server: serve original error for remote models

parsers: fix `&`s in qwen3coder parameter values

.github/workflows/release.yaml

@@ -65,14 +65,36 @@ jobs:
             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'
+          - 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'
           - 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:
@@ -96,7 +118,7 @@ jobs:
           $ErrorActionPreference = "Stop"
           if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
             Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
+            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
             Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
           }
 
@@ -138,7 +160,7 @@ jobs:
         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 }}" ${{ matrix.flags }}
+          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }} -DOLLAMA_RUNNER_DIR="${{ matrix.runner_dir }}"
           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:
@@ -232,7 +254,7 @@ jobs:
             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_sbsa)      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 ;;

.github/workflows/test.yaml

@@ -46,7 +46,7 @@ jobs:
         include:
           - preset: CPU
           - preset: CUDA
-            container: nvidia/cuda:12.8.1-devel-ubuntu22.04
+            container: nvidia/cuda:13.0.0-devel-ubuntu22.04
             flags: '-DCMAKE_CUDA_ARCHITECTURES=87'
           - preset: ROCm
             container: rocm/dev-ubuntu-22.04:6.1.2
@@ -78,8 +78,17 @@ jobs:
         include:
           - preset: CPU
           - preset: CUDA
-            install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
+            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.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"'
@@ -102,7 +111,8 @@ jobs:
           $ErrorActionPreference = "Stop"
           if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
             Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            Start-Process -FilePath .\install.exe -ArgumentList (@("-s", "cudart_12.8", "nvcc_12.8", "cublas_12.8", "cublas_dev_12.8")) -NoNewWindow -Wait
+            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
+            Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
           }
 
           $cudaPath = (Resolve-Path "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*").path

CMakeLists.txt

@@ -38,7 +38,7 @@ 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)
+set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama/${OLLAMA_RUNNER_DIR})
 
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY         ${OLLAMA_BUILD_DIR})
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG   ${OLLAMA_BUILD_DIR})
@@ -81,7 +81,7 @@ if(CMAKE_CUDA_COMPILER)
     add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
     install(TARGETS ggml-cuda
         RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_LIBRARY_DIR}
+            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
             PRE_INCLUDE_REGEXES cublas cublasLt cudart
             PRE_EXCLUDE_REGEXES ".*"
         RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA

CMakePresets.json

@@ -18,6 +18,14 @@
       "name": "CUDA",
       "inherits": [ "Default" ]
     },
+    {
+      "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"
+      }
+    },
     {
       "name": "CUDA 12",
       "inherits": [ "CUDA" ],
@@ -26,6 +34,14 @@
         "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"
+      }
+    },
     {
       "name": "JetPack 5",
       "inherits": [ "CUDA" ],
@@ -72,11 +88,21 @@
       "configurePreset": "CUDA",
       "targets": [ "ggml-cuda" ]
     },
+    {
+      "name": "CUDA 11",
+      "inherits": [ "CUDA" ],
+      "configurePreset": "CUDA 11"
+    },
     {
       "name": "CUDA 12",
       "inherits": [ "CUDA" ],
       "configurePreset": "CUDA 12"
     },
+    {
+      "name": "CUDA 13",
+      "inherits": [ "CUDA" ],
+      "configurePreset": "CUDA 13"
+    },
     {
       "name": "JetPack 5",
       "inherits": [ "CUDA" ],

Dockerfile

@@ -1,6 +1,7 @@
 # vim: filetype=dockerfile
 
 ARG FLAVOR=${TARGETARCH}
+ARG PARALLEL=8
 
 ARG ROCMVERSION=6.3.3
 ARG JETPACK5VERSION=r35.4.1
@@ -34,26 +35,51 @@ 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 --preset 'CPU' \
-        && cmake --install build --component CPU --strip --parallel 8
+        && cmake --build --parallel ${PARALLEL} --preset 'CPU' \
+        && cmake --install build --component CPU --strip --parallel ${PARALLEL}
+
+FROM base AS cuda-11
+ARG CUDA11VERSION=11.8
+RUN dnf install -y cuda-toolkit-${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}
 
 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' \
-        && cmake --build --parallel --preset 'CUDA 12' \
-        && cmake --install build --component CUDA --strip --parallel 8
+    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}
+
 
 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 --preset 'ROCm 6' \
-        && cmake --install build --component HIP --strip --parallel 8
+        && cmake --build --parallel ${PARALLEL} --preset 'ROCm 6' \
+        && cmake --install build --component HIP --strip --parallel ${PARALLEL}
 
