crw-rw---- 1 0  44 226,   0 Sep 16 16:55 /dev/dri/card0` the group ID column is `44`
+When running in a container, in some Linux distributions and container runtimes, the ollama process may be unable to access the GPU.  Use `ls -lnd /dev/kfd /dev/dri /dev/dri/*` on the host system to determine the **numeric** group IDs on your system, and pass additional `--group-add ...` arguments to the container so it can access the required devices.   For example, in the following output `crw-rw---- 1 0  44 226,   0 Sep 16 16:55 /dev/dri/card0` the group ID column is `44` 

 If you are experiencing problems getting Ollama to correctly discover or use your GPU for inference, the following may help isolate the failure.
 - `AMD_LOG_LEVEL=3` Enable info log levels in the AMD HIP/ROCm libraries.  This can help show more detailed error codes that can help troubleshoot problems
--- a/docs/windows.md
+++ b/docs/windows.md
@@ -30,6 +30,20 @@ To install the Ollama application in a location different than your home directo
 OllamaSetup.exe /DIR="d:\some\location"
 ```

+### Changing Model Location
+
+To change where Ollama stores the downloaded models instead of using your home directory, set the environment variable `OLLAMA_MODELS` in your user account.
+
+1. Start the Settings (Windows 11) or Control Panel (Windows 10) application and search for _environment variables_.
+
+2. Click on _Edit environment variables for your account_.
+
+3. Edit or create a new variable for your user account for `OLLAMA_MODELS` where you want the models stored
+
+4. Click OK/Apply to save.
+
+If Ollama is already running, Quit the tray application and relaunch it from the Start menu, or a new terminal started after you saved the environment variables.
+
 ## API Access

 Here's a quick example showing API access from `powershell`
@@ -68,9 +82,9 @@ If you'd like to install or integrate Ollama as a service, a standalone
 `ollama-windows-amd64.zip` zip file is available containing only the Ollama CLI
 and GPU library dependencies for Nvidia.  If you have an AMD GPU, also download
 and extract the additional ROCm package `ollama-windows-amd64-rocm.zip` into the
-same directory.  Both zip files are necessary for a complete AMD installation.
-This allows for embedding Ollama in existing applications, or running it as a
-system service via `ollama serve` with tools such as [NSSM](https://nssm.cc/). 
+same directory.  This allows for embedding Ollama in existing applications, or
+running it as a system service via `ollama serve` with tools such as
+[NSSM](https://nssm.cc/). 

 > [!NOTE]  
 > If you are upgrading from a prior version, you should remove the old directories first.
--- a/envconfig/config.go
+++ b/envconfig/config.go
@@ -134,17 +134,6 @@ func LoadTimeout() (loadTimeout time.Duration) {
 	return loadTimeout
 }

-func Remotes() []string {
-	var r []string
-	raw := strings.TrimSpace(Var("OLLAMA_REMOTES"))
-	if raw == "" {
-		r = []string{"ollama.com"}
-	} else {
-		r = strings.Split(raw, ",")
-	}
-	return r
-}
-
 func Bool(k string) func() bool {
 	return func() bool {
 		if s := Var(k); s != "" {
@@ -160,22 +149,9 @@ func Bool(k string) func() bool {
 	}
 }

-// LogLevel returns the log level for the application.
-// Values are 0 or false INFO (Default), 1 or true DEBUG, 2 TRACE
-func LogLevel() slog.Level {
-	level := slog.LevelInfo
-	if s := Var("OLLAMA_DEBUG"); s != "" {
-		if b, _ := strconv.ParseBool(s); b {
-			level = slog.LevelDebug
-		} else if i, _ := strconv.ParseInt(s, 10, 64); i != 0 {
-			level = slog.Level(i * -4)
-		}
-	}
-
-	return level
-}
-
 var (
+	// Debug enabled additional debug information.
+	Debug = Bool("OLLAMA_DEBUG")
 	// FlashAttention enables the experimental flash attention feature.
 	FlashAttention = Bool("OLLAMA_FLASH_ATTENTION")
 	// KvCacheType is the quantization type for the K/V cache.
@@ -193,9 +169,7 @@ var (
 	// Enable the new Ollama engine
 	NewEngine = Bool("OLLAMA_NEW_ENGINE")
 	// ContextLength sets the default context length
-	ContextLength = Uint("OLLAMA_CONTEXT_LENGTH", 4096)
-	// Auth enables authentication between the Ollama client and server
-	UseAuth = Bool("OLLAMA_AUTH")
+	ContextLength = Int64("OLLAMA_CONTEXT_LENGTH", -1)
 )

 func String(s string) func() string {
@@ -230,11 +204,13 @@ func Uint(key string, defaultValue uint) func() uint {

 var (
 	// NumParallel sets the number of parallel model requests. NumParallel can be configured via the OLLAMA_NUM_PARALLEL environment variable.
-	NumParallel = Uint("OLLAMA_NUM_PARALLEL", 1)
+	NumParallel = Uint("OLLAMA_NUM_PARALLEL", 0)
 	// MaxRunners sets the maximum number of loaded models. MaxRunners can be configured via the OLLAMA_MAX_LOADED_MODELS environment variable.
 	MaxRunners = Uint("OLLAMA_MAX_LOADED_MODELS", 0)
 	// MaxQueue sets the maximum number of queued requests. MaxQueue can be configured via the OLLAMA_MAX_QUEUE environment variable.
 	MaxQueue = Uint("OLLAMA_MAX_QUEUE", 512)
+	// MaxVRAM sets a maximum VRAM override in bytes. MaxVRAM can be configured via the OLLAMA_MAX_VRAM environment variable.
+	MaxVRAM = Uint("OLLAMA_MAX_VRAM", 0)
 )

 func Uint64(key string, defaultValue uint64) func() uint64 {
@@ -251,6 +227,20 @@ func Uint64(key string, defaultValue uint64) func() uint64 {
 	}
 }

+func Int64(key string, defaultValue int64) func() int64 {
+	return func() int64 {
+		if s := Var(key); s != "" {
+			if n, err := strconv.ParseInt(s, 10, 64); err != nil {
+				slog.Warn("invalid environment variable, using default", "key", key, "value", s, "default", defaultValue)
+			} else {
+				return n
+			}
+		}
+
+		return defaultValue
+	}
+}
+
 // Set aside VRAM per GPU
 var GpuOverhead = Uint64("OLLAMA_GPU_OVERHEAD", 0)

@@ -262,7 +252,7 @@ type EnvVar struct {

 func AsMap() map[string]EnvVar {
 	ret := map[string]EnvVar{
-		"OLLAMA_DEBUG":             {"OLLAMA_DEBUG", LogLevel(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
+		"OLLAMA_DEBUG":             {"OLLAMA_DEBUG", Debug(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
 		"OLLAMA_FLASH_ATTENTION":   {"OLLAMA_FLASH_ATTENTION", FlashAttention(), "Enabled flash attention"},
 		"OLLAMA_KV_CACHE_TYPE":     {"OLLAMA_KV_CACHE_TYPE", KvCacheType(), "Quantization type for the K/V cache (default: f16)"},
 		"OLLAMA_GPU_OVERHEAD":      {"OLLAMA_GPU_OVERHEAD", GpuOverhead(), "Reserve a portion of VRAM per GPU (bytes)"},
@@ -279,9 +269,8 @@ func AsMap() map[string]EnvVar {
 		"OLLAMA_ORIGINS":           {"OLLAMA_ORIGINS", AllowedOrigins(), "A comma separated list of allowed origins"},
 		"OLLAMA_SCHED_SPREAD":      {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
 		"OLLAMA_MULTIUSER_CACHE":   {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
-		"OLLAMA_CONTEXT_LENGTH":    {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4096)"},
+		"OLLAMA_CONTEXT_LENGTH":    {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default 4096 or 2048 with low VRAM)"},
 		"OLLAMA_NEW_ENGINE":        {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
-		"OLLAMA_REMOTES":           {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},

 		// Informational
 		"HTTP_PROXY":  {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},
--- a/envconfig/config_test.go
+++ b/envconfig/config_test.go
@@ -1,13 +1,11 @@
 package envconfig

 import (
-	"log/slog"
 	"math"
 	"testing"
 	"time"

 	"github.com/google/go-cmp/cmp"
-	"github.com/ollama/ollama/logutil"
 )

 func TestHost(t *testing.T) {
@@ -280,9 +278,9 @@ func TestVar(t *testing.T) {
 }

 func TestContextLength(t *testing.T) {
-	cases := map[string]uint{
-		"":     4096,
-		"2048": 2048,
+	cases := map[string]int64{
+		"":     -1,
+		"4096": 4096,
 	}

 	for k, v := range cases {
@@ -294,34 +292,3 @@ func TestContextLength(t *testing.T) {
 		})
 	}
 }
-
-func TestLogLevel(t *testing.T) {
-	cases := map[string]slog.Level{
-		// Default to INFO
-		"":      slog.LevelInfo,
-		"false": slog.LevelInfo,
-		"f":     slog.LevelInfo,
-		"0":     slog.LevelInfo,
-
-		// True values enable Debug
-		"true": slog.LevelDebug,
-		"t":    slog.LevelDebug,
-
-		// Positive values increase verbosity
-		"1": slog.LevelDebug,
-		"2": logutil.LevelTrace,
-
-		// Negative values decrease verbosity
-		"-1": slog.LevelWarn,
-		"-2": slog.LevelError,
-	}
-
-	for k, v := range cases {
-		t.Run(k, func(t *testing.T) {
-			t.Setenv("OLLAMA_DEBUG", k)
-			if i := LogLevel(); i != v {
-				t.Errorf("%s: expected %d, got %d", k, v, i)
-			}
-		})
-	}
-}
--- a/fs/config.go
+++ b/fs/config.go
@@ -10,5 +10,4 @@ type Config interface {
 	Strings(string, ...[]string) []string
 	Ints(string, ...[]int32) []int32
 	Floats(string, ...[]float32) []float32
-	Bools(string, ...[]bool) []bool
 }
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -1,24 +1,20 @@
 package ggml

 import (
-	"cmp"
 	"encoding/binary"
 	"errors"
 	"fmt"
 	"io"
 	"log/slog"
-	"math"
 	"slices"
 	"strings"

-	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/fs/util/bufioutil"
 )

 type GGML struct {
 	container
 	model
-	Length int64
 }

 type model interface {
@@ -37,16 +33,15 @@ func (kv KV) Kind() string {
 }

 func (kv KV) ParameterCount() uint64 {
-	val, _ := keyValue(kv, "general.parameter_count", uint64(0))
-	return val
+	return keyValue(kv, "general.parameter_count", uint64(0))
 }

-func (kv KV) FileType() FileType {
+func (kv KV) FileType() fileType {
 	if t := kv.Uint("general.file_type"); t > 0 {
-		return FileType(t)
+		return fileType(t)
 	}

-	return FileTypeUnknown
+	return fileTypeUnknown
 }

 func (kv KV) BlockCount() uint64 {
@@ -57,66 +52,16 @@ func (kv KV) EmbeddingLength() uint64 {
 	return uint64(kv.Uint("embedding_length"))
 }

-func (kv KV) HeadCount() []uint64 {
-	headCountDefault := uint32(1)
-	headCount := kv.UintOrArrayValueAsArray("attention.head_count", headCountDefault)
-	if len(headCount) == 1 {
-		headCountDefault = headCount[0]
-	}
-	nLayers := int(kv.BlockCount())
-	if len(headCount) > nLayers {
-		slog.Warn("got more elements of attention.head_count than layers", "len(headCount)", len(headCount), "layers", nLayers)
-	}
-	out := make([]uint64, nLayers)
-	for i := range nLayers {
-		if i >= len(headCount) {
-			out[i] = uint64(headCountDefault)
-		} else {
-			out[i] = uint64(headCount[i])
-		}
-	}
-	return out
+func (kv KV) HeadCount() uint64 {
+	return uint64(kv.Uint("attention.head_count"))
 }

-func (kv KV) HeadCountMax() uint64 {
-	return uint64(kv.UintOrMaxArrayValue("attention.head_count", 1))
+func (kv KV) HeadCountKV() uint64 {
+	return uint64(kv.Uint("attention.head_count_kv", 1))
 }

-func (kv KV) HeadCountMin() uint64 {
-	return uint64(kv.UintOrMinArrayValue("attention.head_count", 1))
-}
-
-func (kv KV) HeadCountKV() []uint64 {
-	headCountKVDefault := uint32(1)
-	headCountKV := kv.UintOrArrayValueAsArray("attention.head_count_kv", headCountKVDefault)
-	if len(headCountKV) == 1 {
-		headCountKVDefault = headCountKV[0]
-	}
-	nLayers := int(kv.BlockCount())
-	if len(headCountKV) > nLayers {
-		slog.Warn("got more elements of attention.head_count than layers", "len(headCountKV)", len(headCountKV), "layers", nLayers)
-	}
-	out := make([]uint64, nLayers)
-	for i := range nLayers {
-		if i >= len(headCountKV) {
-			out[i] = uint64(headCountKVDefault)
-		} else {
-			out[i] = uint64(headCountKV[i])
-		}
-	}
-	return out
-}
-
-func (kv KV) HeadCountKVMax() uint64 {
-	return uint64(kv.UintOrMaxArrayValue("attention.head_count_kv", 1))
-}
-
-func (kv KV) HeadCountKVMin() uint64 {
-	return uint64(kv.UintOrMinArrayValue("attention.head_count_kv", 1))
-}
-
-func (kv KV) EmbeddingHeadCountMax() uint64 {
-	if heads := kv.HeadCountMin(); heads > 0 {
+func (kv KV) EmbeddingHeadCount() uint64 {
+	if heads := kv.HeadCount(); heads > 0 {
 		return kv.EmbeddingLength() / heads
 	}

@@ -124,11 +69,15 @@ func (kv KV) EmbeddingHeadCountMax() uint64 {
 }

 func (kv KV) EmbeddingHeadCountK() uint64 {
-	return uint64(kv.Uint("attention.key_length", uint32(kv.EmbeddingHeadCountMax())))
+	return uint64(kv.Uint("attention.key_length", uint32(kv.EmbeddingHeadCount())))
 }

 func (kv KV) EmbeddingHeadCountV() uint64 {
-	return uint64(kv.Uint("attention.value_length", uint32(kv.EmbeddingHeadCountMax())))
+	return uint64(kv.Uint("attention.value_length", uint32(kv.EmbeddingHeadCount())))
+}
+
+func (kv KV) GQA() uint64 {
+	return kv.HeadCount() / kv.HeadCountKV()
 }

 func (kv KV) ContextLength() uint64 {
@@ -139,116 +88,43 @@ func (kv KV) ChatTemplate() string {
 	return kv.String("tokenizer.chat_template")
 }

-// ssm architecture parameters
-
-func (kv KV) SSMConvKernel() uint64 {
-	return uint64(kv.Uint("ssm.conv_kernel"))
-}
-
-func (kv KV) SSMInnerSize() uint64 {
-	return uint64(kv.Uint("ssm.inner_size"))
-}
-
-func (kv KV) SSMStateSize() uint64 {
-	return uint64(kv.Uint("ssm.state_size"))
-}
-
-func (kv KV) SSMGroupCount() uint64 {
-	return uint64(kv.Uint("ssm.group_count"))
-}
-
-// general types
-
 func (kv KV) String(key string, defaultValue ...string) string {
-	val, _ := keyValue(kv, key, append(defaultValue, "")...)
-	return val
+	return keyValue(kv, key, append(defaultValue, "")...)
 }

 func (kv KV) Uint(key string, defaultValue ...uint32) uint32 {
-	val, _ := keyValue(kv, key, append(defaultValue, 0)...)
-	return val
+	return keyValue(kv, key, append(defaultValue, 0)...)
 }

 func (kv KV) Float(key string, defaultValue ...float32) float32 {
-	val, _ := keyValue(kv, key, append(defaultValue, 0)...)
-	return val
+	return keyValue(kv, key, append(defaultValue, 0)...)
 }

 func (kv KV) Bool(key string, defaultValue ...bool) bool {
-	val, _ := keyValue(kv, key, append(defaultValue, false)...)
-	return val
-}
-
-func (kv KV) UintOrMaxArrayValue(key string, defaultValue uint32) uint32 {
-	_, max := kv.UintOrArrayValue(key, defaultValue)
-	return max
-}
-
-func (kv KV) UintOrMinArrayValue(key string, defaultValue uint32) uint32 {
-	min, _ := kv.UintOrArrayValue(key, defaultValue)
-	return min
-}
-
-func (kv KV) UintOrArrayValue(key string, defaultValue uint32) (uint32, uint32) {
-	arrVal := kv.UintOrArrayValueAsArray(key, defaultValue)
-	return slices.Min(arrVal), slices.Max(arrVal)
-}
-
-func (kv KV) UintOrArrayValueAsArray(key string, defaultValue uint32) []uint32 {
-	if u32, ok := keyValue(kv, key, uint32(0)); ok {
-		return []uint32{u32}
-	} else if u32s, ok := keyValue(kv, key, &array[uint32]{}); ok {
-		return u32s.values
-	} else if i32s, ok := keyValue(kv, key, &array[int32]{}); ok {
-		dst := make([]uint32, len(i32s.values))
-		for i, v := range i32s.values {
-			if v < 0 {
-				slog.Warn("array values are unexpectedly negative", "key", key, "i", i, "v", v)
-			}
-			dst[i] = uint32(v)
-		}
-		return dst
-	}
-
-	return []uint32{defaultValue}
+	return keyValue(kv, key, append(defaultValue, false)...)
 }

 func (kv KV) Strings(key string, defaultValue ...[]string) []string {
-	val, _ := keyValue(kv, key, &array[string]{values: append(defaultValue, []string(nil))[0]})
-	return val.values
+	return keyValue(kv, key, &array[string]{values: append(defaultValue, []string(nil))[0]}).values
 }

 func (kv KV) Ints(key string, defaultValue ...[]int32) []int32 {
-	val, _ := keyValue(kv, key, &array[int32]{values: append(defaultValue, []int32(nil))[0]})
-	return val.values
+	return keyValue(kv, key, &array[int32]{values: append(defaultValue, []int32(nil))[0]}).values
 }

 func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
-	val, _ := keyValue(kv, key, &array[uint32]{values: append(defaultValue, []uint32(nil))[0]})
-	return val.values
+	return keyValue(kv, key, &array[uint32]{values: append(defaultValue, []uint32(nil))[0]}).values
 }

 func (kv KV) Floats(key string, defaultValue ...[]float32) []float32 {
-	val, _ := keyValue(kv, key, &array[float32]{values: append(defaultValue, []float32(nil))[0]})
-	return val.values
-}
-
-func (kv KV) Bools(key string, defaultValue ...[]bool) []bool {
-	val, _ := keyValue(kv, key, &array[bool]{values: append(defaultValue, []bool(nil))[0]})
-	return val.values
+	return keyValue(kv, key, &array[float32]{values: append(defaultValue, []float32(nil))[0]}).values
 }

 func (kv KV) OllamaEngineRequired() bool {
 	return slices.Contains([]string{
 		"gemma3",
-		"gemma3n",
 		"mistral3",
-		"qwen3",
-		"qwen3moe",
 		"llama4",
-		"mllama",
-		"qwen25vl",
-		"gptoss", "gpt-oss",
 	}, kv.Architecture())
 }

@@ -264,17 +140,17 @@ type arrayValueTypes interface {
 		*array[string] | *array[float32] | *array[float64] | *array[bool]
 }

-func keyValue[T valueTypes | arrayValueTypes](kv KV, key string, defaultValue ...T) (T, bool) {
+func keyValue[T valueTypes | arrayValueTypes](kv KV, key string, defaultValue ...T) T {
 	if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
 		key = kv.Architecture() + "." + key
 	}

-	if val, ok := kv[key].(T); ok {
-		return val, true
+	if val, ok := kv[key]; ok {
+		return val.(T)
 	}

-	slog.Debug("key with type not found", "key", key, "default", defaultValue[0])
-	return defaultValue[0], false
+	slog.Warn("key not found", "key", key, "default", defaultValue[0])
+	return defaultValue[0]
 }

 type Tensors struct {
@@ -343,37 +219,32 @@ type Tensor struct {

 func (t Tensor) block() (n int) {
 	if _, err := fmt.Sscanf(t.Name, "blk.%d.", &n); err != nil {
-		return math.MaxInt
+		return -1
 	}

 	return
 }

 func (t Tensor) blockSize() uint64 {
-	return TensorType(t.Kind).BlockSize()
-}
-
-func (t TensorType) BlockSize() uint64 {
-	switch t {
+	switch t.Kind {
 	case
-		TensorTypeF32,
-		TensorTypeF16,
-		TensorTypeI8,
-		TensorTypeI16,
-		TensorTypeI32,
-		TensorTypeI64,
-		TensorTypeF64,
-		TensorTypeBF16:
+		0,  // F32
+		1,  // F16
+		24, // I8
+		25, // I16
+		26, // I32
+		27, // I64
+		28, // F64
+		30: // BF16
 		return 1
 	case
-		TensorTypeQ4_0,
-		TensorTypeQ4_1,
-		TensorTypeQ5_0,
-		TensorTypeQ5_1,
-		TensorTypeQ8_0,
-		TensorTypeQ8_1,
-		tensorTypeIQ4_NL,
-		4, TensorTypeMXFP4:
+		2,  // Q4_0
+		3,  // Q4_1
+		6,  // Q5_0
+		7,  // Q5_1
+		8,  // Q8_0
+		9,  // Q8_1
+		20: // IQ4_NL
 		return 32
 	default:
 		return 256
@@ -381,79 +252,73 @@ func (t TensorType) BlockSize() uint64 {
 }

 func (t Tensor) typeSize() uint64 {
-	return TensorType(t.Kind).TypeSize()
-}
+	blockSize := t.blockSize()

-func (t TensorType) TypeSize() uint64 {
-	blockSize := t.BlockSize()
-
-	switch t {
-	case TensorTypeF32:
+	switch t.Kind {
+	case 0: // FP32
 		return 4
-	case TensorTypeF16:
+	case 1: // FP16
 		return 2
-	case TensorTypeQ4_0:
+	case 2: // Q4_0
 		return 2 + blockSize/2
-	case TensorTypeQ4_1:
+	case 3: // Q4_1
 		return 2 + 2 + blockSize/2
-	case TensorTypeQ5_0:
+	case 6: // Q5_0
 		return 2 + 4 + blockSize/2
-	case TensorTypeQ5_1:
+	case 7: // Q5_1
 		return 2 + 2 + 4 + blockSize/2
-	case TensorTypeQ8_0:
+	case 8: // Q8_0
 		return 2 + blockSize
-	case TensorTypeQ8_1:
+	case 9: // Q8_1
 		return 2 + 2 + blockSize
-	case TensorTypeQ2_K:
+	case 10: // Q2_K
 		return blockSize/16 + blockSize/4 + 2 + 2
-	case TensorTypeQ3_K:
+	case 11: // Q3_K
 		return blockSize/8 + blockSize/4 + 12 + 2
-	case TensorTypeQ4_K:
+	case 12: // Q4_K
 		return 2 + 2 + 12 + blockSize/2
-	case TensorTypeQ5_K:
+	case 13: // Q5_K
 		return 2 + 2 + 12 + blockSize/8 + blockSize/2
-	case TensorTypeQ6_K:
+	case 14: // Q6_K
 		return blockSize/2 + blockSize/4 + blockSize/16 + 2
-	case TensorTypeQ8_K:
+	case 15: // Q8_K
 		return 4 + blockSize + 2*blockSize/16
-	case tensorTypeIQ2_XXS:
+	case 16: // IQ2_XXS
 		return 2 + 2*blockSize/8
-	case tensorTypeIQ2_XS:
+	case 17: // IQ2_XS
 		return 2 + 2*blockSize/8 + blockSize/32
-	case tensorTypeIQ3_XXS:
+	case 18: // IQ3_XXS
 		return 2 + blockSize/4 + blockSize/8
-	case tensorTypeIQ1_S:
+	case 19: // IQ1_S
 		return 2 + blockSize/8 + blockSize/16
-	case tensorTypeIQ4_NL:
+	case 20: // IQ4_NL
 		return 2 + blockSize/2
-	case tensorTypeIQ3_S:
+	case 21: // IQ3_S
 		return 2 + blockSize/4 + blockSize/8 + blockSize/32 + 4
-	case tensorTypeIQ2_S:
+	case 22: // IQ2_S
 		return 2 + blockSize/4 + blockSize/16
-	case tensorTypeIQ4_XS:
+	case 23: // IQ4_XS
 		return 2 + 2 + blockSize/2 + blockSize/64
-	case TensorTypeI8:
+	case 24: // I8
 		return 1
-	case TensorTypeI16:
+	case 25: // I16
 		return 2
-	case TensorTypeI32:
+	case 26: // I32
 		return 4
-	case TensorTypeI64:
+	case 27: // I64
 		return 8
-	case TensorTypeF64:
+	case 28: // F64
 		return 8
-	case tensorTypeIQ1_M:
+	case 29: // IQ1_M
 		return blockSize/8 + blockSize/16 + blockSize/32
-	case TensorTypeBF16:
+	case 30: // BF16
 		return 2
-	case 4, TensorTypeMXFP4:
-		return 1 + blockSize/2
 	default:
 		return 0
 	}
 }

-func (t Tensor) Elements() uint64 {
+func (t Tensor) parameters() uint64 {
 	var count uint64 = 1
 	for _, n := range t.Shape {
 		count *= n
@@ -462,11 +327,11 @@ func (t Tensor) Elements() uint64 {
 }

 func (t Tensor) Size() uint64 {
-	return t.Elements() * t.typeSize() / t.blockSize()
+	return t.parameters() * t.typeSize() / t.blockSize()
 }

 func (t Tensor) Type() string {
-	return TensorType(t.Kind).String()
+	return fileType(t.Kind).String()
 }

 type container interface {
@@ -511,12 +376,12 @@ func DetectContentType(b []byte) string {
 //
 // It collects array values for arrays with a size less than or equal to
 // maxArraySize. If the maxArraySize is negative, all arrays are collected.
-func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, error) {
+func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
 	rs = bufioutil.NewBufferedSeeker(rs, 32<<10)

 	var magic uint32
 	if err := binary.Read(rs, binary.LittleEndian, &magic); err != nil {
-		return nil, err
+		return nil, 0, err
 	}

 	var c container
@@ -526,89 +391,43 @@ func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, error) {
 	case FILE_MAGIC_GGUF_BE:
 		c = &containerGGUF{ByteOrder: binary.BigEndian, maxArraySize: maxArraySize}
 	default:
-		return nil, errors.New("invalid file magic")
+		return nil, 0, errors.New("invalid file magic")
 	}

 	model, err := c.Decode(rs)
 	if err != nil {
-		return nil, err
+		return nil, 0, err
 	}

 	offset, err := rs.Seek(0, io.SeekCurrent)
 	if err != nil {
-		return nil, err
+		return nil, 0, err
 	}

 	// final model type
 	return &GGML{
 		container: c,
 		model:     model,
-		Length:    offset,
-	}, nil
+	}, offset, nil
 }

-func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType string, useFlashAttention bool) (kv []uint64, partialOffload, fullOffload uint64) {
-	context *= uint64(numParallel)
-
+func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType string) (kv []uint64, partialOffload, fullOffload uint64) {
 	embedding := f.KV().EmbeddingLength()
-	heads := f.KV().HeadCountMax()
-	headsArr := f.KV().HeadCount()
-	headsKV := f.KV().HeadCountKVMax()
-	headsKVArr := f.KV().HeadCountKV()
+	heads := f.KV().HeadCount()
+	headsKV := f.KV().HeadCountKV()
 	vocab := uint64(f.KV()["tokenizer.ggml.tokens"].(*array[string]).size)

-	embeddingHeads := f.KV().EmbeddingHeadCountMax()
+	embeddingHeads := f.KV().EmbeddingHeadCount()
 	embeddingHeadsK := f.KV().EmbeddingHeadCountK()
 	embeddingHeadsV := f.KV().EmbeddingHeadCountV()

 	layers := f.Tensors().GroupLayers()

 	bytesPerElement := kvCacheBytesPerElement(kvCacheType)
-
-	// Default for models unless special-cased below. These defaults mirror the
-	// cache usage in llama.cpp under the assumption that models without special
-	// cases below will use the llamarunner and caching will be handled by the
-	// llama.cpp layer.
-	//
-	// This also assumes that a layer without heads or headsKV set is recurrent
-	// which is usually the case. Some models (eg nemotronh) use "blocks" in
-	// place of layers where some are MLP blocks that don't have any cache.
-	// Models like this will need a special case below to be accurately
-	// estimated.
-	var kvTotal uint64
 	kv = make([]uint64, f.KV().BlockCount())
-	kvSizeAttn := uint64(0)
-	kvSizeRecurrent := uint64(0)
 	for i := range kv {
-		headsL := headsArr[i]
-		headsKVL := headsKVArr[i]
-		if headsL > 0 && headsKVL > 0 {
-			// full attention layer
-			// NOTE: Assumes uniform values for all attn layers
-			kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKVL) * bytesPerElement)
-			kvSizeAttn += kv[i]
-		} else {
-			// recurrent layer
-			ssmDConv := f.KV().SSMConvKernel()
-			ssmDState := f.KV().SSMStateSize()
-			ssmDInner := f.KV().SSMInnerSize()
-			ssmNGroups := f.KV().SSMGroupCount()
-			nEmbdR := uint64(0)
-			if ssmDConv > 0 {
-				nEmbdR = (ssmDConv - 1) * (ssmDInner + 2*ssmNGroups*ssmDState)
-			}
-			nEmbdS := ssmDState * ssmDInner
-
-			// recurrent always uses F32 in llama.cpp backend
-			// https://github.com/ggml-org/llama.cpp/blob/master/src/llama-model.cpp#L18644
-			bytesPerElementRecurrent := kvCacheBytesPerElement("f32")
-
-			kv[i] = (nEmbdR + nEmbdS) * uint64(bytesPerElementRecurrent)
-			kvSizeRecurrent += kv[i]
-		}
-		kvTotal += kv[i]
+		kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
 	}
-	slog.Debug("default cache size estimate", "attention MiB", float32(kvSizeAttn)/(1024.*1024.), "attention bytes", kvSizeAttn, "recurrent MiB", float32(kvSizeRecurrent)/(1024.*1024.), "recurrent bytes", kvSizeRecurrent)

 	switch f.KV().Architecture() {
 	case "llama", "llama4":
@@ -661,7 +480,7 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 		var ropeFreqsCount uint64
 		if ropeFreqs, ok := f.Tensors().GroupLayers()["rope_freqs"]; ok {
 			if ropeFreqsWeights, ok := ropeFreqs["weights"]; ok {
-				ropeFreqsCount = ropeFreqsWeights.Elements()
+				ropeFreqsCount = ropeFreqsWeights.parameters()
 			}
 		}

@@ -673,7 +492,7 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 			// vocab graph
 			4*batch*(embedding+vocab)+embedding*vocab*105/128,
 		)
-	case "gemma", "gemma2", "gemma3", "gemma3n":
+	case "gemma", "gemma2", "gemma3":
 		fullOffload = max(
 			4*batch*(embedding+vocab),
 			4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
@@ -686,11 +505,6 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 				embedding*embeddingHeadsK*heads*9/16,
 		)

-		if f.KV().Architecture() == "gemma3n" {
-			fullOffload *= 4
-			partialOffload *= 4
-		}
-
 		// Gemma2 also has sliding window attention but we only have an optimized implementation in the Ollama
 		// engine. Gemma3 always uses the Ollama engine.
 		if f.KV().Architecture() == "gemma3" {
@@ -776,22 +590,6 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 					4*qkvBias.Shape[0],
 			)
 		}
-	case "gptoss", "gpt-oss":
-		kv = make([]uint64, f.KV().BlockCount())
-		for i := range kv {
-			kv[i] = uint64(float64((embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
-			if i%2 == 0 {
-				kv[i] *= (uint64(numParallel)*4096 + batch)
-			} else {
-				kv[i] *= context
-			}
-		}
-
-		partialOffload = 2 * f.KV().HeadCountMax() / cmp.Or(f.KV().HeadCountKVMin(), 1) * kvTotal / 6
-		if useFlashAttention {
-			// rough estimate of graph size with flash attention on
-			partialOffload = (4*uint64(numParallel) + context>>10 + 110) * format.MebiByte
-		}
 	}

 	return
@@ -842,20 +640,6 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 		graphSize = 4 * (imageSize*imageSize*numChannels +
 			embeddingLength*patchSize +
 			numPatches*numPatches*headCount)
-	case "qwen25vl":
-		maxPixels := uint64(llm.KV().Uint("vision.max_pixels", 28*28*1280))
-
-		numPatches := maxPixels / (patchSize * patchSize)
-
-		graphSize = 4 * (maxPixels*numChannels + // Original image storage
-			// Normalized pixels
-			maxPixels*numChannels +
-			// Patches storage (numPatches * channels * patchSize^2)
-			numPatches*numChannels*patchSize*patchSize +
-			// Self-attention calculations
-			numPatches*numPatches*headCount +
-			// Additional buffer for processing
-			embeddingLength*numPatches)
 	case "llama4":
 		// vision graph is computed independently in the same schedule
 		// and is negligible compared to the worst case text graph
@@ -866,16 +650,7 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {

 // SupportsKVCacheType checks if the requested cache type is supported
 func (f GGML) SupportsKVCacheType(cacheType string) bool {
-	if cacheType == "" || cacheType == "f16" {
-		return true
-	}
-
-	if arch := f.KV().Architecture(); slices.Contains([]string{"gptoss", "gpt-oss"}, arch) {
-		// gpt-oss uses attention with sinks which does not support quantized cache types
-		slog.Warn("model only supports non-quantized cache types", "model", arch)
-		return false
-	}
-	return slices.Contains([]string{"q8_0", "q4_0"}, cacheType)
+	return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
 }

 // SupportsFlashAttention checks if the model supports flash attention
@@ -885,23 +660,12 @@ func (f GGML) SupportsFlashAttention() bool {
 		return false
 	}

-	if arch := f.KV().Architecture(); slices.Contains([]string{"gemma2"}, arch) {
-		return false
-	}
-
 	// Check head counts match and are non-zero
 	headCountK := f.KV().EmbeddingHeadCountK()
 	headCountV := f.KV().EmbeddingHeadCountV()
 	return headCountK != 0 && headCountV != 0 && headCountK == headCountV
 }

-// FlashAttention checks if the model should enable flash attention
-func (f GGML) FlashAttention() bool {
-	return slices.Contains([]string{
-		"gptoss", "gpt-oss",
-	}, f.KV().String("general.architecture"))
-}
-
 // kvCacheBytesPerElement returns the number of bytes per element for a given KV cache type
 func kvCacheBytesPerElement(cacheType string) float64 {
 	switch cacheType {
@@ -909,8 +673,6 @@ func kvCacheBytesPerElement(cacheType string) float64 {
 		return 1 // 1/2 of fp16
 	case "q4_0":
 		return 0.5 // 1/4 of fp16
-	case "f32":
-		return 4 // f32 (default for recurrent)
 	default:
 		return 2 // f16 (default)
 	}
--- a/fs/ggml/ggml_test.go
+++ b/fs/ggml/ggml_test.go
@@ -269,33 +269,3 @@ func TestKeyValue(t *testing.T) {
 		t.Errorf("unexpected uint8s (-got +want):\n%s", diff)
 	}
 }
-
-func TestHeadCount(t *testing.T) {
-	valuesArray := []int32{1, 5, 3, 4}
-	cases := []struct {
-		kv   KV
-		want uint64
-	}{
-		{
-			kv: KV{
-				"general.architecture":     "abc",
-				"abc.attention.head_count": &array[int32]{values: valuesArray, size: len(valuesArray)},
-			},
-			want: uint64(5),
-		},
-		{
-			kv: KV{
-				"general.architecture":     "abc",
-				"abc.attention.head_count": uint32(3),
-			},
-			want: uint64(3),
-		},
-	}
-
-	for _, tt := range cases {
-		got := tt.kv.HeadCountMax()
-		if got != tt.want {
-			t.Errorf("unexpected max value: got=%d want=%d", got, tt.want)
-		}
-	}
-}
--- a/fs/ggml/gguf.go
+++ b/fs/ggml/gguf.go
@@ -9,12 +9,8 @@ import (
 	"io"
 	"log/slog"
 	"maps"
-	"os"
-	"runtime"
 	"slices"
 	"strings"
-
-	"golang.org/x/sync/errgroup"
 )

 type containerGGUF struct {
@@ -229,7 +225,7 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
 		}

 		llm.tensors = append(llm.tensors, &tensor)
-		llm.parameters += tensor.Elements()
+		llm.parameters += tensor.parameters()
 	}

 	// patch KV with parameter count
@@ -492,86 +488,63 @@ func writeGGUFArray[S ~[]E, E any](w io.Writer, t uint32, s S) error {
 		return err
 	}

-	if t == ggufTypeString {
-		for _, e := range any(s).([]string) {
-			if err := binary.Write(w, binary.LittleEndian, uint64(len(e))); err != nil {
-				return err
-			}
-
-			if err := binary.Write(w, binary.LittleEndian, []byte(e)); err != nil {
-				return err
-			}
-		}
-		return nil
-	}
-
 	return binary.Write(w, binary.LittleEndian, s)
 }

-func WriteGGUF(f *os.File, kv KV, ts []*Tensor) error {
+func WriteGGUF(ws io.WriteSeeker, kv KV, ts []Tensor) error {
 	alignment := kv.Uint("general.alignment", 32)

-	if err := binary.Write(f, binary.LittleEndian, []byte("GGUF")); err != nil {
+	if err := binary.Write(ws, binary.LittleEndian, []byte("GGUF")); err != nil {
 		return err
 	}

-	if err := binary.Write(f, binary.LittleEndian, uint32(3)); err != nil {
+	if err := binary.Write(ws, binary.LittleEndian, uint32(3)); err != nil {
 		return err
 	}

-	if err := binary.Write(f, binary.LittleEndian, uint64(len(ts))); err != nil {
+	if err := binary.Write(ws, binary.LittleEndian, uint64(len(ts))); err != nil {
 		return err
 	}

-	if err := binary.Write(f, binary.LittleEndian, uint64(len(kv))); err != nil {
+	if err := binary.Write(ws, binary.LittleEndian, uint64(len(kv))); err != nil {
 		return err
 	}

-	for _, key := range slices.Sorted(maps.Keys(kv)) {
-		if err := ggufWriteKV(f, key, kv[key]); err != nil {
+	keys := slices.Collect(maps.Keys(kv))
+	slices.Sort(keys)
+
+	for _, key := range keys {
+		if err := ggufWriteKV(ws, key, kv[key]); err != nil {
 			return err
 		}
 	}

-	slices.SortStableFunc(
-		ts,
-		func(a, b *Tensor) int {
-			return cmp.Or(
-				cmp.Compare(a.block(), b.block()),
-				cmp.Compare(a.Name, b.Name),
-			)
-		},
-	)
+	slices.SortStableFunc(ts, func(a, b Tensor) int {
+		if i, j := a.block(), b.block(); i < 0 && j > 0 {
+			return 1
+		} else if i > 0 && j < 0 {
+			return -1
+		} else {
+			return cmp.Compare(i, j)
+		}
+	})

 	var s uint64
-	for i := range ts {
-		ts[i].Offset = s
-		if err := ggufWriteTensorInfo(f, ts[i]); err != nil {
+	for _, t := range ts {
+		t.Offset = s + uint64(ggufPadding(int64(s), int64(alignment)))
+		if err := ggufWriteTensorInfo(ws, t); err != nil {
 			return err
 		}
-		s += ts[i].Size()
-		s += uint64(ggufPadding(int64(s), int64(alignment)))
+		s += t.Size()
 	}

-	offset, err := f.Seek(0, io.SeekCurrent)
-	if err != nil {
-		return err
-	}
-	offset += ggufPadding(offset, int64(alignment))
-
-	var g errgroup.Group
-	g.SetLimit(runtime.GOMAXPROCS(0))
-	// TODO consider reducing if tensors size * gomaxprocs is larger than free memory
 	for _, t := range ts {
-		t := t
-		w := io.NewOffsetWriter(f, offset+int64(t.Offset))
-		g.Go(func() error {
-			_, err := t.WriteTo(w)
+		if err := ggufWriteTensor(ws, t, int64(alignment)); err != nil {
 			return err
-		})
+		}
 	}

-	return g.Wait()
+	return nil
 }

 func ggufWriteKV(ws io.WriteSeeker, k string, v any) error {
@@ -586,10 +559,8 @@ func ggufWriteKV(ws io.WriteSeeker, k string, v any) error {

 	var err error
 	switch v := v.(type) {
-	case uint32, FileType:
+	case uint32:
 		err = writeGGUF(ws, ggufTypeUint32, v)
-	case uint64:
-		err = writeGGUF(ws, ggufTypeUint64, v)
 	case float32:
 		err = writeGGUF(ws, ggufTypeFloat32, v)
 	case bool:
@@ -598,24 +569,32 @@ func ggufWriteKV(ws io.WriteSeeker, k string, v any) error {
 		err = writeGGUFString(ws, v)
 	case []int32:
 		err = writeGGUFArray(ws, ggufTypeInt32, v)
-	case *array[int32]:
-		err = writeGGUFArray(ws, ggufTypeInt32, v.values)
 	case []uint32:
 		err = writeGGUFArray(ws, ggufTypeUint32, v)
-	case *array[uint32]:
-		err = writeGGUFArray(ws, ggufTypeUint32, v.values)
 	case []float32:
 		err = writeGGUFArray(ws, ggufTypeFloat32, v)
-	case *array[float32]:
-		err = writeGGUFArray(ws, ggufTypeFloat32, v.values)
 	case []string:
-		err = writeGGUFArray(ws, ggufTypeString, v)
-	case *array[string]:
-		err = writeGGUFArray(ws, ggufTypeString, v.values)
-	case []bool:
-		err = writeGGUFArray(ws, ggufTypeBool, v)
-	case *array[bool]:
-		err = writeGGUFArray(ws, ggufTypeBool, v.values)
+		if err := binary.Write(ws, binary.LittleEndian, ggufTypeArray); err != nil {
+			return err
+		}
+
+		if err := binary.Write(ws, binary.LittleEndian, ggufTypeString); err != nil {
+			return err
+		}
+
+		if err := binary.Write(ws, binary.LittleEndian, uint64(len(v))); err != nil {
+			return err
+		}
+
+		for _, e := range v {
+			if err := binary.Write(ws, binary.LittleEndian, uint64(len(e))); err != nil {
+				return err
+			}
+
+			if err := binary.Write(ws, binary.LittleEndian, []byte(e)); err != nil {
+				return err
+			}
+		}
 	default:
 		return fmt.Errorf("improper type for '%s'", k)
 	}
@@ -623,7 +602,7 @@ func ggufWriteKV(ws io.WriteSeeker, k string, v any) error {
 	return err
 }

-func ggufWriteTensorInfo(ws io.WriteSeeker, t *Tensor) error {
+func ggufWriteTensorInfo(ws io.WriteSeeker, t Tensor) error {
 	slog.Debug(t.Name, "kind", t.Kind, "shape", t.Shape, "offset", t.Offset)
 	if err := binary.Write(ws, binary.LittleEndian, uint64(len(t.Name))); err != nil {
 		return err
@@ -650,6 +629,20 @@ func ggufWriteTensorInfo(ws io.WriteSeeker, t *Tensor) error {
 	return binary.Write(ws, binary.LittleEndian, t.Offset)
 }

+func ggufWriteTensor(ws io.WriteSeeker, t Tensor, alignment int64) error {
+	offset, err := ws.Seek(0, io.SeekCurrent)
+	if err != nil {
+		return err
+	}
+
+	if err := binary.Write(ws, binary.LittleEndian, bytes.Repeat([]byte{0}, int(ggufPadding(offset, alignment)))); err != nil {
+		return err
+	}
+
+	_, err = t.WriteTo(ws)
+	return err
+}
+
 func ggufPadding(offset, align int64) int64 {
 	return (align - offset%align) % align
 }
--- a/fs/ggml/gguf_test.go
+++ b/fs/ggml/gguf_test.go
@@ -1,83 +0,0 @@
-package ggml
-
-import (
-	"bytes"
-	"math/rand/v2"
-	"os"
-	"strings"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-)
-
-func TestWriteGGUF(t *testing.T) {
-	b := bytes.NewBuffer(make([]byte, 2*3))
-	for range 8 {
-		t.Run("shuffle", func(t *testing.T) {
-			t.Parallel()
-
-			ts := []*Tensor{
-				{Name: "token_embd.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.0.ffn_norm.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.0.attn_norm.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.1.ffn_up.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.2.ffn_norm.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.1.ffn_down.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "blk.0.attn_k.weight", Shape: []uint64{2, 3}, WriterTo: b},
-				{Name: "output_norm.weight", Shape: []uint64{3, 2}, WriterTo: b},
-				{Name: "output.weight", Shape: []uint64{3, 2}, WriterTo: b},
-			}
-
-			rand.Shuffle(len(ts), func(i, j int) {
-				ts[i], ts[j] = ts[j], ts[i]
-			})
-
-			w, err := os.CreateTemp(t.TempDir(), strings.ReplaceAll(t.Name(), "/", "_")+"*.bin")
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer w.Close()
-
-			if err := WriteGGUF(w, KV{
-				"general.alignment": uint32(16),
-			}, ts); err != nil {
-				t.Fatal(err)
-			}
-