 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
 ARG CMAKEVERSION
@@ -61,10 +87,11 @@ RUN apt-get update && apt-get install -y curl ccache \
     && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${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 --preset 'JetPack 5' \
-        && cmake --install build --component CUDA --strip --parallel 8
+        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 5' \
+        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
 
 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
 ARG CMAKEVERSION
@@ -72,10 +99,11 @@ RUN apt-get update && apt-get install -y curl ccache \
     && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${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 --preset 'JetPack 6' \
-        && cmake --install build --component CUDA --strip --parallel 8
+        && cmake --build --parallel ${PARALLEL} --preset 'JetPack 6' \
+        && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
 
 FROM base AS build
 WORKDIR /go/src/github.com/ollama/ollama
@@ -92,10 +120,14 @@ 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-12 dist/lib/ollama /lib/ollama
+# 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/
 
 FROM --platform=linux/arm64 scratch AS arm64
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/cuda_sbsa
+# 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
 

README.md

@@ -413,6 +413,8 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [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
 

api/client.go

@@ -222,7 +222,17 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			return fmt.Errorf("unmarshal: %w", err)
 		}
 
-		if response.StatusCode >= http.StatusBadRequest {
+		if response.StatusCode == http.StatusUnauthorized {
+			pubKey, pkErr := auth.GetPublicKey()
+			if pkErr != nil {
+				return pkErr
+			}
+			return AuthorizationError{
+				StatusCode: response.StatusCode,
+				Status:     response.Status,
+				PublicKey:  pubKey,
+			}
+		} else if response.StatusCode >= http.StatusBadRequest {
 			return StatusError{
 				StatusCode:   response.StatusCode,
 				Status:       response.Status,
@@ -428,3 +438,16 @@ func (c *Client) Version(ctx context.Context) (string, error) {
 
 	return version.Version, nil
 }
+
+// Signout will disconnect an ollama instance from ollama.com
+func (c *Client) Signout(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
+}

api/types.go

@@ -11,6 +11,8 @@ import (
 	"strings"
 	"time"
 
+	"github.com/google/uuid"
+
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/types/model"
 )
@@ -36,6 +38,19 @@ func (e StatusError) Error() string {
 	}
 }
 
+type AuthorizationError struct {
+	StatusCode int
+	Status     string
+	PublicKey  string `json:"public_key"`
+}
+
+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
 
@@ -313,13 +328,29 @@ func (t *ToolFunction) String() string {
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
 // similar to [GenerateResponse].
 type ChatResponse struct {
-	Model      string    `json:"model"`
-	CreatedAt  time.Time `json:"created_at"`
-	Message    Message   `json:"message"`
-	DoneReason string    `json:"done_reason,omitempty"`
+	// 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"`
+
+	// 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
 }
 
@@ -329,13 +360,6 @@ type DebugInfo struct {
 	ImageCount       int    `json:"image_count,omitempty"`
 }
 
-// DebugTemplateResponse is returned when _debug_render_only is set to true
-type DebugTemplateResponse struct {
-	Model     string    `json:"model"`
-	CreatedAt time.Time `json:"created_at"`
-	DebugInfo DebugInfo `json:"_debug_info"`
-}
-
 type Metrics struct {
 	TotalDuration      time.Duration `json:"total_duration,omitempty"`
 	LoadDuration       time.Duration `json:"load_duration,omitempty"`
@@ -388,8 +412,12 @@ 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"`
 }
@@ -427,18 +455,47 @@ type EmbeddingResponse struct {
 
 // CreateRequest is the request passed to [Client.Create].
 type CreateRequest struct {
-	Model    string `json:"model"`
-	Stream   *bool  `json:"stream,omitempty"`
+	// 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.
 	Quantize string `json:"quantize,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"`
+	// 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"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -476,8 +533,12 @@ 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"`
@@ -536,12 +597,14 @@ type ProcessResponse struct {
 
 // ListModelResponse is a single model description in [ListResponse].
 type ListModelResponse struct {
-	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"`
+	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"`
 }
 
 // ProcessModelResponse is a single model description in [ProcessResponse].
@@ -565,6 +628,12 @@ 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"`
 
@@ -588,6 +657,8 @@ type GenerateResponse struct {
 	Metrics
 
 	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
+
+	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
 }
 
 // ModelDetails provides details about a model.
@@ -600,6 +671,18 @@ 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"`

auth/auth.go

@@ -19,6 +19,31 @@ import (
 const defaultPrivateKey = "id_ed25519"
 
 func keyPath() (string, error) {
+	fileIsReadable := func(fp string) bool {
+		info, err := os.Stat(fp)
+		if err != nil {
+			return false
+		}
+
+		// Check that it's a regular file, not a directory or other file type
+		if !info.Mode().IsRegular() {
+			return false
+		}
+
+		// Try to open it to check readability
+		file, err := os.Open(fp)
+		if err != nil {
+			return false
+		}
+		file.Close()
+		return true
+	}
+
+	systemPath := filepath.Join("/usr/share/ollama/.ollama", defaultPrivateKey)
+	if fileIsReadable(systemPath) {
+		return systemPath, nil
+	}
+
 	home, err := os.UserHomeDir()
 	if err != nil {
 		return "", err

cmd/cmd.go

@@ -5,6 +5,7 @@ import (
 	"context"
 	"crypto/ed25519"
 	"crypto/rand"
+	"encoding/base64"
 	"encoding/json"
 	"encoding/pem"
 	"errors"
@@ -14,6 +15,7 @@ import (
 	"math"
 	"net"
 	"net/http"
+	"net/url"
 	"os"
 	"os/signal"
 	"path/filepath"
@@ -35,6 +37,7 @@ import (
 	"golang.org/x/term"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/auth"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/parser"
@@ -47,6 +50,8 @@ import (
 	"github.com/ollama/ollama/version"
 )
 
+const ConnectInstructions = "To sign in, navigate to:\n    https://ollama.com/connect?name=%s&key=%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 == "" {
@@ -56,10 +61,8 @@ func ensureThinkingSupport(ctx context.Context, client *api.Client, name string)
 	if err != nil {
 		return
 	}
-	for _, cap := range resp.Capabilities {
-		if cap == model.CapabilityThinking {
-			return
-		}
+	if slices.Contains(resp.Capabilities, model.CapabilityThinking) {
+		return
 	}
 	fmt.Fprintf(os.Stderr, "warning: model %q does not support thinking output\n", name)
 }
@@ -288,7 +291,17 @@ func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
 		Think: opts.Think,
 	}
 
-	return client.Generate(cmd.Context(), req, func(api.GenerateResponse) error { return nil })
+	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
+	})
 }
 
 func StopHandler(cmd *cobra.Command, args []string) error {
@@ -309,9 +322,10 @@ 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{},
+		Model:       args[0],
+		WordWrap:    os.Getenv("TERM") == "xterm-256color",
+		Options:     map[string]any{},
+		ShowConnect: true,
 	}
 
 	format, err := cmd.Flags().GetString("format")
@@ -369,6 +383,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		}
 
 		prompts = append([]string{string(in)}, prompts...)
+		opts.ShowConnect = false
 		opts.WordWrap = false
 		interactive = false
 	}
@@ -435,6 +450,21 @@ 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 {
+				pubKey, pkErr := auth.GetPublicKey()
+				if pkErr != nil {
+					return pkErr
+				}
+				// the server and the client both have the same public key
+				if pubKey == sErr.PublicKey {
+					h, _ := os.Hostname()
+					encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
+					fmt.Printf("You need to be signed in to Ollama to run Cloud models.\n\n")
+					fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
+				}
+				return nil
+			}
 			return err
 		}
 
@@ -455,6 +485,56 @@ 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 {
+		return err
+	}
+
+	if user != nil && user.Name != "" {
+		fmt.Printf("You are already signed in as user '%s'\n", user.Name)
+		fmt.Println()
+		return nil
+	}
+
+	pubKey, pkErr := auth.GetPublicKey()
+	if pkErr != nil {
+		return pkErr
+	}
+	encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
+
+	h, _ := os.Hostname()
+	fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
+
+	return nil
+}
+
+func SignoutHandler(cmd *cobra.Command, args []string) error {
+	pubKey, pkErr := auth.GetPublicKey()
+	if pkErr != nil {
+		return pkErr
+	}
+	encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
+
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		return err
+	}
+
+	err = client.Signout(cmd.Context(), encKey)
+	if err != nil {
+		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 {
@@ -507,7 +587,8 @@ func PushHandler(cmd *cobra.Command, args []string) error {
 		if spinner != nil {
 			spinner.Stop()
 		}
-		if strings.Contains(err.Error(), "access denied") {
+		errStr := strings.ToLower(err.Error())
+		if strings.Contains(errStr, "access denied") || strings.Contains(errStr, "unauthorized") {
 			return errors.New("you are not authorized to push to this namespace, create the model under a namespace you own")
 		}
 		return err
@@ -541,7 +622,14 @@ 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])) {
-			data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), format.HumanTime(m.ModifiedAt, "Never")})
+			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")})
 		}
 	}
 