-			r, err := os.Open(w.Name())
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer r.Close()
-
-			ff, err := Decode(r, 0)
-			if err != nil {
-				t.Fatal(err)
-			}
-
-			if diff := cmp.Diff(KV{
-				"general.alignment":       uint32(16),
-				"general.parameter_count": uint64(54),
-			}, ff.KV()); diff != "" {
-				t.Errorf("Mismatch (-want +got):\n%s", diff)
-			}
-
-			if diff := cmp.Diff(Tensors{
-				Offset: 592,
-				items: []*Tensor{
-					{Name: "blk.0.attn_k.weight", Offset: 0, Shape: []uint64{2, 3}},
-					{Name: "blk.0.attn_norm.weight", Offset: 32, Shape: []uint64{2, 3}},
-					{Name: "blk.0.ffn_norm.weight", Offset: 64, Shape: []uint64{2, 3}},
-					{Name: "blk.1.ffn_down.weight", Offset: 96, Shape: []uint64{2, 3}},
-					{Name: "blk.1.ffn_up.weight", Offset: 128, Shape: []uint64{2, 3}},
-					{Name: "blk.2.ffn_norm.weight", Offset: 160, Shape: []uint64{2, 3}},
-					{Name: "output.weight", Offset: 192, Shape: []uint64{3, 2}},
-					{Name: "output_norm.weight", Offset: 224, Shape: []uint64{3, 2}},
-					{Name: "token_embd.weight", Offset: 256, Shape: []uint64{2, 3}},
-				},
-			}, ff.Tensors(), cmp.AllowUnexported(Tensors{})); diff != "" {
-				t.Errorf("Mismatch (-want +got):\n%s", diff)
-			}
-		})
-	}
-}
--- a/fs/ggml/type.go
+++ b/fs/ggml/type.go
@@ -1,31 +1,26 @@
 package ggml

-import (
-	"fmt"
-	"log/slog"
-	"strings"
-)
+import "fmt"

-// FileType is the Go equivalent to llama_ftype used for gguf file typing
-type FileType uint32
+type fileType uint32

 const (
-	FileTypeF32 FileType = iota
-	FileTypeF16
+	fileTypeF32 fileType = iota
+	fileTypeF16
 	fileTypeQ4_0
 	fileTypeQ4_1
-	fileTypeMXFP4 // originally fileTypeQ4_1_F16 // unused by GGML
-	fileTypeQ4_2  // unused by GGML
-	fileTypeQ4_3  // unused by GGML
-	FileTypeQ8_0
+	fileTypeQ4_1_F16
+	fileTypeQ4_2 // unused
+	fileTypeQ4_3 // unused
+	fileTypeQ8_0
 	fileTypeQ5_0
 	fileTypeQ5_1
 	fileTypeQ2_K
 	fileTypeQ3_K_S
 	fileTypeQ3_K_M
 	fileTypeQ3_K_L
-	FileTypeQ4_K_S
-	FileTypeQ4_K_M
+	fileTypeQ4_K_S
+	fileTypeQ4_K_M
 	fileTypeQ5_K_S
 	fileTypeQ5_K_M
 	fileTypeQ6_K
@@ -42,64 +37,93 @@ const (
 	fileTypeIQ2_M
 	fileTypeIQ4_XS
 	fileTypeIQ1_M
-	FileTypeBF16
-	fileTypeQ4_0_4_4 // unused by GGML
-	fileTypeQ4_0_4_8 // unused by GGML
-	fileTypeQ4_0_8_8 // unused by GGML
-	fileTypeTQ1_0
-	fileTypeTQ2_0
+	fileTypeBF16

-	FileTypeUnknown = 1024
+	fileTypeUnknown
 )

-// ParseFileType parses the provided GGUF file type
-// Only Ollama supported types are considered valid
-func ParseFileType(s string) (FileType, error) {
+func ParseFileType(s string) (fileType, error) {
 	switch s {
 	case "F32":
-		return FileTypeF32, nil
+		return fileTypeF32, nil
 	case "F16":
-		return FileTypeF16, nil
+		return fileTypeF16, nil
+	case "Q4_0":
+		return fileTypeQ4_0, nil
+	case "Q4_1":
+		return fileTypeQ4_1, nil
+	case "Q4_1_F16":
+		return fileTypeQ4_1_F16, nil
 	case "Q8_0":
-		return FileTypeQ8_0, nil
+		return fileTypeQ8_0, nil
+	case "Q5_0":
+		return fileTypeQ5_0, nil
+	case "Q5_1":
+		return fileTypeQ5_1, nil
+	case "Q2_K":
+		return fileTypeQ2_K, nil
+	case "Q3_K_S":
+		return fileTypeQ3_K_S, nil
+	case "Q3_K_M":
+		return fileTypeQ3_K_M, nil
+	case "Q3_K_L":
+		return fileTypeQ3_K_L, nil
 	case "Q4_K_S":
-		return FileTypeQ4_K_S, nil
-	case "Q4_K_M", "Q4_K":
-		return FileTypeQ4_K_M, nil
+		return fileTypeQ4_K_S, nil
+	case "Q4_K_M":
+		return fileTypeQ4_K_M, nil
+	case "Q5_K_S":
+		return fileTypeQ5_K_S, nil
+	case "Q5_K_M":
+		return fileTypeQ5_K_M, nil
+	case "Q6_K":
+		return fileTypeQ6_K, nil
+	case "IQ2_XXS":
+		return fileTypeIQ2_XXS, nil
+	case "IQ2_XS":
+		return fileTypeIQ2_XS, nil
+	case "Q2_K_S":
+		return fileTypeQ2_K_S, nil
+	case "IQ3_XS":
+		return fileTypeIQ3_XS, nil
+	case "IQ3_XXS":
+		return fileTypeIQ3_XXS, nil
+	case "IQ1_S":
+		return fileTypeIQ1_S, nil
+	case "IQ4_NL":
+		return fileTypeIQ4_NL, nil
+	case "IQ3_S":
+		return fileTypeIQ3_S, nil
+	case "IQ3_M":
+		return fileTypeIQ3_M, nil
+	case "IQ2_S":
+		return fileTypeIQ2_S, nil
+	case "IQ2_M":
+		return fileTypeIQ2_M, nil
+	case "IQ4_XS":
+		return fileTypeIQ4_XS, nil
+	case "IQ1_M":
+		return fileTypeIQ1_M, nil
 	case "BF16":
-		return FileTypeBF16, nil
+		return fileTypeBF16, nil
 	default:
-		supportedFileTypes := []FileType{
-			FileTypeF32,
-			FileTypeF16,
-			FileTypeQ4_K_S,
-			FileTypeQ4_K_M,
-			FileTypeQ8_0,
-			// fsggml.FileTypeBF16, // TODO
-		}
-		strs := make([]string, len(supportedFileTypes))
-		for i := range supportedFileTypes {
-			strs[i] = supportedFileTypes[i].String()
-		}
-
-		return FileTypeUnknown, fmt.Errorf("unsupported quantization type %s - supported types are %s", s, strings.Join(strs, ", "))
+		return fileTypeUnknown, fmt.Errorf("unknown fileType: %s", s)
 	}
 }

-func (t FileType) String() string {
-	// Note: this routine will return a broader set of file types for existing models
+func (t fileType) String() string {
 	switch t {
-	case FileTypeF32:
+	case fileTypeF32:
 		return "F32"
-	case FileTypeF16:
+	case fileTypeF16:
 		return "F16"
 	case fileTypeQ4_0:
 		return "Q4_0"
 	case fileTypeQ4_1:
 		return "Q4_1"
-	case fileTypeMXFP4:
-		return "MXFP4"
-	case FileTypeQ8_0:
+	case fileTypeQ4_1_F16:
+		return "Q4_1_F16"
+	case fileTypeQ8_0:
 		return "Q8_0"
 	case fileTypeQ5_0:
 		return "Q5_0"
@@ -113,9 +137,9 @@ func (t FileType) String() string {
 		return "Q3_K_M"
 	case fileTypeQ3_K_L:
 		return "Q3_K_L"
-	case FileTypeQ4_K_S:
+	case fileTypeQ4_K_S:
 		return "Q4_K_S"
-	case FileTypeQ4_K_M:
+	case fileTypeQ4_K_M:
 		return "Q4_K_M"
 	case fileTypeQ5_K_S:
 		return "Q5_K_S"
@@ -123,205 +147,39 @@ func (t FileType) String() string {
 		return "Q5_K_M"
 	case fileTypeQ6_K:
 		return "Q6_K"
+	case fileTypeIQ2_XXS:
+		return "IQ2_XXS"
+	case fileTypeIQ2_XS:
+		return "IQ2_XS"
 	case fileTypeQ2_K_S:
 		return "Q2_K_S"
-	case FileTypeBF16:
+	case fileTypeIQ3_XS:
+		return "IQ3_XS"
+	case fileTypeIQ3_XXS:
+		return "IQ3_XXS"
+	case fileTypeIQ1_S:
+		return "IQ1_S"
+	case fileTypeIQ4_NL:
+		return "IQ4_NL"
+	case fileTypeIQ3_S:
+		return "IQ3_S"
+	case fileTypeIQ3_M:
+		return "IQ3_M"
+	case fileTypeIQ2_S:
+		return "IQ2_S"
+	case fileTypeIQ4_XS:
+		return "IQ4_XS"
+	case fileTypeIQ2_M:
+		return "IQ2_M"
+	case fileTypeIQ1_M:
+		return "IQ1_M"
+	case fileTypeBF16:
 		return "BF16"
 	default:
 		return "unknown"
 	}
 }

-func (t FileType) Value() uint32 {
+func (t fileType) Value() uint32 {
 	return uint32(t)
 }
-
-func (ftype FileType) ToTensorType() TensorType {
-	switch ftype {
-	case FileTypeF32:
-		return TensorTypeF32
-	case FileTypeF16:
-		return TensorTypeF16
-	case fileTypeQ4_0:
-		return TensorTypeQ4_0
-	case fileTypeQ4_1:
-		return TensorTypeQ4_1
-	case FileTypeQ8_0:
-		return TensorTypeQ8_0
-	case fileTypeQ5_0:
-		return TensorTypeQ5_0
-	case fileTypeQ5_1:
-		return TensorTypeQ5_1
-	case fileTypeQ2_K:
-		return TensorTypeQ2_K
-	case fileTypeQ3_K_S:
-		return TensorTypeQ3_K
-	case fileTypeQ3_K_M:
-		return TensorTypeQ3_K
-	case fileTypeQ3_K_L:
-		return TensorTypeQ3_K
-	case FileTypeQ4_K_S:
-		return TensorTypeQ4_K
-	case FileTypeQ4_K_M:
-		return TensorTypeQ4_K
-	case fileTypeQ5_K_S:
-		return TensorTypeQ5_K
-	case fileTypeQ5_K_M:
-		return TensorTypeQ5_K
-	case fileTypeQ6_K:
-		return TensorTypeQ6_K
-	case fileTypeQ2_K_S:
-		return TensorTypeQ2_K
-	case FileTypeBF16:
-		return TensorTypeBF16
-	case fileTypeMXFP4:
-		return TensorTypeMXFP4
-	default:
-		slog.Warn("unsupported file type", "type", ftype)
-		return 0 // F32
-	}
-}
-
-// TensorType is equivalent to ggml_type for individual tensor types
-// Note: these are not the same as FileType
-type TensorType uint32
-
-const (
-	TensorTypeF32 TensorType = iota
-	TensorTypeF16
-	TensorTypeQ4_0
-	TensorTypeQ4_1
-	tensorTypeQ4_2
-	tensorTypeQ4_3 // unused by GGML
-	TensorTypeQ5_0
-	TensorTypeQ5_1
-	TensorTypeQ8_0
-	TensorTypeQ8_1
-	TensorTypeQ2_K
-	TensorTypeQ3_K
-	TensorTypeQ4_K
-	TensorTypeQ5_K
-	TensorTypeQ6_K
-	TensorTypeQ8_K
-	tensorTypeIQ2_XXS // not supported by ollama
-	tensorTypeIQ2_XS  // not supported by ollama
-	tensorTypeIQ3_XXS // not supported by ollama
-	tensorTypeIQ1_S   // not supported by ollama
-	tensorTypeIQ4_NL  // not supported by ollama
-	tensorTypeIQ3_S   // not supported by ollama
-	tensorTypeIQ2_S   // not supported by ollama
-	tensorTypeIQ4_XS  // not supported by ollama
-	TensorTypeI8
-	TensorTypeI16
-	TensorTypeI32
-	TensorTypeI64
-	TensorTypeF64
-	tensorTypeIQ1_M // not supported by ollama
-	TensorTypeBF16
-	tensorTypeQ4_0_4_4   // unused by GGML
-	tensorTypeQ4_0_4_8   // unused by GGML
-	tensorTypeQ4_0_8_8   // unused by GGML
-	tensorTypeTQ1_0      // not supported by ollama
-	tensorTypeTQ2_0      // not supported by ollama
-	tensorTypeIQ4_NL_4_4 // unused by GGML
-	tensorTypeIQ4_NL_4_8 // unused by GGML
-	tensorTypeIQ4_NL_8_8 // unused by GGML
-	TensorTypeMXFP4
-)
-
-// ParseFileType parses the provided GGUF file type
-// Only Ollama supported types are considered valid
-func ParseTensorType(s string) (TensorType, error) {
-	switch s {
-	case "F32":
-		return TensorTypeF32, nil
-	case "F16":
-		return TensorTypeF16, nil
-	case "Q4_0":
-		return TensorTypeQ4_0, nil
-	case "Q4_1":
-		return TensorTypeQ4_1, nil
-	case "Q5_0":
-		return TensorTypeQ5_0, nil
-	case "Q5_1":
-		return TensorTypeQ5_1, nil
-	case "Q8_0":
-		return TensorTypeQ8_0, nil
-	case "Q8_1":
-		return TensorTypeQ8_1, nil
-	case "Q2_K":
-		return TensorTypeQ2_K, nil
-	case "Q3_K":
-		return TensorTypeQ3_K, nil
-	case "Q4_K":
-		return TensorTypeQ4_K, nil
-	case "Q5_K":
-		return TensorTypeQ5_K, nil
-	case "Q6_K":
-		return TensorTypeQ6_K, nil
-	case "Q8_K":
-		return TensorTypeQ8_K, nil
-	case "F64":
-		return TensorTypeF64, nil
-	case "BF16":
-		return TensorTypeBF16, nil
-	case "MXFP4":
-		return TensorTypeMXFP4, nil
-	default:
-		return 0, fmt.Errorf("unsupported quantization type %s", s)
-	}
-}
-
-func (t TensorType) IsQuantized() bool {
-	switch t {
-	case TensorTypeF32, TensorTypeF16, TensorTypeBF16:
-		return false
-	default:
-		return true
-	}
-}
-
-func (t TensorType) RowSize(ne uint64) uint64 {
-	return t.TypeSize() * ne / t.BlockSize()
-}
-
-func (t TensorType) String() string {
-	switch t {
-	case TensorTypeF32:
-		return "F32"
-	case TensorTypeF16:
-		return "F16"
-	case TensorTypeQ4_0:
-		return "Q4_0"
-	case TensorTypeQ4_1:
-		return "Q4_1"
-	case TensorTypeQ5_0:
-		return "Q5_0"
-	case TensorTypeQ5_1:
-		return "Q5_1"
-	case TensorTypeQ8_0:
-		return "Q8_0"
-	case TensorTypeQ8_1:
-		return "Q8_1"
-	case TensorTypeQ2_K:
-		return "Q2_K"
-	case TensorTypeQ3_K:
-		return "Q3_K"
-	case TensorTypeQ4_K:
-		return "Q4_K"
-	case TensorTypeQ5_K:
-		return "Q5_K"
-	case TensorTypeQ6_K:
-		return "Q6_K"
-	case TensorTypeQ8_K:
-		return "Q8_K"
-	case TensorTypeF64:
-		return "F64"
-	case TensorTypeBF16:
-		return "BF16"
-	case 4, TensorTypeMXFP4:
-		return "MXFP4"
-	default:
-		return "unknown"
-	}
-}
--- a/fs/gguf/gguf.go
+++ b/fs/gguf/gguf.go
@@ -1,347 +0,0 @@
-package gguf
-
-import (
-	"bytes"
-	"cmp"
-	"encoding/binary"
-	"errors"
-	"fmt"
-	"io"
-	"iter"
-	"os"
-	"slices"
-	"strings"
-)
-
-const (
-	typeUint8 uint32 = iota
-	typeInt8
-	typeUint16
-	typeInt16
-	typeUint32
-	typeInt32
-	typeFloat32
-	typeBool
-	typeString
-	typeArray
-	typeUint64
-	typeInt64
-	typeFloat64
-)
-
-var ErrUnsupported = errors.New("unsupported")
-
-type File struct {
-	Magic   [4]byte
-	Version uint32
-
-	keyValues *lazy[KeyValue]
-	tensors   *lazy[TensorInfo]
-	offset    int64
-
-	file   *os.File
-	reader *bufferedReader
-	bts    []byte
-}
-
-func Open(path string) (f *File, err error) {
-	f = &File{bts: make([]byte, 4096)}
-	f.file, err = os.Open(path)
-	if err != nil {
-		return nil, err
-	}
-
-	f.reader = newBufferedReader(f.file, 32<<10)
-
-	if err := binary.Read(f.reader, binary.LittleEndian, &f.Magic); err != nil {
-		return nil, err
-	}
-
-	if bytes.Equal(f.Magic[:], []byte("gguf")) {
-		return nil, fmt.Errorf("%w file type %v", ErrUnsupported, f.Magic)
-	}
-
-	if err := binary.Read(f.reader, binary.LittleEndian, &f.Version); err != nil {
-		return nil, err
-	}
-
-	if f.Version < 2 {
-		return nil, fmt.Errorf("%w version %v", ErrUnsupported, f.Version)
-	}
-
-	f.tensors, err = newLazy(f, f.readTensor)
-	if err != nil {
-		return nil, err
-	}
-
-	f.tensors.successFunc = func() error {
-		offset := f.reader.offset
-
-		alignment := cmp.Or(f.KeyValue("general.alignment").Int(), 32)
-		f.offset = offset + (alignment-offset%alignment)%alignment
-		return nil
-	}
-
-	f.keyValues, err = newLazy(f, f.readKeyValue)
-	if err != nil {
-		return nil, err
-	}
-
-	return f, nil
-}
-
-func (f *File) readTensor() (TensorInfo, error) {
-	name, err := readString(f)
-	if err != nil {
-		return TensorInfo{}, err
-	}
-
-	dims, err := read[uint32](f)
-	if err != nil {
-		return TensorInfo{}, err
-	}
-
-	shape := make([]uint64, dims)
-	for i := range dims {
-		shape[i], err = read[uint64](f)
-		if err != nil {
-			return TensorInfo{}, err
-		}
-	}
-
-	type_, err := read[uint32](f)
-	if err != nil {
-		return TensorInfo{}, err
-	}
-
-	offset, err := read[uint64](f)
-	if err != nil {
-		return TensorInfo{}, err
-	}
-
-	return TensorInfo{
-		Name:   name,
-		Offset: offset,
-		Shape:  shape,
-		Type:   TensorType(type_),
-	}, nil
-}
-
-func (f *File) readKeyValue() (KeyValue, error) {
-	key, err := readString(f)
-	if err != nil {
-		return KeyValue{}, err
-	}
-
-	t, err := read[uint32](f)
-	if err != nil {
-		return KeyValue{}, err
-	}
-
-	value, err := func() (any, error) {
-		switch t {
-		case typeUint8:
-			return read[uint8](f)
-		case typeInt8:
-			return read[int8](f)
-		case typeUint16:
-			return read[uint16](f)
-		case typeInt16:
-			return read[int16](f)
-		case typeUint32:
-			return read[uint32](f)
-		case typeInt32:
-			return read[int32](f)
-		case typeUint64:
-			return read[uint64](f)
-		case typeInt64:
-			return read[int64](f)
-		case typeFloat32:
-			return read[float32](f)
-		case typeFloat64:
-			return read[float64](f)
-		case typeBool:
-			return read[bool](f)
-		case typeString:
-			return readString(f)
-		case typeArray:
-			return readArray(f)
-		default:
-			return nil, fmt.Errorf("%w type %d", ErrUnsupported, t)
-		}
-	}()
-	if err != nil {
-		return KeyValue{}, err
-	}
-
-	return KeyValue{
-		Key:   key,
-		Value: Value{value},
-	}, nil
-}
-
-func read[T any](f *File) (t T, err error) {
-	err = binary.Read(f.reader, binary.LittleEndian, &t)
-	return t, err
-}
-
-func readString(f *File) (string, error) {
-	n, err := read[uint64](f)
-	if err != nil {
-		return "", err
-	}
-
-	if int(n) > len(f.bts) {
-		f.bts = make([]byte, n)
-	}
-
-	bts := f.bts[:n]
-	if _, err := io.ReadFull(f.reader, bts); err != nil {
-		return "", err
-	}
-	defer clear(bts)
-
-	return string(bts), nil
-}
-
-func readArray(f *File) (any, error) {
-	t, err := read[uint32](f)
-	if err != nil {
-		return nil, err
-	}
-
-	n, err := read[uint64](f)
-	if err != nil {
-		return nil, err
-	}
-
-	switch t {
-	case typeUint8:
-		return readArrayData[uint8](f, n)
-	case typeInt8:
-		return readArrayData[int8](f, n)
-	case typeUint16:
-		return readArrayData[uint16](f, n)
-	case typeInt16:
-		return readArrayData[int16](f, n)
-	case typeUint32:
-		return readArrayData[uint32](f, n)
-	case typeInt32:
-		return readArrayData[int32](f, n)
-	case typeUint64:
-		return readArrayData[uint64](f, n)
-	case typeInt64:
-		return readArrayData[int64](f, n)
-	case typeFloat32:
-		return readArrayData[float32](f, n)
-	case typeFloat64:
-		return readArrayData[float64](f, n)
-	case typeBool:
-		return readArrayData[bool](f, n)
-	case typeString:
-		return readArrayString(f, n)
-	default:
-		return nil, fmt.Errorf("%w type %d", ErrUnsupported, t)
-	}
-}
-
-func readArrayData[T any](f *File, n uint64) (s []T, err error) {
-	s = make([]T, n)
-	for i := range n {
-		e, err := read[T](f)
-		if err != nil {
-			return nil, err
-		}
-
-		s[i] = e
-	}
-
-	return s, nil
-}
-
-func readArrayString(f *File, n uint64) (s []string, err error) {
-	s = make([]string, n)
-	for i := range n {
-		e, err := readString(f)
-		if err != nil {
-			return nil, err
-		}
-
-		s[i] = e
-	}
-
-	return s, nil
-}
-
-func (f *File) Close() error {
-	f.keyValues.stop()
-	f.tensors.stop()
-	return f.file.Close()
-}
-
-func (f *File) KeyValue(key string) KeyValue {
-	if !strings.HasPrefix(key, "general.") && !strings.HasPrefix(key, "tokenizer.") {
-		key = f.KeyValue("general.architecture").String() + "." + key
-	}
-
-	if index := slices.IndexFunc(f.keyValues.values, func(kv KeyValue) bool {
-		return kv.Key == key
-	}); index >= 0 {
-		return f.keyValues.values[index]
-	}
-
-	for keyValue, ok := f.keyValues.next(); ok; keyValue, ok = f.keyValues.next() {
-		if keyValue.Key == key {
-			return keyValue
-		}
-	}
-