@@ -626,8 +714,8 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
 		KeepAlive: &api.Duration{Duration: 0},
 	}
 	if err := loadOrUnloadModel(cmd, opts); err != nil {
-		if !strings.Contains(err.Error(), "not found") {
-			return fmt.Errorf("unable to stop existing running model \"%s\": %s", args[0], err)
+		if !strings.Contains(strings.ToLower(err.Error()), "not found") {
+			fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
 		}
 	}
 
@@ -738,12 +826,36 @@ 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})
-			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)})
+
+			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)})
+				}
+			}
 		} else {
 			rows = append(rows, []string{"", "architecture", resp.Details.Family})
 			rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
@@ -991,6 +1103,7 @@ type runOptions struct {
 	KeepAlive    *api.Duration
 	Think        *api.ThinkValue
 	HideThinking bool
+	ShowConnect  bool
 }
 
 type displayResponseState struct {
@@ -1546,6 +1659,22 @@ 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"},
@@ -1640,6 +1769,8 @@ func NewCLI() *cobra.Command {
 		stopCmd,
 		pullCmd,
 		pushCmd,
+		signinCmd,
+		signoutCmd,
 		listCmd,
 		psCmd,
 		copyCmd,

cmd/cmd_test.go

@@ -3,6 +3,7 @@ package cmd
 import (
 	"bytes"
 	"encoding/json"
+	"fmt"
 	"io"
 	"net/http"
 	"net/http/httptest"
@@ -304,6 +305,8 @@ 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
 		}
@@ -346,7 +349,7 @@ func TestDeleteHandler(t *testing.T) {
 	}
 
 	err := DeleteHandler(cmd, []string{"test-model-not-found"})
-	if err == nil || !strings.Contains(err.Error(), "unable to stop existing running model \"test-model-not-found\"") {
+	if err == nil || !strings.Contains(err.Error(), "model 'test-model-not-found' not found") {
 		t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err)
 	}
 }
@@ -499,7 +502,7 @@ 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": "access denied",
+						"error": "403: {\"errors\":[{\"code\":\"ACCESS DENIED\", \"message\":\"access denied\"}]}",
 					})
 					if err != nil {
 						t.Fatal(err)
@@ -522,6 +525,7 @@ func TestPushHandler(t *testing.T) {
 			defer mockServer.Close()
 
 			t.Setenv("OLLAMA_HOST", mockServer.URL)
+			initializeKeypair()
 
 			cmd := &cobra.Command{}
 			cmd.Flags().Bool("insecure", false, "")

convert/convert_bert.go

@@ -28,6 +28,7 @@ type bertModel struct {
 	LayerNormEPS          float32 `json:"layer_norm_eps"`
 	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
 	NormEpsilon           float32 `json:"norm_epsilon"`
+	normalizeEmbeddings   bool
 
 	PoolingType uint32
 }
@@ -54,9 +55,11 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
 
 	var pooling string
 	for _, m := range modules {
-		if m.Type == "sentence_transformers.models.Pooling" {
+		switch m.Type {
+		case "sentence_transformers.models.Pooling":
 			pooling = m.Path
-			break
+		case "sentence_transformers.models.Normalize":
+			p.normalizeEmbeddings = true
 		}
 	}
 
@@ -90,6 +93,7 @@ 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)
 

convert/reader_safetensors.go

@@ -96,7 +96,7 @@ type safetensor struct {
 
 func (st safetensor) Kind() uint32 {
 	kind := st.tensorBase.Kind()
-	if st.dtype == "BF16" && kind != tensorKindFP32 {
+	if !strings.HasPrefix(st.name, "v.") && st.dtype == "BF16" && kind != tensorKindFP32 {
 		kind = tensorKindBF16
 	}
 

convert/reader_test.go

@@ -230,3 +230,65 @@ func TestSafetensors(t *testing.T) {
 		})
 	}
 }
+
+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)
+			}
+		})
+	}
+}

discover/cuda_common.go

@@ -16,7 +16,7 @@ import (
 // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
 var CudaTegra string = os.Getenv("JETSON_JETPACK")
 