-	return KeyValue{}
-}
-
-func (f *File) NumKeyValues() int {
-	return int(f.keyValues.count)
-}
-
-func (f *File) KeyValues() iter.Seq2[int, KeyValue] {
-	return f.keyValues.All()
-}
-
-func (f *File) TensorInfo(name string) TensorInfo {
-	if index := slices.IndexFunc(f.tensors.values, func(t TensorInfo) bool {
-		return t.Name == name
-	}); index >= 0 {
-		return f.tensors.values[index]
-	}
-
-	// fast-forward through key values if we haven't already
-	_ = f.keyValues.rest()
-	for tensor, ok := f.tensors.next(); ok; tensor, ok = f.tensors.next() {
-		if tensor.Name == name {
-			return tensor
-		}
-	}
-
-	return TensorInfo{}
-}
-
-func (f *File) NumTensors() int {
-	return int(f.tensors.count)
-}
-
-func (f *File) TensorInfos() iter.Seq2[int, TensorInfo] {
-	// fast forward through key values if we haven't already
-	f.keyValues.rest()
-	return f.tensors.All()
-}
-
-func (f *File) TensorReader(name string) (TensorInfo, io.Reader, error) {
-	t := f.TensorInfo(name)
-	if t.NumBytes() == 0 {
-		return TensorInfo{}, nil, fmt.Errorf("tensor %s not found", name)
-	}
-
-	// fast forward through tensor info if we haven't already
-	_ = f.tensors.rest()
-	return t, io.NewSectionReader(f.file, f.offset+int64(t.Offset), t.NumBytes()), nil
-}
--- a/fs/gguf/gguf_test.go
+++ b/fs/gguf/gguf_test.go
@@ -1,249 +0,0 @@
-package gguf_test
-
-import (
-	"bytes"
-	"os"
-	"strconv"
-	"strings"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-	"github.com/google/go-cmp/cmp/cmpopts"
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/ollama/ollama/fs/gguf"
-)
-
-func createBinFile(tb testing.TB) string {
-	tb.Helper()
-	f, err := os.CreateTemp(tb.TempDir(), "")
-	if err != nil {
-		tb.Fatal(err)
-	}
-	defer f.Close()
-
-	kv := ggml.KV{
-		"general.architecture":                   "llama",
-		"llama.block_count":                      uint32(8),
-		"llama.embedding_length":                 uint32(3),
-		"llama.attention.head_count":             uint32(2),
-		"llama.attention.head_count_kv":          uint32(2),
-		"llama.attention.key_length":             uint32(3),
-		"llama.rope.dimension_count":             uint32(4),
-		"llama.rope.freq_base":                   float32(10000.0),
-		"llama.rope.freq_scale":                  float32(1.0),
-		"llama.attention.layer_norm_rms_epsilon": float32(1e-6),
-		"tokenizer.ggml.eos_token_id":            uint32(0),
-		"tokenizer.ggml.eos_token_ids":           []int32{1, 2, 3},
-		"tokenizer.ggml.tokens":                  []string{"hello", "world"},
-		"tokenizer.ggml.scores":                  []float32{0, 1},
-	}
-
-	tensors := []*ggml.Tensor{
-		{
-			Name:     "token_embd.weight",
-			Kind:     0,
-			Shape:    []uint64{2, 3},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*2*3)),
-		},
-		{
-			Name:     "output.weight",
-			Kind:     0,
-			Shape:    []uint64{3, 2},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*3*2)),
-		},
-	}
-
-	for i := range 8 {
-		tensors = append(tensors, &ggml.Tensor{
-			Name:     "blk." + strconv.Itoa(i) + ".attn_q.weight",
-			Kind:     0,
-			Shape:    []uint64{3, 3},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*3*3)),
-		}, &ggml.Tensor{
-			Name:     "blk." + strconv.Itoa(i) + ".attn_k.weight",
-			Kind:     0,
-			Shape:    []uint64{3, 3},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*3*3)),
-		}, &ggml.Tensor{
-			Name:     "blk." + strconv.Itoa(i) + ".attn_v.weight",
-			Kind:     0,
-			Shape:    []uint64{3, 3},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*3*3)),
-		}, &ggml.Tensor{
-			Name:     "blk." + strconv.Itoa(i) + ".attn_output.weight",
-			Kind:     0,
-			Shape:    []uint64{3, 3},
-			WriterTo: bytes.NewBuffer(make([]byte, 4*3*3)),
-		})
-	}
-
-	if err := ggml.WriteGGUF(f, kv, tensors); err != nil {
-		tb.Fatal(err)
-	}
-
-	return f.Name()
-}
-
-func TestRead(t *testing.T) {
-	f, err := gguf.Open(createBinFile(t))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
-
-	if got := f.KeyValue("does.not.exist").Valid(); got {
-		t.Errorf(`KeyValue("does.not.exist").Exists() = %v, want false`, got)
-	}
-
-	if got := f.KeyValue("general.architecture").String(); got != "llama" {
-		t.Errorf(`KeyValue("general.architecture").String() = %q, want %q`, got, "llama")
-	}
-
-	if got := f.TensorInfo("token_embd.weight"); got.Name != "token_embd.weight" {
-		t.Errorf(`TensorInfo("token_embd.weight").Name = %q, want %q`, got.Name, "token_embd.weight")
-	} else if diff := cmp.Diff(got.Shape, []uint64{2, 3}); diff != "" {
-		t.Errorf(`TensorInfo("token_embd.weight").Shape mismatch (-got +want):\n%s`, diff)
-	} else if got.Type != gguf.TensorTypeF32 {
-		t.Errorf(`TensorInfo("token_embd.weight").Type = %d, want %d`, got.Type, gguf.TensorTypeF32)
-	}
-
-	if got := f.KeyValue("block_count").Uint(); got != 8 {
-		t.Errorf(`KeyValue("block_count").Uint() = %d, want %d`, got, 8)
-	}
-
-	if diff := cmp.Diff(f.KeyValue("tokenizer.ggml.tokens").Strings(), []string{"hello", "world"}); diff != "" {
-		t.Errorf("KeyValue(\"tokenizer.ggml.tokens\").Strings() mismatch (-got +want):\n%s", diff)
-	}
-
-	if diff := cmp.Diff(f.KeyValue("tokenizer.ggml.scores").Floats(), []float64{0, 1}); diff != "" {
-		t.Errorf("KeyValue(\"tokenizer.ggml.scores\").Ints() mismatch (-got +want):\n%s", diff)
-	}
-
-	var kvs []string
-	for _, kv := range f.KeyValues() {
-		if !kv.Valid() {
-			t.Error("found invalid key-value pair:", kv)
-		}
-
-		kvs = append(kvs, kv.Key)
-	}
-
-	if len(kvs) != f.NumKeyValues() {
-		t.Errorf("iterated key count = %d, want %d", len(kvs), f.NumKeyValues())
-	}
-
-	if diff := cmp.Diff(kvs, []string{
-		"general.architecture",
-		"llama.block_count",
-		"llama.embedding_length",
-		"llama.attention.head_count",
-		"llama.attention.head_count_kv",
-		"llama.attention.key_length",
-		"llama.rope.dimension_count",
-		"llama.rope.freq_base",
-		"llama.rope.freq_scale",
-		"llama.attention.layer_norm_rms_epsilon",
-		"tokenizer.ggml.eos_token_id",
-		"tokenizer.ggml.eos_token_ids",
-		"tokenizer.ggml.tokens",
-		"tokenizer.ggml.scores",
-	}, cmpopts.SortSlices(strings.Compare)); diff != "" {
-		t.Errorf("KeyValues() mismatch (-got +want):\n%s", diff)
-	}
-
-	var tis []string
-	for _, ti := range f.TensorInfos() {
-		if !ti.Valid() {
-			t.Error("found invalid tensor info:", ti)
-		}
-
-		tis = append(tis, ti.Name)
-	}
-
-	if len(tis) != f.NumTensors() {
-		t.Errorf("iterated tensor count = %d, want %d", len(tis), f.NumTensors())
-	}
-
-	if diff := cmp.Diff(tis, []string{
-		"token_embd.weight",
-		"output.weight",
-		"blk.0.attn_q.weight",
-		"blk.0.attn_k.weight",
-		"blk.0.attn_v.weight",
-		"blk.0.attn_output.weight",
-		"blk.1.attn_q.weight",
-		"blk.1.attn_k.weight",
-		"blk.1.attn_v.weight",
-		"blk.1.attn_output.weight",
-		"blk.2.attn_q.weight",
-		"blk.2.attn_k.weight",
-		"blk.2.attn_v.weight",
-		"blk.2.attn_output.weight",
-		"blk.3.attn_q.weight",
-		"blk.3.attn_k.weight",
-		"blk.3.attn_v.weight",
-		"blk.3.attn_output.weight",
-		"blk.4.attn_q.weight",
-		"blk.4.attn_k.weight",
-		"blk.4.attn_v.weight",
-		"blk.4.attn_output.weight",
-		"blk.5.attn_q.weight",
-		"blk.5.attn_k.weight",
-		"blk.5.attn_v.weight",
-		"blk.5.attn_output.weight",
-		"blk.6.attn_q.weight",
-		"blk.6.attn_k.weight",
-		"blk.6.attn_v.weight",
-		"blk.6.attn_output.weight",
-		"blk.7.attn_q.weight",
-		"blk.7.attn_k.weight",
-		"blk.7.attn_v.weight",
-		"blk.7.attn_output.weight",
-	}, cmpopts.SortSlices(strings.Compare)); diff != "" {
-		t.Errorf("TensorInfos() mismatch (-got +want):\n%s", diff)
-	}
-
-	ti, r, err := f.TensorReader("output.weight")
-	if err != nil {
-		t.Fatalf(`TensorReader("output.weight") error: %v`, err)
-	}
-
-	if ti.Name != "output.weight" {
-		t.Errorf(`TensorReader("output.weight").Name = %q, want %q`, ti.Name, "output.weight")
-	} else if diff := cmp.Diff(ti.Shape, []uint64{3, 2}); diff != "" {
-		t.Errorf(`TensorReader("output.weight").Shape mismatch (-got +want):\n%s`, diff)
-	} else if ti.Type != gguf.TensorTypeF32 {
-		t.Errorf(`TensorReader("output.weight").Type = %d, want %d`, ti.Type, gguf.TensorTypeF32)
-	}
-
-	var b bytes.Buffer
-	if _, err := b.ReadFrom(r); err != nil {
-		t.Fatalf(`ReadFrom TensorReader("output.weight") error: %v`, err)
-	}
-
-	if b.Len() != int(ti.NumBytes()) {
-		t.Errorf(`ReadFrom TensorReader("output.weight") length = %d, want %d`, b.Len(), ti.NumBytes())
-	}
-}
-
-func BenchmarkRead(b *testing.B) {
-	b.ReportAllocs()
-
-	p := createBinFile(b)
-	for b.Loop() {
-		f, err := gguf.Open(p)
-		if err != nil {
-			b.Fatal(err)
-		}
-
-		if got := f.KeyValue("general.architecture").String(); got != "llama" {
-			b.Errorf("got = %q, want %q", got, "llama")
-		}
-
-		// Iterate through some tensors
-		for range f.TensorInfos() {
-		}
-
-		f.Close()
-	}
-}
--- a/fs/gguf/keyvalue.go
+++ b/fs/gguf/keyvalue.go
@@ -1,90 +0,0 @@
-package gguf
-
-import (
-	"reflect"
-	"slices"
-)
-
-type KeyValue struct {
-	Key string
-	Value
-}
-
-func (kv KeyValue) Valid() bool {
-	return kv.Key != "" && kv.Value.value != nil
-}
-
-type Value struct {
-	value any
-}
-
-func value[T any](v Value, kinds ...reflect.Kind) (t T) {
-	vv := reflect.ValueOf(v.value)
-	if slices.Contains(kinds, vv.Kind()) {
-		t = vv.Convert(reflect.TypeOf(t)).Interface().(T)
-	}
-	return
-}
-
-func values[T any](v Value, kinds ...reflect.Kind) (ts []T) {
-	switch vv := reflect.ValueOf(v.value); vv.Kind() {
-	case reflect.Slice:
-		if slices.Contains(kinds, vv.Type().Elem().Kind()) {
-			ts = make([]T, vv.Len())
-			for i := range vv.Len() {
-				ts[i] = vv.Index(i).Convert(reflect.TypeOf(ts[i])).Interface().(T)
-			}
-		}
-	}
-	return
-}
-
-// Int returns Value as a signed integer. If it is not a signed integer, it returns 0.
-func (v Value) Int() int64 {
-	return value[int64](v, reflect.Int, reflect.Int8, reflect.Int16, reflect.Int32, reflect.Int64)
-}
-
-// Ints returns Value as a signed integer slice. If it is not a signed integer slice, it returns nil.
-func (v Value) Ints() (i64s []int64) {
-	return values[int64](v, reflect.Int, reflect.Int8, reflect.Int16, reflect.Int32, reflect.Int64)
-}
-
-// Uint converts an unsigned integer value to uint64. If the value is not a unsigned integer, it returns 0.
-func (v Value) Uint() uint64 {
-	return value[uint64](v, reflect.Uint, reflect.Uint8, reflect.Uint16, reflect.Uint32, reflect.Uint64)
-}
-
-// Uints returns Value as a unsigned integer slice. If it is not a unsigned integer slice, it returns nil.
-func (v Value) Uints() (u64s []uint64) {
-	return values[uint64](v, reflect.Uint, reflect.Uint8, reflect.Uint16, reflect.Uint32, reflect.Uint64)
-}
-
-// Float returns Value as a float. If it is not a float, it returns 0.
-func (v Value) Float() float64 {
-	return value[float64](v, reflect.Float32, reflect.Float64)
-}
-
-// Floats returns Value as a float slice. If it is not a float slice, it returns nil.
-func (v Value) Floats() (f64s []float64) {
-	return values[float64](v, reflect.Float32, reflect.Float64)
-}
-
-// Bool returns Value as a boolean. If it is not a boolean, it returns false.
-func (v Value) Bool() bool {
-	return value[bool](v, reflect.Bool)
-}
-
-// Bools returns Value as a boolean slice. If it is not a boolean slice, it returns nil.
-func (v Value) Bools() (bools []bool) {
-	return values[bool](v, reflect.Bool)
-}
-
-// String returns Value as a string. If it is not a string, it returns an empty string.
-func (v Value) String() string {
-	return value[string](v, reflect.String)
-}
-
-// Strings returns Value as a string slice. If it is not a string slice, it returns nil.
-func (v Value) Strings() (strings []string) {
-	return values[string](v, reflect.String)
-}
--- a/fs/gguf/keyvalue_test.go
+++ b/fs/gguf/keyvalue_test.go
@@ -1,208 +0,0 @@
-package gguf
-
-import (
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-)
-
-func split(name string, values map[string][]any) (matched []any, unmatched []any) {
-	for key, value := range values {
-		if key == name {
-			matched = value
-		} else {
-			unmatched = append(unmatched, value...)
-		}
-	}
-	return
-}
-
-func TestValue(t *testing.T) {
-	values := map[string][]any{
-		"int64":   {int(42), int8(42), int16(42), int32(42), int64(42)},
-		"uint64":  {uint(42), uint8(42), uint16(42), uint32(42), uint64(42)},
-		"float64": {float32(42), float64(42)},
-		"string":  {"42", "hello"},
-		"bool":    {true, false},
-	}
-
-	t.Run("int64", func(t *testing.T) {
-		matched, unmatched := split("int64", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if i64 := kv.Int(); i64 != 42 {
-				t.Errorf("expected 42, got %d", i64)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if i64 := kv.Int(); i64 != 0 {
-				t.Errorf("expected 42, got %d", i64)
-			}
-		}
-	})
-
-	t.Run("uint64", func(t *testing.T) {
-		matched, unmatched := split("uint64", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if u64 := kv.Uint(); u64 != 42 {
-				t.Errorf("expected 42, got %d", u64)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if u64 := kv.Uint(); u64 != 0 {
-				t.Errorf("expected 42, got %d", u64)
-			}
-		}
-	})
-
-	t.Run("float64", func(t *testing.T) {
-		matched, unmatched := split("float64", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if f64 := kv.Float(); f64 != 42 {
-				t.Errorf("expected 42, got %f", f64)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if f64 := kv.Float(); f64 != 0 {
-				t.Errorf("expected 42, got %f", f64)
-			}
-		}
-	})
-
-	t.Run("string", func(t *testing.T) {
-		matched, unmatched := split("string", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if s := kv.String(); s != v {
-				t.Errorf("expected 42, got %s", s)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if s := kv.String(); s != "" {
-				t.Errorf("expected 42, got %s", s)
-			}
-		}
-	})
-
-	t.Run("bool", func(t *testing.T) {
-		matched, unmatched := split("bool", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if b := kv.Bool(); b != v {
-				t.Errorf("expected true, got %v", b)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if b := kv.Bool(); b != false {
-				t.Errorf("expected false, got %v", b)
-			}
-		}
-	})
-}
-
-func TestValues(t *testing.T) {
-	values := map[string][]any{
-		"int64s":   {[]int{42}, []int8{42}, []int16{42}, []int32{42}, []int64{42}},
-		"uint64s":  {[]uint{42}, []uint8{42}, []uint16{42}, []uint32{42}, []uint64{42}},
-		"float64s": {[]float32{42}, []float64{42}},
-		"strings":  {[]string{"42"}, []string{"hello"}},
-		"bools":    {[]bool{true}, []bool{false}},
-	}
-
-	t.Run("int64s", func(t *testing.T) {
-		matched, unmatched := split("int64s", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if diff := cmp.Diff(kv.Ints(), []int64{42}); diff != "" {
-				t.Errorf("diff: %s", diff)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if i64s := kv.Ints(); i64s != nil {
-				t.Errorf("expected nil, got %v", i64s)
-			}
-		}
-	})
-
-	t.Run("uint64s", func(t *testing.T) {
-		matched, unmatched := split("uint64s", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if diff := cmp.Diff(kv.Uints(), []uint64{42}); diff != "" {
-				t.Errorf("diff: %s", diff)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if u64s := kv.Uints(); u64s != nil {
-				t.Errorf("expected nil, got %v", u64s)
-			}
-		}
-	})
-
-	t.Run("float64s", func(t *testing.T) {
-		matched, unmatched := split("float64s", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if diff := cmp.Diff(kv.Floats(), []float64{42}); diff != "" {
-				t.Errorf("diff: %s", diff)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if f64s := kv.Floats(); f64s != nil {
-				t.Errorf("expected nil, got %v", f64s)
-			}
-		}
-	})
-
-	t.Run("strings", func(t *testing.T) {
-		matched, unmatched := split("strings", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if diff := cmp.Diff(kv.Strings(), v); diff != "" {
-				t.Errorf("diff: %s", diff)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if s := kv.Strings(); s != nil {
-				t.Errorf("expected nil, got %v", s)
-			}
-		}
-	})
-
-	t.Run("bools", func(t *testing.T) {
-		matched, unmatched := split("bools", values)
-		for _, v := range matched {
-			kv := KeyValue{"key", Value{v}}
-			if diff := cmp.Diff(kv.Bools(), v); diff != "" {
-				t.Errorf("diff: %s", diff)
-			}
-		}
-
-		for _, v := range unmatched {
-			kv := KeyValue{"key", Value{v}}
-			if b := kv.Bools(); b != nil {
-				t.Errorf("expected nil, got %v", b)
-			}
-		}
-	})
-}
--- a/fs/gguf/lazy.go
+++ b/fs/gguf/lazy.go
@@ -1,89 +0,0 @@
-package gguf
-
-import (
-	"encoding/binary"
-	"iter"
-	"log/slog"
-)
-
-type lazy[T any] struct {
-	count  uint64
-	next   func() (T, bool)
-	stop   func()
-	values []T
-
-	// successFunc is called when all values have been successfully read.
-	successFunc func() error
-}
-
-func newLazy[T any](f *File, fn func() (T, error)) (*lazy[T], error) {
-	it := lazy[T]{}
-	if err := binary.Read(f.reader, binary.LittleEndian, &it.count); err != nil {
-		return nil, err
-	}
-
-	it.values = make([]T, 0)
-	it.next, it.stop = iter.Pull(func(yield func(T) bool) {
-		for i := range it.count {
-			t, err := fn()
-			if err != nil {
-				slog.Error("error reading tensor", "index", i, "error", err)
-				return
-			}
-
-			it.values = append(it.values, t)
-			if !yield(t) {
-				break
-			}
-		}
-
-		if it.successFunc != nil {
-			it.successFunc()
-		}
-	})
-
-	return &it, nil
-}
-
-func (g *lazy[T]) Values() iter.Seq[T] {
-	return func(yield func(T) bool) {
-		for _, v := range g.All() {
-			if !yield(v) {
-				break
-			}
-		}
-	}
-}
-
-func (g *lazy[T]) All() iter.Seq2[int, T] {
-	return func(yield func(int, T) bool) {
-		for i := range int(g.count) {
-			if i < len(g.values) {
-				if !yield(i, g.values[i]) {
-					break
-				}
-			} else {
-				t, ok := g.next()
-				if !ok {
-					break
-				}
-
-				if !yield(i, t) {
-					break
-				}
-			}
-		}
-	}
-}
-
-func (g *lazy[T]) rest() (collected bool) {
-	for {
-		_, ok := g.next()
-		collected = collected || ok
-		if !ok {
-			break
-		}
-	}
-
-	return collected
-}
--- a/fs/gguf/reader.go
+++ b/fs/gguf/reader.go
@@ -1,23 +0,0 @@
-package gguf
-
-import (
-	"bufio"
-	"io"
-)
-
-type bufferedReader struct {
-	offset int64
-	*bufio.Reader
-}
-
-func newBufferedReader(rs io.ReadSeeker, size int) *bufferedReader {
-	return &bufferedReader{
-		Reader: bufio.NewReaderSize(rs, size),
-	}
-}
-
-func (rs *bufferedReader) Read(p []byte) (n int, err error) {
-	n, err = rs.Reader.Read(p)
-	rs.offset += int64(n)
-	return n, err
-}
--- a/fs/gguf/tensor.go
+++ b/fs/gguf/tensor.go
@@ -1,288 +0,0 @@
-package gguf
-
-import (
-	"log/slog"
-	"strings"
-)
-
-type TensorInfo struct {
-	Name   string
-	Offset uint64
-	Shape  []uint64
-	Type   TensorType
-}
-
-func (ti TensorInfo) Valid() bool {
-	return ti.Name != "" && ti.NumBytes() > 0
-}
-
-func (ti TensorInfo) NumValues() int64 {
-	var numItems int64 = 1
-	for _, dim := range ti.Shape {
-		numItems *= int64(dim)
-	}
-	return numItems
-}
-
-// NumBytes returns the number of bytes in the tensor.
-func (ti TensorInfo) NumBytes() int64 {
-	return int64(float64(ti.NumValues()) * ti.Type.NumBytes())
-}
-
-func (ti TensorInfo) LogValue() slog.Value {
-	return slog.GroupValue(
-		slog.String("name", ti.Name),
-		slog.Int64("offset", int64(ti.Offset)),
-		slog.Any("shape", ti.Shape),
-		slog.Int64("num_values", ti.NumValues()),
-		slog.Int64("num_bytes", ti.NumBytes()),
-		slog.Any("type", ti.Type),
-	)
-}
-
-type TensorType uint32
-
-const (
-	TensorTypeF32 TensorType = iota
-	TensorTypeF16
-	TensorTypeQ4_0
-	TensorTypeQ4_1
-
-	// unexported // unused in gguf
-	tensorTypeQ4_2
-	tensorTypeQ4_3
-
-	TensorTypeQ5_0
-	TensorTypeQ5_1
-	TensorTypeQ8_0
-	TensorTypeQ8_1
-	TensorTypeQ2_K
-	TensorTypeQ3_K
-	TensorTypeQ4_K
-	TensorTypeQ5_K
-	TensorTypeQ6_K
-	TensorTypeQ8_K
-
-	// unexported // unquantizable by ollama
-	tensorTypeIQ2_XXS
-	tensorTypeIQ2_XS
-	tensorTypeIQ3_XXS
-	tensorTypeIQ1_S
-	tensorTypeIQ4_NL
-	tensorTypeIQ3_S
-	tensorTypeIQ2_S
-	tensorTypeIQ4_XS
-
-	TensorTypeI8
-	TensorTypeI16
-	TensorTypeI32
-	TensorTypeI64
-	TensorTypeF64
-
-	// unexported // unquantizable by ollama
-	tensorTypeIQ1_M
-
-	TensorTypeBF16
-
-	// unexported // unused in gguf
-	tensorTypeQ4_0_4_4
-	tensorTypeQ4_0_4_8
-	tensorTypeQ4_0_8_8
-
-	// unexported // unquantizable by ollama
-	tensorTypeTQ1_0
-	tensorTypeTQ2_0
-
-	// unexported // unused in gguf
-	tensorTypeIQ4_NL_4_4
-	tensorTypeIQ4_NL_4_8
-	tensorTypeIQ4_NL_8_8
-)
-
-func (tt TensorType) NumBytes() float64 {
-	return float64(tt.typeSize()) / float64(tt.blockSize())
-}
-
-func (tt TensorType) typeSize() int64 {
-	switch tt {
-	case TensorTypeF32:
-		return 4
-	case TensorTypeF16:
-		return 2
-	case TensorTypeQ4_0:
-		return 2 + tt.blockSize()/2
-	case TensorTypeQ4_1:
-		return 2 + 2 + tt.blockSize()/2
-	case TensorTypeQ5_0:
-		return 2 + 4 + tt.blockSize()/2
-	case TensorTypeQ5_1:
-		return 2 + 2 + 4 + tt.blockSize()/2
-	case TensorTypeQ8_0:
-		return 2 + tt.blockSize()
-	case TensorTypeQ8_1:
-		return 2 + 2 + tt.blockSize()
-	case TensorTypeQ2_K:
-		return tt.blockSize()/16 + tt.blockSize()/4 + 2 + 2
-	case TensorTypeQ3_K:
-		return tt.blockSize()/8 + tt.blockSize()/4 + 12 + 2
-	case TensorTypeQ4_K:
-		return 2 + 2 + 12 + tt.blockSize()/2
-	case TensorTypeQ5_K:
-		return 2 + 2 + 12 + tt.blockSize()/8 + tt.blockSize()/2
-	case TensorTypeQ6_K:
-		return tt.blockSize()/2 + tt.blockSize()/4 + tt.blockSize()/16 + 2
-	case TensorTypeQ8_K:
-		return 4 + tt.blockSize() + 2*tt.blockSize()/16
-	case tensorTypeIQ2_XXS:
-		return 2 + 2*tt.blockSize()/8
-	case tensorTypeIQ2_XS:
-		return 2 + 2*tt.blockSize()/8 + tt.blockSize()/32
-	case tensorTypeIQ3_XXS:
-		return 2 + tt.blockSize()/4 + tt.blockSize()/8
-	case tensorTypeIQ1_S:
-		return 2 + tt.blockSize()/8 + tt.blockSize()/16
-	case tensorTypeIQ4_NL:
-		return 2 + tt.blockSize()/2
-	case tensorTypeIQ3_S:
-		return 2 + tt.blockSize()/4 + tt.blockSize()/8 + tt.blockSize()/32 + 4
-	case tensorTypeIQ2_S:
-		return 2 + tt.blockSize()/4 + tt.blockSize()/16
-	case tensorTypeIQ4_XS:
-		return 2 + 2 + tt.blockSize()/2 + tt.blockSize()/64
-	case TensorTypeI8:
-		return 1
-	case TensorTypeI16:
-		return 2
-	case TensorTypeI32:
-		return 4
-	case TensorTypeI64:
-		return 8
-	case TensorTypeF64:
-		return 8
-	case tensorTypeIQ1_M:
-		return tt.blockSize()/8 + tt.blockSize()/16 + tt.blockSize()/32
-	case TensorTypeBF16:
-		return 2
-	default:
-		return 0
-	}
-}
-
-func (tt TensorType) blockSize() int64 {
-	switch tt {
-	case TensorTypeF32,
-		TensorTypeF16,
-		TensorTypeI8,
-		TensorTypeI16,
-		TensorTypeI32,
-		TensorTypeI64,
-		TensorTypeF64,
-		TensorTypeBF16:
-		return 1
-	case TensorTypeQ4_0,
-		TensorTypeQ4_1,
-		TensorTypeQ5_0,
-		TensorTypeQ5_1,
-		TensorTypeQ8_0,
-		TensorTypeQ8_1,
-		tensorTypeIQ4_NL:
-		return 32
-	default:
-		return 256
-	}
-}
-
-func (tt TensorType) String() string {
-	switch tt {
-	case TensorTypeF32:
-		return "f32"
-	case TensorTypeF16:
-		return "f16"
-	case TensorTypeQ4_0:
-		return "q4_0"
-	case TensorTypeQ4_1:
-		return "q4_1"
-	case tensorTypeQ4_2:
-		return "q4_2"
-	case tensorTypeQ4_3:
-		return "q4_3"
-	case TensorTypeQ5_0:
-		return "q5_0"
-	case TensorTypeQ5_1:
-		return "q5_1"
-	case TensorTypeQ8_0:
-		return "q8_0"
-	case TensorTypeQ8_1:
-		return "q8_1"
-	case TensorTypeQ2_K:
-		return "q2_k"
-	case TensorTypeQ3_K:
-		return "q3_k"
-	case TensorTypeQ4_K:
-		return "q4_k"
-	case TensorTypeQ5_K:
-		return "q5_k"
-	case TensorTypeQ6_K:
-		return "q6_k"
-	case TensorTypeQ8_K:
-		return "q8_k"
-	case tensorTypeIQ2_XXS:
-		return "iq2_xxs"
-	case tensorTypeIQ2_XS:
-		return "iq2_xs"
-	case tensorTypeIQ3_XXS:
-		return "iq3_xxs"
-	case tensorTypeIQ1_S:
-		return "iq1_s"
-	case tensorTypeIQ4_NL:
-		return "iq4_nl"
-	case tensorTypeIQ3_S:
-		return "iq3_s"
-	case tensorTypeIQ2_S:
-		return "iq2_s"
-	case tensorTypeIQ4_XS:
-		return "iq4_xs"
-	case TensorTypeI8:
-		return "i8"
-	case TensorTypeI16:
-		return "i16"
-	case TensorTypeI32:
-		return "i32"
-	case TensorTypeI64:
-		return "i64"
-	case TensorTypeF64:
-		return "f64"
-	case tensorTypeIQ1_M:
-		return "iq1_m"
-	case TensorTypeBF16:
-		return "bf16"
-	case tensorTypeQ4_0_4_4:
-		return "q4_0_4_4"
-	case tensorTypeQ4_0_4_8:
-		return "q4_0_4_8"
-	case tensorTypeQ4_0_8_8:
-		return "q4_0_8_8"
-	case tensorTypeTQ1_0:
-		return "tq1_0"
-	case tensorTypeTQ2_0:
-		return "tq2_0"
-	case tensorTypeIQ4_NL_4_4:
-		return "iq4_nl_4_4"
-	case tensorTypeIQ4_NL_4_8:
-		return "iq4_nl_4_8"
-	case tensorTypeIQ4_NL_8_8:
-		return "iq4_nl_8_8"
-	default:
-		return "unknown"
-	}
-}
-
-func (tt TensorType) LogValue() slog.Value {
-	return slog.GroupValue(
-		slog.Uint64("value", uint64(tt)),
-		slog.String("name", strings.ToUpper(tt.String())),
-		slog.Int64("size", tt.typeSize()),
-		slog.Int64("block_size", tt.blockSize()),
-		slog.Float64("num_bytes", tt.NumBytes()),
-	)
-}
--- a/go.mod
+++ b/go.mod
@@ -11,7 +11,7 @@ require (
 	github.com/spf13/cobra v1.7.0
 	github.com/stretchr/testify v1.9.0
 	github.com/x448/float16 v0.8.4
-	golang.org/x/sync v0.12.0
+	golang.org/x/sync v0.11.0
 )

 require (
@@ -19,13 +19,12 @@ require (
 	github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
 	github.com/dlclark/regexp2 v1.11.4
 	github.com/emirpasic/gods/v2 v2.0.0-alpha
-	github.com/google/go-cmp v0.7.0
+	github.com/google/go-cmp v0.6.0
 	github.com/mattn/go-runewidth v0.0.14
 	github.com/nlpodyssey/gopickle v0.3.0
 	github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
 	golang.org/x/image v0.22.0
 	golang.org/x/tools v0.30.0
-	gonum.org/v1/gonum v0.15.0
 )

 require (
@@ -45,6 +44,7 @@ require (
 	github.com/xtgo/set v1.0.0 // indirect
 	go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
 	golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect
+	gonum.org/v1/gonum v0.15.0 // indirect
 	gorgonia.org/vecf32 v0.9.0 // indirect
 	gorgonia.org/vecf64 v0.9.0 // indirect
 )
@@ -70,12 +70,12 @@ require (
 	github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
 	github.com/ugorji/go/codec v1.2.12 // indirect
 	golang.org/x/arch v0.8.0 // indirect
-	golang.org/x/crypto v0.36.0
-	golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa // indirect
-	golang.org/x/net v0.38.0 // indirect
-	golang.org/x/sys v0.31.0
-	golang.org/x/term v0.30.0
-	golang.org/x/text v0.23.0
+	golang.org/x/crypto v0.33.0
+	golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa
+	golang.org/x/net v0.35.0 // indirect
+	golang.org/x/sys v0.30.0
+	golang.org/x/term v0.29.0
+	golang.org/x/text v0.22.0
 	google.golang.org/protobuf v1.34.1
 	gopkg.in/yaml.v3 v3.0.1 // indirect
 )
--- a/go.sum
+++ b/go.sum
@@ -112,8 +112,8 @@ github.com/google/go-cmp v0.4.0/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/
 github.com/google/go-cmp v0.5.0/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
 github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
 github.com/google/go-cmp v0.5.6/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
-github.com/google/go-cmp v0.7.0 h1:wk8382ETsv4JYUZwIsn6YpYiWiBsYLSJiTsyBybVuN8=
-github.com/google/go-cmp v0.7.0/go.mod h1:pXiqmnSA92OHEEa9HXL2W4E7lf9JzCmGVUdgjX3N/iU=
+github.com/google/go-cmp v0.6.0 h1:ofyhxvXcZhMsU5ulbFiLKl/XBFqE1GSq7atu8tAmTRI=
+github.com/google/go-cmp v0.6.0/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
 github.com/google/gofuzz v1.0.0/go.mod h1:dBl0BpW6vV/+mYPU4Po3pmUjxk6FQPldtuIdl/M65Eg=
 github.com/google/uuid v1.1.2/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
 github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
@@ -214,8 +214,8 @@ golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACk
 golang.org/x/crypto v0.0.0-20190510104115-cbcb75029529/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
 golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
 golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
-golang.org/x/crypto v0.36.0 h1:AnAEvhDddvBdpY+uR+MyHmuZzzNqXSe/GvuDeob5L34=
-golang.org/x/crypto v0.36.0/go.mod h1:Y4J0ReaxCR1IMaabaSMugxJES1EpwhBHhv2bDHklZvc=
+golang.org/x/crypto v0.33.0 h1:IOBPskki6Lysi0lo9qQvbxiQ+FvsCC/YWOecCHAixus=
+golang.org/x/crypto v0.33.0/go.mod h1:bVdXmD7IV/4GdElGPozy6U7lWdRXA4qyRVGJV57uQ5M=
 golang.org/x/exp v0.0.0-20180321215751-8460e604b9de/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
 golang.org/x/exp v0.0.0-20180807140117-3d87b88a115f/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
 golang.org/x/exp v0.0.0-20190121172915-509febef88a4/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
@@ -257,8 +257,8 @@ golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81R
 golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
 golang.org/x/net v0.0.0-20210405180319-a5a99cb37ef4/go.mod h1:p54w0d4576C0XHj96bSt6lcn1PtDYWL6XObtHCRCNQM=
 golang.org/x/net v0.0.0-20210614182718-04defd469f4e/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
-golang.org/x/net v0.38.0 h1:vRMAPTMaeGqVhG5QyLJHqNDwecKTomGeqbnfZyKlBI8=
-golang.org/x/net v0.38.0/go.mod h1:ivrbrMbzFq5J41QOQh0siUuly180yBYtLp+CKbEaFx8=
+golang.org/x/net v0.35.0 h1:T5GQRQb2y08kTAByq9L4/bz8cipCdA8FbRTXewonqY8=
+golang.org/x/net v0.35.0/go.mod h1:EglIi67kWsHKlRzzVMUD93VMSWGFOMSZgxFjparz1Qk=
 golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
 golang.org/x/oauth2 v0.0.0-20200107190931-bf48bf16ab8d/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
 golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -268,8 +268,8 @@ golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJ
 golang.org/x/sync v0.0.0-20190911185100-cd5d95a43a6e/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.0.0-20210220032951-036812b2e83c/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
-golang.org/x/sync v0.12.0 h1:MHc5BpPuC30uJk597Ri8TV3CNZcTLu6B6z4lJy+g6Jw=
-golang.org/x/sync v0.12.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
+golang.org/x/sync v0.11.0 h1:GGz8+XQP4FvTTrjZPzNKTMFtSXH80RAzG+5ghFPgK9w=
+golang.org/x/sync v0.11.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
 golang.org/x/sys v0.0.0-20180830151530-49385e6e1522/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
 golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
 golang.org/x/sys v0.0.0-20190312061237-fead79001313/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -285,17 +285,17 @@ golang.org/x/sys v0.0.0-20210510120138-977fb7262007/go.mod h1:oPkhp1MJrh7nUepCBc
 golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
-golang.org/x/sys v0.31.0 h1:ioabZlmFYtWhL+TRYpcnNlLwhyxaM9kWTDEmfnprqik=
-golang.org/x/sys v0.31.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
+golang.org/x/sys v0.30.0 h1:QjkSwP/36a20jFYWkSue1YwXzLmsV5Gfq7Eiy72C1uc=
+golang.org/x/sys v0.30.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
 golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
-golang.org/x/term v0.30.0 h1:PQ39fJZ+mfadBm0y5WlL4vlM7Sx1Hgf13sMIY2+QS9Y=
-golang.org/x/term v0.30.0/go.mod h1:NYYFdzHoI5wRh/h5tDMdMqCqPJZEuNqVR5xJLd/n67g=
+golang.org/x/term v0.29.0 h1:L6pJp37ocefwRRtYPKSWOWzOtWSxVajvz2ldH/xi3iU=
+golang.org/x/term v0.29.0/go.mod h1:6bl4lRlvVuDgSf3179VpIxBF0o10JUpXWOnI7nErv7s=
 golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
 golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
 golang.org/x/text v0.3.5/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
 golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
-golang.org/x/text v0.23.0 h1:D71I7dUrlY+VX0gQShAThNGHFxZ13dGLBHQLVl1mJlY=
-golang.org/x/text v0.23.0/go.mod h1:/BLNzu4aZCJ1+kcD0DNRotWKage4q2rGVAg4o22unh4=
+golang.org/x/text v0.22.0 h1:bofq7m3/HAFvbF51jz3Q9wLg3jkvSPuiZu/pD1XwgtM=
+golang.org/x/text v0.22.0/go.mod h1:YRoo4H8PVmsu+E3Ou7cqLVH8oXWIHVoX0jqUWALQhfY=
 golang.org/x/tools v0.0.0-20180525024113-a5b4c53f6e8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
 golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
 golang.org/x/tools v0.0.0-20190114222345-bf090417da8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
--- a/harmony/harmonyparser.go
+++ b/harmony/harmonyparser.go
@@ -1,544 +0,0 @@
-package harmony
-
-import (
-	"encoding/json"
-	"fmt"
-	"log/slog"
-	"strings"
-	"unicode"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/logutil"
-)
-
-type harmonyParserState int
-
-const (
-	harmonyParserState_LookingForMessageStart harmonyParserState = iota
-	harmonyParserState_ParsingHeader
-	harmonyParserState_ParsingContent
-)
-
-func (s harmonyParserState) String() string {
-	switch s {
-	// we're looking for the message start tag
-	case harmonyParserState_LookingForMessageStart:
-		return "LookingForMessageStart"
-	case harmonyParserState_ParsingHeader:
-		return "ParsingHeader"
-	case harmonyParserState_ParsingContent:
-		return "ParsingContent"
-	default:
-		return "Unknown"
-	}
-}
-
-type HarmonyParser struct {
-	state           harmonyParserState
-	MessageStartTag string
-	MessageEndTag   string
-	HeaderEndTag    string
-	acc             strings.Builder
-	lifetimeAcc     strings.Builder
-}
-
-type HarmonyEvent interface {
-	isHarmonyEvent()
-}
-
-type HarmonyEventMessageStart struct{}
-
-func (HarmonyEventMessageStart) isHarmonyEvent() {}
-
-type HarmonyEventHeaderComplete struct {
-	Header HarmonyHeader
-}
-
-func (HarmonyEventHeaderComplete) isHarmonyEvent() {}
-
-type HarmonyEventContentEmitted struct {
-	Content string
-}
-
-func (HarmonyEventContentEmitted) isHarmonyEvent() {}
-
-type HarmonyEventMessageEnd struct{}
-
-func (HarmonyEventMessageEnd) isHarmonyEvent() {}
-
-type HarmonyHeader struct {
-	Role      string
-	Channel   string
-	Recipient string
-}
-
-func (s *HarmonyParser) AddImplicitStart() {
-	s.acc.WriteString("<|start|>assistant")
-}
-
-func (s *HarmonyParser) AddImplicitStartOrPrefill(lastMessage *api.Message) {
-	if lastMessage != nil && lastMessage.Role == "assistant" {
-		// handle prefilling conditions
-		if lastMessage.Content != "" {
-			s.acc.WriteString("<|start|>assistant<|channel|>final<|message|>")
-			return
-		} else if lastMessage.Thinking != "" {
-			s.acc.WriteString("<|start|>assistant<|channel|>analysis<|message|>")
-			return
-		}
-	}
-	s.AddImplicitStart()
-}
-
-func (s *HarmonyParser) AddContent(content string) []HarmonyEvent {
-	s.lifetimeAcc.WriteString(content)
-	s.acc.WriteString(content)
-
-	var events []HarmonyEvent
-
-	keepLooping := true
-	// we loop because we might pass through multiple parsing states in a single
-	// call to addContent, and we want to make sure callers don't have to wait for
-	// data that's already unambiguous
-	for keepLooping {
-		var newEvents []HarmonyEvent
-		newEvents, keepLooping = eat(s)
-		events = append(events, newEvents...)
-	}
-
-	return events
-}
-
-// the additional bool return is true iff we should continue eating
-func eat(s *HarmonyParser) ([]HarmonyEvent, bool) {
-	switch s.state {
-	case harmonyParserState_LookingForMessageStart:
-		// does the acc contain the message start tag?
-		if strings.Contains(s.acc.String(), s.MessageStartTag) {
-			// split the acc into the message start tag and the rest
-			split := strings.SplitN(s.acc.String(), s.MessageStartTag, 2)
-			before := split[0]
-			if before != "" {
-				slog.Warn("harmony parser: found message start tag in the middle of the content", "content", s.acc.String())
-			}
-			after := split[1]
-			s.acc.Reset()
-			s.acc.WriteString(after)
-			s.state = harmonyParserState_ParsingHeader
-			return []HarmonyEvent{HarmonyEventMessageStart{}}, true
-		}
-
-		// no match, so we keep accumulating
-		return nil, false
-	case harmonyParserState_ParsingHeader:
-		if strings.Contains(s.acc.String(), s.HeaderEndTag) {
-			split := strings.SplitN(s.acc.String(), s.HeaderEndTag, 2)
-			header := split[0]
-			after := split[1]
-			s.acc.Reset()
-			s.acc.WriteString(after)
-			s.state = harmonyParserState_ParsingContent
-			return []HarmonyEvent{HarmonyEventHeaderComplete{Header: s.parseHeader(header)}}, true
-		}
-		return nil, false
-	case harmonyParserState_ParsingContent:
-		if strings.Contains(s.acc.String(), s.MessageEndTag) {
-			// if we already have the message end tag, we can emit the content up to it
-			split := strings.SplitN(s.acc.String(), s.MessageEndTag, 2)
-			content := split[0]
-			after := split[1]
-			s.acc.Reset()
-			s.acc.WriteString(after)
-			s.state = harmonyParserState_LookingForMessageStart
-			events := []HarmonyEvent{}
-			if content != "" {
-				events = append(events, HarmonyEventContentEmitted{Content: content})
-			}
-			events = append(events, HarmonyEventMessageEnd{})
-			return events, true
-		} else if overlapLen := overlap(s.acc.String(), s.MessageEndTag); overlapLen > 0 {
-			// if our suffix contains the start of the message end tag, we can emit
-			// the content up to the start of the message end tag
-			content := s.acc.String()[:len(s.acc.String())-overlapLen]
-			remaining := s.acc.String()[len(s.acc.String())-overlapLen:]
-			s.acc.Reset()
-			s.acc.WriteString(remaining)
-			// emit the content we know isn't part of the message end tag, and keep
-			// accumulating to disambiguate the rest
-			if content == "" {
-				return nil, false
-			}
-			return []HarmonyEvent{HarmonyEventContentEmitted{Content: content}}, false
-		} else {
-			// no end tag, so it's still normal content that we can immediately emit
-			content := s.acc.String()
-			if content == "" {
-				return nil, false
-			}
-			s.acc.Reset()
-			return []HarmonyEvent{HarmonyEventContentEmitted{Content: content}}, false
-		}
-	}
-
-	return nil, false
-}
-
-func (s *HarmonyParser) parseHeader(raw string) HarmonyHeader {
-	harmonyHeader := HarmonyHeader{}
-
-	// if `<|constrain|>` is present, ensure it has a space before it so it gets
-	// parsed as a separate token, even if the model didn't include the space
-	if strings.Contains(raw, "<|constrain|>") {
-		raw = strings.Replace(raw, "<|constrain|>", " <|constrain|>", 1)
-		raw = strings.TrimSpace(raw)
-	}
-
-	// look for the optional channel tag, which is `<|channel|>` followed by the
-	// channel name, all without any whitespace
-	channelIndex := strings.Index(raw, "<|channel|>")
-	if channelIndex != -1 {
-		before := raw[:channelIndex]
-		after := raw[channelIndex+len("<|channel|>"):]
-		// the channel name is `after` all the way up to the first (if any) whitespace character
-		idx := strings.IndexFunc(after, func(r rune) bool {
-			return unicode.IsSpace(r)
-		})
-		if idx == -1 {
-			idx = len(after)
-		}
-		harmonyHeader.Channel = after[:idx]
-		after = after[idx:]
-		// now we remove the channel tag from the raw string to further process
-		raw = before + after
-		raw = strings.TrimSpace(raw)
-	}
-
-	// split the header into whitespace-separated tokens
-	tokens := strings.Fields(raw)
-
-	// the first token is treated as the role
-	if len(tokens) == 0 {
-		slog.Error("harmony parser: missing role in header", "header", raw)
-		return harmonyHeader
-	}
-	role := tokens[0]
-	tokens = tokens[1:]
-	// special case: if role starts with to= then it's a tool call
-	if strings.HasPrefix(role, "to=") {
-		harmonyHeader.Recipient = role[3:]
-		harmonyHeader.Role = "tool"
-	} else {
-		harmonyHeader.Role = role
-	}
-
-	// the recipient (if any) can be specified before or after the channel tag, so
-	// we check it at the end once we've already parsed the channel and role
-	if harmonyHeader.Recipient == "" && len(tokens) > 0 && strings.HasPrefix(tokens[0], "to=") {
-		harmonyHeader.Recipient = tokens[0][3:]
-	}
-
-	return harmonyHeader
-}
-
-// longest overlap between suffix of s and prefix of delim
-func overlap(s, delim string) int {
-	max := min(len(delim), len(s))
-	for i := max; i > 0; i-- {
-		if strings.HasSuffix(s, delim[:i]) {
-			return i
-		}
-	}
-	return 0
-}
-
-// harmonyMessageState represents the current state of message processing
-type harmonyMessageState int
-
-const (
-	harmonyMessageState_Normal harmonyMessageState = iota
-	harmonyMessageState_Thinking
-	harmonyMessageState_ToolCalling
-)
-
-// HarmonyMessageHandler processes harmony events and accumulates content appropriately.
-// This is a higher level interface that maps harmony concepts into ollama concepts
-type HarmonyMessageHandler struct {
-	state           harmonyMessageState
-	HarmonyParser   *HarmonyParser
-	FunctionNameMap *FunctionNameMap
-	toolAccumulator *HarmonyToolCallAccumulator
-	convertedTools  map[string]struct{}
-}
-
-// NewHarmonyMessageHandler creates a new message handler
-func NewHarmonyMessageHandler() *HarmonyMessageHandler {
-	return &HarmonyMessageHandler{
-		state: harmonyMessageState_Normal,
-		HarmonyParser: &HarmonyParser{
-			MessageStartTag: "<|start|>",
-			MessageEndTag:   "<|end|>",
-			HeaderEndTag:    "<|message|>",
-		},
-		FunctionNameMap: NewFunctionNameMap(),
-		convertedTools:  make(map[string]struct{}),
-	}
-}
-
-// AddContent processes the content and returns the content, thinking, and tool content.
-// content and thinking are already fully parsed, but tool content still needs to be passed to the tool parser
-func (h *HarmonyMessageHandler) AddContent(content string, toolParser *HarmonyToolCallAccumulator) (string, string, string) {
-	contentSb := strings.Builder{}
-	thinkingSb := strings.Builder{}
-	toolContentSb := strings.Builder{}
-
-	events := h.HarmonyParser.AddContent(content)
-	for _, event := range events {
-		switch event := event.(type) {
-		case HarmonyEventHeaderComplete:
-			logutil.Trace("harmony event header complete", "header", event.Header)
-			switch event.Header.Channel {
-			case "analysis":
-				if event.Header.Recipient != "" {
-					h.state = harmonyMessageState_ToolCalling
-					// event.Header.Recipient is the tool name, something like
-					// "browser.search" for a built-in, or "functions.calc" for a
-					// custom one
-					toolParser.SetToolName(event.Header.Recipient)
-				} else {
-					h.state = harmonyMessageState_Thinking
-				}
-			case "commentary":
-				if event.Header.Recipient != "" {
-					h.state = harmonyMessageState_ToolCalling
-					toolParser.SetToolName(event.Header.Recipient)
-				} else {
-					h.state = harmonyMessageState_Normal
-				}
-			case "final":
-				h.state = harmonyMessageState_Normal
-			}
-		case HarmonyEventContentEmitted:
-			logutil.Trace("harmony event content", "content", event.Content, "state", h.state)
-			if h.state == harmonyMessageState_Normal {
-				contentSb.WriteString(event.Content)
-			} else if h.state == harmonyMessageState_Thinking {
-				thinkingSb.WriteString(event.Content)
-			} else if h.state == harmonyMessageState_ToolCalling {
-				toolContentSb.WriteString(event.Content)
-			}
-		case HarmonyEventMessageEnd:
-			h.state = harmonyMessageState_Normal
-		}
-	}
-	return contentSb.String(), thinkingSb.String(), toolContentSb.String()
-}
-
-func (h *HarmonyMessageHandler) CreateToolParser() *HarmonyToolCallAccumulator {
-	return &HarmonyToolCallAccumulator{
-		state:           harmonyToolCallState_Normal,
-		currentToolName: nil,
-	}
-}
-
-type harmonyToolCallState int
-
-const (
-	harmonyToolCallState_Normal harmonyToolCallState = iota
-	harmonyToolCallState_ToolCalling
-)
-
-type HarmonyToolCallAccumulator struct {
-	state           harmonyToolCallState
-	acc             strings.Builder
-	currentToolName *string
-}
-
-func (a *HarmonyToolCallAccumulator) SetToolName(toolName string) {
-	a.currentToolName = &toolName
-}
-
-func (a *HarmonyToolCallAccumulator) Add(content string) {
-	a.acc.WriteString(content)
-}
-
-func (a *HarmonyToolCallAccumulator) Drain() (*string, string) {
-	str := a.acc.String()
-	a.state = harmonyToolCallState_Normal
-	a.acc.Reset()
-	return a.currentToolName, str
-}
-
-func (a *HarmonyToolCallAccumulator) Content() string {
-	return a.acc.String()
-}
-
-// FunctionNameMap maps a user-specified function name to a valid function
-// name for harmony (which look like TypeScript identifiers). This is needed to
-// transform user-specified function names, which might contain characters that
-// are not allowed in TypeScript identifiers
-type FunctionNameMap struct {
-	userToHarmony map[string]string
-	harmonyToUser map[string]string
-}
-
-func NewFunctionNameMap() *FunctionNameMap {
-	return &FunctionNameMap{
-		userToHarmony: make(map[string]string),
-		harmonyToUser: make(map[string]string),
-	}
-}
-
-// Init initializes the handler with tools and optional last message
-// Implements the Parser interface
-func (h *HarmonyMessageHandler) Init(tools []api.Tool, lastMessage *api.Message) []api.Tool {
-	// Initialize the harmony parser
-	if h.HarmonyParser == nil {
-		h.HarmonyParser = &HarmonyParser{
-			MessageStartTag: "<|start|>",
-			MessageEndTag:   "<|end|>",
-			HeaderEndTag:    "<|message|>",
-		}
-	}
-
-	// Handle prefill for chat mode
-	if lastMessage != nil {
-		h.HarmonyParser.AddImplicitStartOrPrefill(lastMessage)
-	} else {
-		h.HarmonyParser.AddImplicitStart()
-	}
-
-	// Initialize tool accumulator
-	h.toolAccumulator = h.CreateToolParser()
-
-	// Process tools and return renamed versions
-	if len(tools) == 0 {
-		return tools
-	}
-
-	processedTools := make([]api.Tool, len(tools))
-	copy(processedTools, tools)
-	for i, tool := range processedTools {
-		if tool.Function.Name != "" {
-			processedTools[i].Function.Name = h.FunctionNameMap.ConvertAndAdd(tool.Function.Name)
-			h.convertedTools[tool.Function.Name] = struct{}{}
-		}
-	}
-	return processedTools
-}
-
-// Add implements the Parser interface - processes streamed content and extracts content, thinking, and tool calls
-func (h *HarmonyMessageHandler) Add(s string, done bool) (content string, thinking string, calls []api.ToolCall, err error) {
-	content, thinking, toolContent := h.AddContent(s, h.toolAccumulator)
-	if toolContent != "" {
-		h.toolAccumulator.Add(toolContent)
-	}
-
-	// tool calls always happen one at a time, and always at the end of a message,
-	// so for simplicity we defer parsing them until we know we're done
-	if done {
-		toolName, raw := h.toolAccumulator.Drain()
-		if toolName != nil {
-			name := strings.TrimPrefix(*toolName, "functions.")
-			name = h.FunctionNameMap.OriginalFromConverted(name)
-			var args api.ToolCallFunctionArguments
-			if err := json.Unmarshal([]byte(raw), &args); err != nil {
-				return "", "", nil, fmt.Errorf("error parsing tool call: raw='%s', err=%w", raw, err)
-			}
-			calls = append(calls, api.ToolCall{Function: api.ToolCallFunction{Name: name, Arguments: args}})
-		}
-	}
-
-	return content, thinking, calls, nil
-}
-
-// HasToolSupport implements the Parser interface
-func (h *HarmonyMessageHandler) HasToolSupport() bool {
-	return true
-}
-
-// HasThinkingSupport implements the Parser interface
-func (h *HarmonyMessageHandler) HasThinkingSupport() bool {
-	return true
-}
-
-func (m *FunctionNameMap) ConvertAndAdd(userFunctionName string) string {
-	harmonyFunctionName := m.deriveName(userFunctionName)
-	// built-in functions should not be renamed
-	if userFunctionName == "browser.open" || userFunctionName == "browser.search" || userFunctionName == "browser.find" || userFunctionName == "python" {
-		harmonyFunctionName = userFunctionName
-	}
-	m.userToHarmony[userFunctionName] = harmonyFunctionName
-	m.harmonyToUser[harmonyFunctionName] = userFunctionName
-	return harmonyFunctionName
-}
-
-// OriginalFromConverted looks up the reverse-mapping of a previously-converted
-// user->harmony function name. To unmap reliably, the mapping must exist, as
-// the conversion process is not reversible without the appropriate state
-func (m *FunctionNameMap) OriginalFromConverted(harmonyFunctionName string) string {
-	if userFunctionName, ok := m.harmonyToUser[harmonyFunctionName]; ok {
-		return userFunctionName
-	}
-	slog.Warn("harmony parser: no reverse mapping found for function name", "harmonyFunctionName", harmonyFunctionName)
-	// fallback to the original function name if we can't find a mapping
-	return harmonyFunctionName
-}
-
-// convertToValidChars converts a user-specified function name to a valid
-// TypeScript identifier.
-//
-// Limitations:
-//
-//   - This doesn't restrict reserved TypeScript keywords.
-//   - We don't perform a real ID_Start/ID_Continue check, and instead use the more
-//     restrictive unicode.IsLetter/unicode.IsDigit check. Unclear what kind of
-//     identifiers these models were trained on, so in the end we might want to
-//     convert unicode-heavy identifiers to their closest ASCII equivalents.
-func (m *FunctionNameMap) convertToValidChars(userFunctionName string) string {
-	mapper := func(r rune) rune {
-		// first, replace certain characters with underscores
-		if r == ' ' || r == '-' || r == '.' {
-			return '_'
-		}
-
-		if unicode.IsLetter(r) || unicode.IsDigit(r) || r == '_' || r == '$' {
-			return r
-		}
-
-		// finally, remove any other characters
-		return -1
-	}
-	candidate := strings.Map(mapper, userFunctionName)
-
-	// set a default name if we end up with nothing left
-	if candidate == "" {
-		return "unnamed"
-	}
-
-	// if the candidate starts with a number, prepend an underscore to make it a
-	// valid identifier
-	if unicode.IsDigit(rune(candidate[0])) {
-		candidate = "_" + candidate
-	}
-
-	return candidate
-}
-
-func (m *FunctionNameMap) deriveName(userFunctionName string) string {
-	originalCandidate := m.convertToValidChars(userFunctionName)
-	candidate := originalCandidate
-
-	// Check for dupes, and if so, add a number to the end.
-	// We start at 2 because if we have dupes and the first is never renamed, it
-	// makes sense for them to be named, say, `f`, `f_2`, `f_3`
-	count := 2
-	for {
-		if _, exists := m.harmonyToUser[candidate]; !exists {
-			break
-		}
-		candidate = fmt.Sprintf("%s_%d", originalCandidate, count)
-		count++
-	}
-
-	return candidate
-}
--- a/harmony/harmonyparser_test.go
+++ b/harmony/harmonyparser_test.go
@@ -1,538 +0,0 @@
-package harmony
-
-import (
-	"fmt"
-	"reflect"
-	"testing"
-)
-
-func TestHeaderParsing(t *testing.T) {
-	tests := []struct {
-		in, wantRole, wantChannel, wantRecipient string
-	}{
-		{
-			in:            "assistant<|channel|>analysis",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "",
-		},
-		{
-			in:            "assistant<|channel|>analysis to=functions.get_weather",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "functions.get_weather",
-		},
-		{
-			in:            "assistant to=functions.get_weather<|channel|>analysis",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "functions.get_weather",
-		},
-		// special case where the role is replaced by the recipient (matches reference code)
-		{
-			in:            "to=functions.get_weather<|channel|>analysis",
-			wantRole:      "tool",
-			wantChannel:   "analysis",
-			wantRecipient: "functions.get_weather",
-		},
-		// extra token after the recipient is ignored
-		{
-			in:            "assistant to=functions.get_weather abc<|channel|>analysis",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "functions.get_weather",
-		},
-		// with constrain tag, recipient after channel tag
-		{
-			in:            "assistant<|channel|>commentary to=functions.get_weather <|constrain|>json",
-			wantRole:      "assistant",
-			wantChannel:   "commentary",
-			wantRecipient: "functions.get_weather",
-		},
-		// with constrain tag, recipient before channel tag
-		{
-			in:            "assistant to=functions.get_weather<|channel|>commentary <|constrain|>json",
-			wantRole:      "assistant",
-			wantChannel:   "commentary",
-			wantRecipient: "functions.get_weather",
-		},
-		// constrain tag without space
-		{
-			in:            "assistant<|channel|>commentary to=functions.get_weather<|constrain|>json",
-			wantRole:      "assistant",
-			wantChannel:   "commentary",
-			wantRecipient: "functions.get_weather",
-		},
-		// constrain tag without space, different order
-		{
-			in:            "assistant to=functions.get_weather<|channel|>commentary<|constrain|>json",
-			wantRole:      "assistant",
-			wantChannel:   "commentary",
-			wantRecipient: "functions.get_weather",
-		},
-	}
-	for i, tt := range tests {
-		parser := HarmonyParser{
-			MessageStartTag: "<|start|>",
-			MessageEndTag:   "<|end|>",
-			HeaderEndTag:    "<|message|>",
-		}
-		header := parser.parseHeader(tt.in)
-
-		if header.Role != tt.wantRole {
-			t.Errorf("case %d: got role \"%s\", want \"%s\"", i, header.Role, tt.wantRole)
-		}
-		if header.Channel != tt.wantChannel {
-			t.Errorf("case %d: got channel \"%s\", want \"%s\"", i, header.Channel, tt.wantChannel)
-		}
-		if header.Recipient != tt.wantRecipient {
-			t.Errorf("case %d: got recipient \"%s\", want \"%s\"", i, header.Recipient, tt.wantRecipient)
-		}
-	}
-}
-
-func TestHarmonyParserHeaderEvent(t *testing.T) {
-	tests := []struct {
-		in, wantRole, wantChannel, wantRecipient string
-		implicitStart                            bool
-	}{
-		{
-			in:            "<|start|>user<|message|>What is 2 + 2?<|end|>",
-			wantRole:      "user",
-			wantChannel:   "",
-			wantRecipient: "",
-		},
-		{
-			in:            "<|start|>assistant<|channel|>analysis<|message|>What is 2 + 2?<|end|>",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "",
-		},
-		{
-			in:            "<|start|>assistant<|channel|>commentary to=functions.get_weather <|constrain|>json<|message|>{\"location\":\"San Francisco\"}<|call|><|start|>functions.get_weather to=assistant<|message|>{\"sunny\": true, \"temperature\": 20}<|end|>",
-			wantRole:      "assistant",
-			wantChannel:   "commentary",
-			wantRecipient: "functions.get_weather",
-		},
-		{
-			in:            "<|channel|>analysis<|message|>User asks weather in SF. We need location. Use get_current_weather with location \"San Francisco, CA\".<|end|><|start|>assistant<|channel|>commentary to=functions.get_current_weather <|constrain|>json<|message|>{\"location\":\"San Francisco, CA\"}<|call|>",
-			wantRole:      "assistant",
-			wantChannel:   "analysis",
-			wantRecipient: "",
-			implicitStart: true,
-		},
-	}
-	for i, tt := range tests {
-		parser := HarmonyParser{
-			MessageStartTag: "<|start|>",
-			MessageEndTag:   "<|end|>",
-			HeaderEndTag:    "<|message|>",
-		}
-		if tt.implicitStart {
-			parser.AddImplicitStart()
-		}
-		gotEvents := parser.AddContent(tt.in)
-		if len(gotEvents) == 0 {
-			t.Errorf("case %d: got no events, want at least one", i)
-		}
-
-		var firstHeaderEvent *HarmonyEventHeaderComplete
-		// print events
-		for _, event := range gotEvents {
-			fmt.Printf("event: %+v\n", event)
-		}
-		for _, event := range gotEvents {
-			if event, ok := event.(HarmonyEventHeaderComplete); ok {
-				firstHeaderEvent = &event
-				break
-			}
-		}
-
-		if firstHeaderEvent == nil {
-			t.Errorf("case %d: got no header complete event, want one", i)
-			continue
-		}
-		gotHeader := firstHeaderEvent.Header
-		if gotHeader.Role != tt.wantRole || gotHeader.Channel != tt.wantChannel || gotHeader.Recipient != tt.wantRecipient {
-			t.Errorf("case %d: got header %+v, want role=%s channel=%s recipient=%s", i, gotHeader, tt.wantRole, tt.wantChannel, tt.wantRecipient)
-		}
-	}
-}
-
-func TestHarmonyParserNonStreaming(t *testing.T) {
-	tests := []struct {
-		in            string
-		implicitStart bool
-		wantEvents    []HarmonyEvent
-	}{
-		{
-			in: "<|start|>user<|message|>What is 2 + 2?<|end|>",
-			wantEvents: []HarmonyEvent{
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-				HarmonyEventContentEmitted{Content: "What is 2 + 2?"},
-				HarmonyEventMessageEnd{},
-			},
-		},
-		{
-			in: "<|start|>assistant<|channel|>analysis<|message|>The answer is 4<|end|>",
-			wantEvents: []HarmonyEvent{
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "analysis", Recipient: ""}},
-				HarmonyEventContentEmitted{Content: "The answer is 4"},
-				HarmonyEventMessageEnd{},
-			},
-		},
-		{
-			in: "<|start|>assistant<|channel|>commentary to=functions.calc<|message|>Computing...<|end|>",
-			wantEvents: []HarmonyEvent{
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "commentary", Recipient: "functions.calc"}},
-				HarmonyEventContentEmitted{Content: "Computing..."},
-				HarmonyEventMessageEnd{},
-			},
-		},
-		{
-			in: "<|start|>user<|message|><|end|>",
-			wantEvents: []HarmonyEvent{
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-				HarmonyEventMessageEnd{},
-			},
-		},
-		{
-			in: "<|start|>user<|message|>Hello<|end|><|start|>assistant<|message|>Hi!<|end|>",
-			wantEvents: []HarmonyEvent{
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-				HarmonyEventContentEmitted{Content: "Hello"},
-				HarmonyEventMessageEnd{},
-				HarmonyEventMessageStart{},
-				HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "", Recipient: ""}},
-				HarmonyEventContentEmitted{Content: "Hi!"},
-				HarmonyEventMessageEnd{},
-			},
-		},
-		{
-			in:            "<|channel|>analysis<|message|>Thinking about the request<|end|>",
-			implicitStart: true,
-			wantEvents:    []HarmonyEvent{HarmonyEventMessageStart{}, HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "analysis", Recipient: ""}}, HarmonyEventContentEmitted{Content: "Thinking about the request"}, HarmonyEventMessageEnd{}},
-		},
-	}
-	for i, tt := range tests {
-		parser := HarmonyParser{
-			MessageStartTag: "<|start|>",
-			MessageEndTag:   "<|end|>",
-			HeaderEndTag:    "<|message|>",
-		}
-		if tt.implicitStart {
-			parser.AddImplicitStart()
-		}
-		gotEvents := parser.AddContent(tt.in)
-		if !reflect.DeepEqual(gotEvents, tt.wantEvents) {
-			t.Errorf("case %d: got events %#v, want %#v", i, gotEvents, tt.wantEvents)
-		}
-	}
-}
-
-func TestHarmonyParserStreaming(t *testing.T) {
-	type step struct {
-		input      string
-		wantEvents []HarmonyEvent
-	}
-
-	cases := []struct {
-		desc          string
-		implicitStart bool
-		steps         []step
-	}{
-		{
-			desc: "simple message streamed character by character",
-			steps: []step{
-				{
-					input:      "<",
-					wantEvents: nil,
-				},
-				{
-					input:      "|",
-					wantEvents: nil,
-				},
-				{
-					input:      "start|>u",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageStart{}},
-				},
-				{
-					input:      "ser<|mess",
-					wantEvents: nil,
-				},
-				{
-					input: "age|>Hi",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-						HarmonyEventContentEmitted{Content: "Hi"},
-					},
-				},
-				{
-					input:      " there",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: " there"}},
-				},
-				{
-					input:      "<|e",
-					wantEvents: nil,
-				},
-				{
-					input:      "nd|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc: "message with channel streamed",
-			steps: []step{
-				{
-					input:      "<|start|>assistant",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageStart{}},
-				},
-				{
-					input:      "<|chan",
-					wantEvents: nil,
-				},
-				{
-					input:      "nel|>analysis",
-					wantEvents: nil,
-				},
-				{
-					input:      "<|message|>",
-					wantEvents: []HarmonyEvent{HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "analysis", Recipient: ""}}},
-				},
-				{
-					input:      "Thinking",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "Thinking"}},
-				},
-				{
-					input:      "...",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "..."}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc: "message with channel and recipient",
-			steps: []step{
-				{
-					input: "<|start|>assistant<|channel|>commentary to=functions.calc<|message|>",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventMessageStart{},
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "commentary", Recipient: "functions.calc"}},
-					},
-				},
-				{
-					input:      "{\"x\": 5}",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "{\"x\": 5}"}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc: "message with channel and recipient (receipient before channel)",
-			steps: []step{
-				{
-					input: "<|start|>assistant to=functions.calc<|channel|>commentary<|message|>",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventMessageStart{},
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "commentary", Recipient: "functions.calc"}},
-					},
-				},
-				{
-					input:      "{\"x\": 5}",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "{\"x\": 5}"}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc:          "implicit start with channel",
-			implicitStart: true,
-			steps: []step{
-				{
-					input:      "<|channel|>thinking",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageStart{}},
-				},
-				{
-					input:      "<|message|>",
-					wantEvents: []HarmonyEvent{HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "thinking", Recipient: ""}}},
-				},
-				{
-					input:      "Processing request",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "Processing request"}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc: "multiple messages streamed",
-			steps: []step{
-				{
-					input: "<|start|>user<|message|>Hello<|end|>",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventMessageStart{},
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-						HarmonyEventContentEmitted{Content: "Hello"},
-						HarmonyEventMessageEnd{},
-					},
-				},
-				{
-					input:      "<|start|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageStart{}},
-				},
-				{
-					input:      "assistant<|message|>",
-					wantEvents: []HarmonyEvent{HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "assistant", Channel: "", Recipient: ""}}},
-				},
-				{
-					input:      "Hi!",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "Hi!"}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-		{
-			desc: "empty message",
-			steps: []step{
-				{
-					input: "<|start|>system<|message|><|end|>",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventMessageStart{},
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "system", Channel: "", Recipient: ""}},
-						HarmonyEventMessageEnd{},
-					},
-				},
-			},
-		},
-		{
-			desc: "partial tag that looks like end but isn't",
-			steps: []step{
-				{
-					input: "<|start|>user<|message|>test<|e",
-					wantEvents: []HarmonyEvent{
-						HarmonyEventMessageStart{},
-						HarmonyEventHeaderComplete{Header: HarmonyHeader{Role: "user", Channel: "", Recipient: ""}},
-						HarmonyEventContentEmitted{Content: "test"},
-					},
-				},
-				{
-					input:      "xample|>more",
-					wantEvents: []HarmonyEvent{HarmonyEventContentEmitted{Content: "<|example|>more"}},
-				},
-				{
-					input:      "<|end|>",
-					wantEvents: []HarmonyEvent{HarmonyEventMessageEnd{}},
-				},
-			},
-		},
-	}
-
-	for _, tc := range cases {
-		t.Run(tc.desc, func(t *testing.T) {
-			parser := HarmonyParser{
-				MessageStartTag: "<|start|>",
-				MessageEndTag:   "<|end|>",
-				HeaderEndTag:    "<|message|>",
-			}
-			if tc.implicitStart {
-				parser.AddImplicitStart()
-			}
-
-			for i, step := range tc.steps {
-				gotEvents := parser.AddContent(step.input)
-				if !reflect.DeepEqual(gotEvents, step.wantEvents) {
-					t.Errorf("step %d: input %q: got events %#v, want %#v", i, step.input, gotEvents, step.wantEvents)
-				}
-			}
-		})
-	}
-}
-
-// TestFunctionConvertToValidChars tests only FunctionNameMap.convert(), which doesn't
-// handle any saving (and therefore no dupe handling)
-func TestFunctionConvertToValidChars(t *testing.T) {
-	tests := []struct {
-		name string
-		in   string
-		want string
-	}{
-		{name: "replace spaces with underscores", in: "get weather", want: "get_weather"},
-		{name: "replace hyphens with underscores", in: "get-weather", want: "get_weather"},
-		{name: "replace periods with underscores", in: "get.weather", want: "get_weather"},
-		{name: "disallow non-word characters", in: "get weather!", want: "get_weather"},
-		{name: "strip out invalid non-alphanumeric unicode characters", in: "a🫠bc", want: "abc"},
-		{name: "names that only contain invalid characters", in: "🫠", want: "unnamed"},
-		{name: "leading number", in: "123", want: "_123"},
-		{name: "$ allowed", in: "$", want: "$"},
-		// show that we allow weird unicode letter characters, though we might want
-		// to convert them to their closest ASCII equivalents in the future
-		{name: "allow weird unicode letter characters", in: "𝓸𝓵𝓵𝓪𝓶𝓪", want: "𝓸𝓵𝓵𝓪𝓶𝓪"},
-		// names that look like words but are invalid (i.e., not ID_Start/ID_Continue)
-		{name: "disallow non-word characters that look like words", in: "ⓞⓛⓛⓐⓜⓐ123", want: "_123"},
-	}
-
-	for i, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			parser := NewFunctionNameMap()
-			got := parser.convertToValidChars(tt.in)
-			if got != tt.want {
-				t.Errorf("case %d: got %q, want %q", i, got, tt.want)
-			}
-		})
-	}
-}
-
-func TestFunctionConvertAndAdd(t *testing.T) {
-	// make a fresh map for each test, but within a test use the same map so we can test for dupe handling
-	tests := []struct {
-		name string
-		in   []string
-		want []string
-	}{
-		{name: "basic dupe handling", in: []string{"get weather", "get weather"}, want: []string{"get_weather", "get_weather_2"}},
-		{name: "dupes from different user-specified names", in: []string{"get weather", "get_weather", "get-weather"}, want: []string{"get_weather", "get_weather_2", "get_weather_3"}},
-		{name: "non dupes after dupes", in: []string{"get weather", "get_weather", "get-weather", "something-different"}, want: []string{"get_weather", "get_weather_2", "get_weather_3", "something_different"}},
-		{name: "multiple sets of dupes", in: []string{"a", "a", "b", "a", "a", "b", "a"}, want: []string{"a", "a_2", "b", "a_3", "a_4", "b_2", "a_5"}},
-		{name: "built-in functions should not be renamed", in: []string{"browser.open", "python", "not.a.built-in.function", "browser.not_a_real_built_in"}, want: []string{"browser.open", "python", "not_a_built_in_function", "browser_not_a_real_built_in"}},
-	}
-
-	for i, tt := range tests {
-		parser := NewFunctionNameMap()
-		t.Run(tt.name, func(t *testing.T) {
-			for j, in := range tt.in {
-				got := parser.ConvertAndAdd(in)
-				want := tt.want[j]
-				if got != want {
-					t.Errorf("case %d: got %q, want %q", i, got, want)
-				}
-				// check that the maps are correct
-				if parser.userToHarmony[in] != want {
-					t.Errorf("case %d: userToHarmony[%q] = %q, want %q", i, in, parser.userToHarmony[in], want)
-				}
-				if parser.harmonyToUser[want] != in {
-					t.Errorf("case %d: harmonyToUser[%q] = %q, want %q", i, want, parser.harmonyToUser[want], in)
-				}
-			}
-		})
-	}
-}
--- a/integration/README.md
+++ b/integration/README.md
@@ -2,16 +2,10 @@

 This directory contains integration tests to exercise Ollama end-to-end to verify behavior

-By default, these tests are disabled so `go test ./...` will exercise only unit tests.  To run integration tests you must pass the integration tag.  `go test -tags=integration ./...` Some tests require additional tags to enable to allow scoped testing to keep the duration reasonable.  For example, testing a broad set of models requires `-tags=integration,models` and a longer timeout (~60m or more depending on the speed of your GPU.). To view the current set of tag combinations use `find integration -type f | xargs grep "go:build"`
+By default, these tests are disabled so `go test ./...` will exercise only unit tests.  To run integration tests you must pass the integration tag.  `go test -tags=integration ./...`


 The integration tests have 2 modes of operating.

 1. By default, they will start the server on a random port, run the tests, and then shutdown the server.
-2. If `OLLAMA_TEST_EXISTING` is set to a non-empty string, the tests will run against an existing running server, which can be remote based on your `OLLAMA_HOST` environment variable
-
-> [!IMPORTANT]
-> Before running the tests locally without the "test existing" setting, compile ollama from the top of the source tree  `go build .` in addition to GPU support with cmake if applicable on your platform.  The integration tests expect to find an ollama binary at the top of the tree.
-
-
-Many tests use a default small model suitable to run on many systems.  You can override this default model by setting `OLLAMA_TEST_DEFAULT_MODEL`
+2. If `OLLAMA_TEST_EXISTING` is set to a non-empty string, the tests will run against an existing running server, which can be remote
--- a/integration/api_test.go
+++ b/integration/api_test.go
@@ -22,12 +22,13 @@ func TestAPIGenerate(t *testing.T) {
 	// Set up the test data
 	req := api.GenerateRequest{
 		Model:  smol,
-		Prompt: blueSkyPrompt,
+		Prompt: "why is the sky blue? be brief",
 		Options: map[string]interface{}{
 			"temperature": 0,
 			"seed":        123,
 		},
 	}
+	anyResp := []string{"rayleigh", "scattering"}

 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
@@ -119,14 +120,14 @@ func TestAPIGenerate(t *testing.T) {
 				// Verify the response contains the expected data
 				response := buf.String()
 				atLeastOne := false
-				for _, resp := range blueSkyExpected {
+				for _, resp := range anyResp {
 					if strings.Contains(strings.ToLower(response), resp) {
 						atLeastOne = true
 						break
 					}
 				}
 				if !atLeastOne {
-					t.Errorf("none of %v found in %s", blueSkyExpected, response)
+					t.Errorf("none of %v found in %s", anyResp, response)
 				}
 			case <-ctx.Done():
 				t.Error("outer test context done while waiting for generate")
@@ -180,7 +181,7 @@ func TestAPIChat(t *testing.T) {
 		Messages: []api.Message{
 			{
 				Role:    "user",
-				Content: blueSkyPrompt,
+				Content: "why is the sky blue?  be brief",
 			},
 		},
 		Options: map[string]interface{}{
@@ -188,6 +189,7 @@ func TestAPIChat(t *testing.T) {
 			"seed":        123,
 		},
 	}
+	anyResp := []string{"rayleigh", "scattering"}

 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
@@ -277,14 +279,14 @@ func TestAPIChat(t *testing.T) {
 				// Verify the response contains the expected data
 				response := buf.String()
 				atLeastOne := false
-				for _, resp := range blueSkyExpected {
+				for _, resp := range anyResp {
 					if strings.Contains(strings.ToLower(response), resp) {
 						atLeastOne = true
 						break
 					}
 				}
 				if !atLeastOne {
-					t.Errorf("none of %v found in %s", blueSkyExpected, response)
+					t.Errorf("none of %v found in %s", anyResp, response)
 				}
 			case <-ctx.Done():
 				t.Error("outer test context done while waiting for chat")
@@ -388,7 +390,7 @@ func TestAPIEmbeddings(t *testing.T) {
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
 	req := api.EmbeddingRequest{
-		Model:  libraryEmbedModels[0],
+		Model:  "orca-mini",
 		Prompt: "why is the sky blue?",
 		Options: map[string]interface{}{
 			"temperature": 0,
@@ -408,99 +410,3 @@ func TestAPIEmbeddings(t *testing.T) {
 		t.Errorf("zero length embedding response")
 	}
 }
-
-func TestAPIToolCalling(t *testing.T) {
-	initialTimeout := 60 * time.Second
-	streamTimeout := 30 * time.Second
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	modelName := "qwen3:0.6b"
-	if err := PullIfMissing(ctx, client, modelName); err != nil {
-		t.Fatalf("pull failed %s", err)
-	}
-
-	tools := []api.Tool{
-		{
-			Type: "function",
-			Function: api.ToolFunction{
-				Name:        "get_weather",
-				Description: "Get the current weather in a given location",
-				Parameters: api.ToolFunctionParameters{
-					Type:     "object",
-					Required: []string{"location"},
-					Properties: map[string]api.ToolProperty{
-						"location": {
-							Type:        api.PropertyType{"string"},
-							Description: "The city and state, e.g. San Francisco, CA",
-						},
-					},
-				},
-			},
-		},
-	}
-
-	req := api.ChatRequest{
-		Model: modelName,
-		Messages: []api.Message{
-			{
-				Role:    "user",
-				Content: "Call get_weather with location set to San Francisco.",
-			},
-		},
-		Tools: tools,
-		Options: map[string]any{
-			"temperature": 0,
-		},
-	}
-
-	stallTimer := time.NewTimer(initialTimeout)
-	var gotToolCall bool
-	var lastToolCall api.ToolCall
-
-	fn := func(response api.ChatResponse) error {
-		if len(response.Message.ToolCalls) > 0 {
-			gotToolCall = true
-			lastToolCall = response.Message.ToolCalls[len(response.Message.ToolCalls)-1]
-		}
-		if !stallTimer.Reset(streamTimeout) {
-			return fmt.Errorf("stall was detected while streaming response, aborting")
-		}
-		return nil
-	}
-
-	stream := true
-	req.Stream = &stream
-	done := make(chan int)
-	var genErr error
-	go func() {
-		genErr = client.Chat(ctx, &req, fn)
-		done <- 0
-	}()
-
-	select {
-	case <-stallTimer.C:
-		t.Errorf("tool-calling chat never started. Timed out after: %s", initialTimeout.String())
-	case <-done:
-		if genErr != nil {
-			t.Fatalf("chat failed: %v", genErr)
-		}
-
-		if !gotToolCall {
-			t.Fatalf("expected at least one tool call, got none")
-		}
-
-		if lastToolCall.Function.Name != "get_weather" {
-			t.Errorf("unexpected tool called: got %q want %q", lastToolCall.Function.Name, "get_weather")
-		}
-
-		if _, ok := lastToolCall.Function.Arguments["location"]; !ok {
-			t.Errorf("expected tool arguments to include 'location', got: %s", lastToolCall.Function.Arguments.String())
-		}
-	case <-ctx.Done():
-		t.Error("outer test context done while waiting for tool-calling chat")
-	}
-}
--- a/integration/basic_test.go
+++ b/integration/basic_test.go
@@ -11,6 +11,7 @@ import (
 	"time"

 	"github.com/ollama/ollama/api"
+	"github.com/stretchr/testify/require"
 )

 func TestBlueSky(t *testing.T) {
@@ -19,14 +20,14 @@ func TestBlueSky(t *testing.T) {
 	// Set up the test data
 	req := api.GenerateRequest{
 		Model:  smol,
-		Prompt: blueSkyPrompt,
+		Prompt: "why is the sky blue?",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
 	}
-	GenerateTestHelper(ctx, t, req, blueSkyExpected)
+	GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
 }

 func TestUnicode(t *testing.T) {
@@ -36,8 +37,8 @@ func TestUnicode(t *testing.T) {
 	// Set up the test data
 	req := api.GenerateRequest{
 		// DeepSeek has a Unicode tokenizer regex, making it a unicode torture test
-		Model:  "deepseek-coder-v2:16b-lite-instruct-q2_K", // TODO is there an ollama-engine model we can switch to and keep the coverage?
-		Prompt: "天空为什么是蓝色的?",                               // Why is the sky blue?
+		Model:  "deepseek-coder-v2:16b-lite-instruct-q2_K",
+		Prompt: "天空为什么是蓝色的?",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,
@@ -49,20 +50,8 @@ func TestUnicode(t *testing.T) {
 	}
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
-	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatal(err)
-	}
-	slog.Info("loading", "model", req.Model)
-	err := client.Generate(ctx, &api.GenerateRequest{Model: req.Model}, func(response api.GenerateResponse) error { return nil })
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", req.Model, err)
-	}
-	skipIfNotGPULoaded(ctx, t, client, req.Model, 100)
-
-	DoGenerate(ctx, t, client, req, []string{
-		"散射", // scattering
-		"频率", // frequency
-	}, 120*time.Second, 120*time.Second)
+	require.NoError(t, PullIfMissing(ctx, client, req.Model))
+	DoGenerate(ctx, t, client, req, []string{"散射", "频率"}, 120*time.Second, 120*time.Second)
 }

 func TestExtendedUnicodeOutput(t *testing.T) {
@@ -80,9 +69,7 @@ func TestExtendedUnicodeOutput(t *testing.T) {
 	}
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
-	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatal(err)
-	}
+	require.NoError(t, PullIfMissing(ctx, client, req.Model))
 	DoGenerate(ctx, t, client, req, []string{"😀", "😊", "😁", "😂", "😄", "😃"}, 120*time.Second, 120*time.Second)
 }

@@ -97,9 +84,7 @@ func TestUnicodeModelDir(t *testing.T) {
 	}

 	modelDir, err := os.MkdirTemp("", "ollama_埃")
-	if err != nil {
-		t.Fatal(err)
-	}
+	require.NoError(t, err)
 	defer os.RemoveAll(modelDir)
 	slog.Info("unicode", "OLLAMA_MODELS", modelDir)

@@ -110,12 +95,12 @@ func TestUnicodeModelDir(t *testing.T) {

 	req := api.GenerateRequest{
 		Model:  smol,
-		Prompt: blueSkyPrompt,
+		Prompt: "why is the sky blue?",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
 	}
-	GenerateTestHelper(ctx, t, req, blueSkyExpected)
+	GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
 }
--- a/integration/concurrency_test.go
+++ b/integration/concurrency_test.go
@@ -4,184 +4,257 @@ package integration

 import (
 	"context"
-	"fmt"
 	"log/slog"
-	"math"
-	"math/rand"
 	"os"
 	"strconv"
 	"sync"
 	"testing"
 	"time"

+	"github.com/stretchr/testify/require"
+
 	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 )

-// Send multiple requests in parallel (concurrently) to a single model and ensure responses are expected
-func TestConcurrentGenerate(t *testing.T) {
-	// Assumes all requests have the same model
-	req, resp := GenerateRequests()
-	numParallel := int(envconfig.NumParallel() + 1)
-	iterLimit := 3
+func TestMultiModelConcurrency(t *testing.T) {
+	var (
+		req = [2]api.GenerateRequest{
+			{
+				Model:     "llama3.2:1b",
+				Prompt:    "why is the ocean blue?",
+				Stream:    &stream,
+				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Options: map[string]any{
+					"seed":        42,
+					"temperature": 0.0,
+				},
+			}, {
+				Model:     "tinydolphin",
+				Prompt:    "what is the origin of the us thanksgiving holiday?",
+				Stream:    &stream,
+				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Options: map[string]any{
+					"seed":        42,
+					"temperature": 0.0,
+				},
+			},
+		}
+		resp = [2][]string{
+			{"sunlight"},
+			{"england", "english", "massachusetts", "pilgrims", "british", "festival"},
+		}
+	)
+	var wg sync.WaitGroup
+	wg.Add(len(req))
+	ctx, cancel := context.WithTimeout(context.Background(), time.Second*240)
+	defer cancel()

-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	for i := 0; i < len(req); i++ {
+		require.NoError(t, PullIfMissing(ctx, client, req[i].Model))
+	}
+
+	for i := 0; i < len(req); i++ {
+		go func(i int) {
+			defer wg.Done()
+			// Note: CPU based inference can crawl so don't give up too quickly
+			DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 30*time.Second)
+		}(i)
+	}
+	wg.Wait()
+}
+
+func TestIntegrationConcurrentPredict(t *testing.T) {
+	req, resp := GenerateRequests()
+	reqLimit := len(req)
+	iterLimit := 5
+
+	if s := os.Getenv("OLLAMA_MAX_VRAM"); s != "" {
+		maxVram, err := strconv.ParseUint(s, 10, 64)
+		require.NoError(t, err)
+		// Don't hammer on small VRAM cards...
+		if maxVram < 4*format.GibiByte {
+			reqLimit = min(reqLimit, 2)
+			iterLimit = 2
+		}
+	}
+
+	ctx, cancel := context.WithTimeout(context.Background(), 9*time.Minute)
 	defer cancel()
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()

 	// Get the server running (if applicable) warm the model up with a single initial request
-	slog.Info("loading", "model", req[0].Model)
-	err := client.Generate(ctx,
-		&api.GenerateRequest{Model: req[0].Model, KeepAlive: &api.Duration{Duration: 10 * time.Second}},
-		func(response api.GenerateResponse) error { return nil },
-	)
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", req[0].Model, err)
-	}
+	DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 10*time.Second)

 	var wg sync.WaitGroup
-	r := rand.New(rand.NewSource(0))
-	wg.Add(numParallel)
-	for i := range numParallel {
+	wg.Add(reqLimit)
+	for i := 0; i < reqLimit; i++ {
 		go func(i int) {
 			defer wg.Done()
 			for j := 0; j < iterLimit; j++ {
-				if time.Now().Sub(started) > softTimeout {
-					slog.Info("exceeded soft timeout, winding down test")
-					return
-				}
-				k := r.Int() % len(req)
-				slog.Info("Starting", "thread", i, "iter", j)
+				slog.Info("Starting", "req", i, "iter", j)
 				// On slower GPUs it can take a while to process the concurrent requests
 				// so we allow a much longer initial timeout
-				DoGenerate(ctx, t, client, req[k], resp[k], 120*time.Second, 20*time.Second)
+				DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 20*time.Second)
 			}
 		}(i)
 	}
 	wg.Wait()
 }

-// Stress the scheduler and attempt to load more models than will fit to cause thrashing
-// This test will always load at least 2 models even on CPU based systems
+// Stress the system if we know how much VRAM it has, and attempt to load more models than will fit
 func TestMultiModelStress(t *testing.T) {
-	s := os.Getenv("OLLAMA_MAX_VRAM")
+	s := os.Getenv("OLLAMA_MAX_VRAM") // TODO - discover actual VRAM
 	if s == "" {
-		s = "0"
+		t.Skip("OLLAMA_MAX_VRAM not specified, can't pick the right models for the stress test")
 	}

 	maxVram, err := strconv.ParseUint(s, 10, 64)
 	if err != nil {
 		t.Fatal(err)
 	}
-
-	// All models compatible with ollama-engine
-	smallModels := []string{
-		"llama3.2:1b",
-		"qwen3:0.6b",
-		"gemma2:2b",
-		"deepseek-r1:1.5b", // qwen2 arch
-		"gemma3:270m",
-	}
-	mediumModels := []string{
-		"llama3.2:3b",    // ~3.4G
-		"qwen3:8b",       // ~6.6G
-		"gpt-oss:20b",    // ~15G
-		"deepseek-r1:7b", // ~5.6G
-		"gemma3:4b",      // ~5.8G
-		"gemma2:9b",      // ~8.1G
+	if maxVram < 2*format.GibiByte {
+		t.Skip("VRAM less than 2G, skipping model stress tests")
 	}

-	var chosenModels []string
+	type model struct {
+		name string
+		size uint64 // Approximate amount of VRAM they typically use when fully loaded in VRAM
+	}
+
+	smallModels := []model{
+		{
+			name: "llama3.2:1b",
+			size: 2876 * format.MebiByte,
+		},
+		{
+			name: "phi",
+			size: 2616 * format.MebiByte,
+		},
+		{
+			name: "gemma:2b",
+			size: 2364 * format.MebiByte,
+		},
+		{
+			name: "stable-code:3b",
+			size: 2608 * format.MebiByte,
+		},
+		{
+			name: "starcoder2:3b",
+			size: 2166 * format.MebiByte,
+		},
+	}
+	mediumModels := []model{
+		{
+			name: "llama2",
+			size: 5118 * format.MebiByte,
+		},
+		{
+			name: "mistral",
+			size: 4620 * format.MebiByte,
+		},
+		{
+			name: "orca-mini:7b",
+			size: 5118 * format.MebiByte,
+		},
+		{
+			name: "dolphin-mistral",
+			size: 4620 * format.MebiByte,
+		},
+		{
+			name: "gemma:7b",
+			size: 5000 * format.MebiByte,
+		},
+		{
+			name: "codellama:7b",
+			size: 5118 * format.MebiByte,
+		},
+	}
+
+	// These seem to be too slow to be useful...
+	// largeModels := []model{
+	// 	{
+	// 		name: "llama2:13b",
+	// 		size: 7400 * format.MebiByte,
+	// 	},
+	// 	{
+	// 		name: "codellama:13b",
+	// 		size: 7400 * format.MebiByte,
+	// 	},
+	// 	{
+	// 		name: "orca-mini:13b",
+	// 		size: 7400 * format.MebiByte,
+	// 	},
+	// 	{
+	// 		name: "gemma:7b",
+	// 		size: 5000 * format.MebiByte,
+	// 	},
+	// 	{
+	// 		name: "starcoder2:15b",
+	// 		size: 9100 * format.MebiByte,
+	// 	},
+	// }
+
+	var chosenModels []model
 	switch {
 	case maxVram < 10000*format.MebiByte:
 		slog.Info("selecting small models")
 		chosenModels = smallModels
+	// case maxVram < 30000*format.MebiByte:
 	default:
 		slog.Info("selecting medium models")
 		chosenModels = mediumModels
+		// default:
+		// 	slog.Info("selecting large models")
+		// 	chosenModels = largeModels
 	}

-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
+	req, resp := GenerateRequests()
+
+	for i := range req {
+		if i > len(chosenModels) {
+			break
+		}
+		req[i].Model = chosenModels[i].name
+	}
+
+	ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute) // TODO baseline -- 10m too short
 	defer cancel()
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()

 	// Make sure all the models are pulled before we get started
-	for _, model := range chosenModels {
-		if err := PullIfMissing(ctx, client, model); err != nil {
-			t.Fatal(err)
-		}
+	for _, r := range req {
+		require.NoError(t, PullIfMissing(ctx, client, r.Model))
 	}

-	// Determine how many models we can load in parallel before we exceed VRAM
-	// The intent is to go 1 over what can fit so we force the scheduler to thrash
-	targetLoadCount := 0
-	slog.Info("Loading models to find how many can fit in VRAM before overflowing")
-chooseModels:
-	for i, model := range chosenModels {
-		req := &api.GenerateRequest{Model: model}
-		slog.Info("loading", "model", model)
-		err = client.Generate(ctx, req, func(response api.GenerateResponse) error { return nil })
-		if err != nil {
-			t.Fatalf("failed to load model %s: %s", model, err)
-		}
-		targetLoadCount++
-		if i > 0 {
-			models, err := client.ListRunning(ctx)
-			if err != nil {
-				t.Fatalf("failed to list running models: %s", err)
-			}
-			if len(models.Models) < targetLoadCount {
-				loaded := []string{}
-				for _, m := range models.Models {
-					loaded = append(loaded, m.Name)
-				}
-				slog.Info("found model load capacity", "target", targetLoadCount, "current", loaded, "chosen", chosenModels[:targetLoadCount])
-				break
-			}
-			// Effectively limit model count to 2 on CPU only systems to avoid thrashing and timeouts
-			for _, m := range models.Models {
-				if m.SizeVRAM == 0 {
-					slog.Info("model running on CPU", "name", m.Name, "target", targetLoadCount, "chosen", chosenModels[:targetLoadCount])
-					break chooseModels
-				}
-			}
-		}
-	}
-	if targetLoadCount == len(chosenModels) {
-		// TODO consider retrying the medium models
-		slog.Warn("all models being used without exceeding VRAM, set OLLAMA_MAX_VRAM so test can pick larger models")
-	}
-
-	r := rand.New(rand.NewSource(0))
 	var wg sync.WaitGroup
-	for i := range targetLoadCount {
+	consumed := uint64(256 * format.MebiByte) // Assume some baseline usage
+	for i := 0; i < len(req); i++ {
+		// Always get at least 2 models, but don't overshoot VRAM too much or we'll take too long
+		if i > 1 && consumed > maxVram {
+			slog.Info("achieved target vram exhaustion", "count", i, "vram", format.HumanBytes2(maxVram), "models", format.HumanBytes2(consumed))
+			break
+		}
+		consumed += chosenModels[i].size
+		slog.Info("target vram", "count", i, "vram", format.HumanBytes2(maxVram), "models", format.HumanBytes2(consumed))
+
 		wg.Add(1)
 		go func(i int) {
 			defer wg.Done()
-			reqs, resps := GenerateRequests()
 			for j := 0; j < 3; j++ {
-				if time.Now().Sub(started) > softTimeout {
-					slog.Info("exceeded soft timeout, winding down test")
-					return
-				}
-				k := r.Int() % len(reqs)
-				reqs[k].Model = chosenModels[i]
-				slog.Info("Starting", "model", reqs[k].Model, "iteration", j, "request", reqs[k].Prompt)
-				DoGenerate(ctx, t, client, reqs[k], resps[k],
-					120*time.Second, // Be extra patient for the model to load initially
-					10*time.Second,  // Once results start streaming, fail if they stall
-				)
+				slog.Info("Starting", "req", i, "iter", j, "model", req[i].Model)
+				DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 5*time.Second)
 			}
 		}(i)
 	}
 	go func() {
 		for {
-			time.Sleep(10 * time.Second)
+			time.Sleep(2 * time.Second)
 			select {
 			case <-ctx.Done():
 				return
@@ -192,21 +265,7 @@ chooseModels:
 					continue
 				}
 				for _, m := range models.Models {
-					var procStr string
-					switch {
-					case m.SizeVRAM == 0:
-						procStr = "100% CPU"
-					case m.SizeVRAM == m.Size:
-						procStr = "100% GPU"
-					case m.SizeVRAM > m.Size || m.Size == 0:
-						procStr = "Unknown"
-					default:
-						sizeCPU := m.Size - m.SizeVRAM
-						cpuPercent := math.Round(float64(sizeCPU) / float64(m.Size) * 100)
-						procStr = fmt.Sprintf("%d%%/%d%%", int(cpuPercent), int(100-cpuPercent))
-					}
-
-					slog.Info("loaded model snapshot", "model", m.Name, "CPU/GPU", procStr, "expires", format.HumanTime(m.ExpiresAt, "Never"))
+					slog.Info("loaded model snapshot", "model", m)
 				}
 			}
 		}
--- a/integration/context_test.go
+++ b/integration/context_test.go
@@ -4,8 +4,6 @@ package integration

 import (
 	"context"
-	"log/slog"
-	"sync"
 	"testing"
 	"time"

@@ -22,7 +20,7 @@ func TestLongInputContext(t *testing.T) {
 	defer cancel()
 	// Set up the test data
 	req := api.GenerateRequest{
-		Model:  smol,
+		Model:  "llama2",
 		Prompt: "Oh, don’t speak to me of Austria. Perhaps I don’t understand things, but Austria never has wished, and does not wish, for war. She is betraying us! Russia alone must save Europe. Our gracious sovereign recognizes his high vocation and will be true to it. That is the one thing I have faith in! Our good and wonderful sovereign has to perform the noblest role on earth, and he is so virtuous and noble that God will not forsake him. He will fulfill his vocation and crush the hydra of revolution, which has become more terrible than ever in the person of this murderer and villain! We alone must avenge the blood of the just one.... Whom, I ask you, can we rely on?... England with her commercial spirit will not and cannot understand the Emperor Alexander’s loftiness of soul. She has refused to evacuate Malta. She wanted to find, and still seeks, some secret motive in our actions. What answer did Novosíltsev get? None. The English have not understood and cannot understand the self-abnegation of our Emperor who wants nothing for himself, but only desires the good of mankind. And what have they promised? Nothing! And what little they have promised they will not perform! Prussia has always declared that Buonaparte is invincible, and that all Europe is powerless before him.... And I don’t believe a word that Hardenburg says, or Haugwitz either. This famous Prussian neutrality is just a trap. I have faith only in God and the lofty destiny of our adored monarch. He will save Europe! What country is this referring to?",
 		Stream: &stream,
 		Options: map[string]any{
@@ -36,7 +34,7 @@ func TestLongInputContext(t *testing.T) {
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
 		t.Fatalf("PullIfMissing failed: %v", err)
 	}
-	DoGenerate(ctx, t, client, req, []string{"russia", "germany", "france", "england", "austria", "prussia", "europe", "individuals", "coalition", "conflict"}, 120*time.Second, 10*time.Second)
+	DoGenerate(ctx, t, client, req, []string{"russia", "germany", "france", "england", "austria", "prussia"}, 120*time.Second, 10*time.Second)
 }

 func TestContextExhaustion(t *testing.T) {
@@ -49,8 +47,8 @@ func TestContextExhaustion(t *testing.T) {
 	defer cancel()
 	// Set up the test data
 	req := api.GenerateRequest{
-		Model:  smol,
-		Prompt: "Write me a story in english with a lot of emojis",
+		Model:  "llama2",
+		Prompt: "Write me a story with a ton of emojis?",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,
@@ -63,196 +61,5 @@ func TestContextExhaustion(t *testing.T) {
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
 		t.Fatalf("PullIfMissing failed: %v", err)
 	}
-	DoGenerate(ctx, t, client, req, []string{"once", "upon", "lived", "sunny", "cloudy", "clear", "water", "time", "travel", "world"}, 120*time.Second, 10*time.Second)
-}
-
-// Send multiple generate requests with prior context and ensure the response is coherant and expected
-func TestParallelGenerateWithHistory(t *testing.T) {
-	modelOverride := ollamaEngineChatModels[0] // Most recent ollama engine model
-	req, resp := GenerateRequests()
-	numParallel := 2
-	iterLimit := 2
-
-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
-	defer cancel()
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	// Get the server running (if applicable) warm the model up with a single initial request
-	slog.Info("loading", "model", modelOverride)
-	err := client.Generate(ctx,
-		&api.GenerateRequest{Model: modelOverride, KeepAlive: &api.Duration{Duration: 10 * time.Second}},
-		func(response api.GenerateResponse) error { return nil },
-	)
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", modelOverride, err)
-	}
-
-	var wg sync.WaitGroup
-	wg.Add(numParallel)
-	for i := range numParallel {
-		go func(i int) {
-			defer wg.Done()
-			k := i % len(req)
-			req[k].Model = modelOverride
-			for j := 0; j < iterLimit; j++ {
-				if time.Now().Sub(started) > softTimeout {
-					slog.Info("exceeded soft timeout, winding down test")
-					return
-				}
-				slog.Info("Starting", "thread", i, "iter", j)
-				// On slower GPUs it can take a while to process the concurrent requests
-				// so we allow a much longer initial timeout
-				c := DoGenerate(ctx, t, client, req[k], resp[k], 120*time.Second, 20*time.Second)
-				req[k].Context = c
-				req[k].Prompt = "tell me more!"
-			}
-		}(i)
-	}
-	wg.Wait()
-}
-
-// Send generate requests with prior context and ensure the response is coherant and expected
-func TestGenerateWithHistory(t *testing.T) {
-	req := api.GenerateRequest{
-		Model:     smol,
-		Prompt:    rainbowPrompt,
-		Stream:    &stream,
-		KeepAlive: &api.Duration{Duration: 10 * time.Second},
-		Options: map[string]any{
-			"num_ctx": 16384,
-		},
-	}
-
-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
-	defer cancel()
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	// Get the server running (if applicable) warm the model up with a single initial request
-	slog.Info("loading", "model", req.Model)
-	err := client.Generate(ctx,
-		&api.GenerateRequest{Model: req.Model, KeepAlive: &api.Duration{Duration: 10 * time.Second}, Options: req.Options},
-		func(response api.GenerateResponse) error { return nil },
-	)
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", req.Model, err)
-	}
-
-	req.Context = DoGenerate(ctx, t, client, req, rainbowExpected, 30*time.Second, 20*time.Second)
-
-	for i := 0; i < len(rainbowFollowups); i++ {
-		req.Prompt = rainbowFollowups[i]
-		if time.Now().Sub(started) > softTimeout {
-			slog.Info("exceeded soft timeout, winding down test")
-			return
-		}
-		req.Context = DoGenerate(ctx, t, client, req, rainbowExpected, 30*time.Second, 20*time.Second)
-	}
-}
-
-// Send multiple chat requests with prior context and ensure the response is coherant and expected
-func TestParallelChatWithHistory(t *testing.T) {
-	modelOverride := ollamaEngineChatModels[0] // Most recent ollama engine model
-	req, resp := ChatRequests()
-	numParallel := 2
-	iterLimit := 2
-
-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
-	defer cancel()
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	// Get the server running (if applicable) warm the model up with a single initial empty request
-	slog.Info("loading", "model", modelOverride)
-	err := client.Generate(ctx,
-		&api.GenerateRequest{Model: modelOverride, KeepAlive: &api.Duration{Duration: 10 * time.Second}},
-		func(response api.GenerateResponse) error { return nil },
-	)
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", modelOverride, err)
-	}
-
-	var wg sync.WaitGroup
-	wg.Add(numParallel)
-	for i := range numParallel {
-		go func(i int) {
-			defer wg.Done()
-			k := i % len(req)
-			req[k].Model = modelOverride
-			for j := 0; j < iterLimit; j++ {
-				if time.Now().Sub(started) > softTimeout {
-					slog.Info("exceeded soft timeout, winding down test")
-					return
-				}
-				slog.Info("Starting", "thread", i, "iter", j)
-				// On slower GPUs it can take a while to process the concurrent requests
-				// so we allow a much longer initial timeout
-				assistant := DoChat(ctx, t, client, req[k], resp[k], 120*time.Second, 20*time.Second)
-				if assistant == nil {
-					t.Fatalf("didn't get an assistant response for context")
-				}
-				req[k].Messages = append(req[k].Messages,
-					*assistant,
-					api.Message{Role: "user", Content: "tell me more!"},
-				)
-			}
-		}(i)
-	}
-	wg.Wait()
-}
-
-// Send generate requests with prior context and ensure the response is coherant and expected
-func TestChatWithHistory(t *testing.T) {
-	req := api.ChatRequest{
-		Model:     smol,
-		Stream:    &stream,
-		KeepAlive: &api.Duration{Duration: 10 * time.Second},
-		Options: map[string]any{
-			"num_ctx": 16384,
-		},
-		Messages: []api.Message{
-			{
-				Role:    "user",
-				Content: rainbowPrompt,
-			},
-		},
-	}
-
-	softTimeout, hardTimeout := getTimeouts(t)
-	ctx, cancel := context.WithTimeout(context.Background(), hardTimeout)
-	defer cancel()
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	// Get the server running (if applicable) warm the model up with a single initial request
-	slog.Info("loading", "model", req.Model)
-	err := client.Generate(ctx,
-		&api.GenerateRequest{Model: req.Model, KeepAlive: &api.Duration{Duration: 10 * time.Second}, Options: req.Options},
-		func(response api.GenerateResponse) error { return nil },
-	)
-	if err != nil {
-		t.Fatalf("failed to load model %s: %s", req.Model, err)
-	}
-
-	assistant := DoChat(ctx, t, client, req, rainbowExpected, 30*time.Second, 20*time.Second)
-
-	for i := 0; i < len(rainbowFollowups); i++ {
-		if time.Now().Sub(started) > softTimeout {
-			slog.Info("exceeded soft timeout, winding down test")
-			return
-		}
-		req.Messages = append(req.Messages,
-			*assistant,
-			api.Message{Role: "user", Content: rainbowFollowups[i]},
-		)
-
-		assistant = DoChat(ctx, t, client, req, rainbowExpected, 30*time.Second, 20*time.Second)
-		if assistant == nil {
-			t.Fatalf("didn't get an assistant response for context")
-		}
-	}
+	DoGenerate(ctx, t, client, req, []string{"once", "upon", "lived"}, 120*time.Second, 10*time.Second)
 }
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
ParthSareen	23e8ac9428	wip?	2025-05-07 19:00:44 -07:00
ParthSareen	611d3a17ed	server: add python tool parsing logic	2025-05-02 16:23:54 -07:00