-func cudaVariant(gpuInfo CudaGPUInfo) string {
+func cudaVariant(gpuInfos []CudaGPUInfo) string {
 	if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" {
 		if CudaTegra != "" {
 			ver := strings.Split(CudaTegra, ".")
@@ -43,14 +43,22 @@ func cudaVariant(gpuInfo CudaGPUInfo) string {
 				}
 			}
 		}
-		return "sbsa"
 	}
 
-	// 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) {
-		// The detected driver is older than Feb 2023
-		slog.Warn("old CUDA driver detected - please upgrade to a newer driver", "version", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor))
-		return "v11"
+	// 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"
+		}
 	}
-	return "v12"
+
+	// 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"
 }

discover/gpu.go

@@ -284,18 +284,8 @@ 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,
@@ -333,6 +323,24 @@ 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

docs/api.md

@@ -1708,6 +1708,7 @@ 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
 

docs/development.md

@@ -11,6 +11,10 @@ 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.

docs/linux.md

@@ -11,12 +11,13 @@ curl -fsSL https://ollama.com/install.sh | sh
 ## Manual install
 
 > [!NOTE]
-> If you are upgrading from a prior version, you should remove the old libraries with `sudo rm -rf /usr/lib/ollama` first.
+> If you are upgrading from a prior version, you **MUST** 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
 sudo tar -C /usr -xzf ollama-linux-amd64.tgz
 ```
 

docs/troubleshooting.md

@@ -92,6 +92,9 @@ 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
 

envconfig/config.go

@@ -134,6 +134,17 @@ 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 != "" {
@@ -185,8 +196,6 @@ var (
 	ContextLength = Uint("OLLAMA_CONTEXT_LENGTH", 4096)
 	// Auth enables authentication between the Ollama client and server
 	UseAuth = Bool("OLLAMA_AUTH")
-	// Enable the new memory estimation logic
-	NewMemoryEstimates = Bool("OLLAMA_NEW_ESTIMATES")
 )
 
 func String(s string) func() string {
@@ -272,7 +281,7 @@ func AsMap() map[string]EnvVar {
 		"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_NEW_ENGINE":        {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
-		"OLLAMA_NEW_ESTIMATES":     {"OLLAMA_NEW_ESTIMATES", NewMemoryEstimates(), "Enable the new memory estimation logic"},
+		"OLLAMA_REMOTES":           {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
 
 		// Informational
 		"HTTP_PROXY":  {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

fs/ggml/ggml.go

@@ -57,10 +57,28 @@ 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) HeadCountMax() uint64 {
-	// TODO(drifkin): using the max value can cause an overestimation. In the
-	// future if array values become more popular, we can adapt the more invasive
-	// <https://github.com/ollama/ollama/pull/10225>
 	return uint64(kv.UintOrMaxArrayValue("attention.head_count", 1))
 }
 
@@ -68,6 +86,27 @@ 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))
 }
@@ -100,6 +139,26 @@ 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
@@ -131,22 +190,27 @@ func (kv KV) UintOrMinArrayValue(key string, defaultValue uint32) uint32 {
 }
 
 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 u32, u32
+		return []uint32{u32}
 	} else if u32s, ok := keyValue(kv, key, &array[uint32]{}); ok {
-		min := slices.Min(u32s.values)
-		max := slices.Max(u32s.values)
-		return min, max
+		return u32s.values
 	} else if i32s, ok := keyValue(kv, key, &array[int32]{}); ok {
-		min := slices.Min(i32s.values)
-		max := slices.Max(i32s.values)
-		if min < 0 || max < 0 {
-			slog.Warn("array values are unexpectedly negative", "key", key, "min", min, "max", max)
+		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 uint32(min), uint32(max)
+		return dst
 	}
 
-	return defaultValue, defaultValue
+	return []uint32{defaultValue}
 }
 
 func (kv KV) Strings(key string, defaultValue ...[]string) []string {
@@ -179,6 +243,7 @@ func (kv KV) OllamaEngineRequired() bool {
 		"gemma3",
 		"gemma3n",
 		"mistral3",
+		"qwen3",
 		"llama4",
 		"mllama",
 		"qwen25vl",
@@ -486,7 +551,9 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 
 	embedding := f.KV().EmbeddingLength()
 	heads := f.KV().HeadCountMax()
+	headsArr := f.KV().HeadCount()
 	headsKV := f.KV().HeadCountKVMax()
+	headsKVArr := f.KV().HeadCountKV()
 	vocab := uint64(f.KV()["tokenizer.ggml.tokens"].(*array[string]).size)
 
 	embeddingHeads := f.KV().EmbeddingHeadCountMax()
@@ -496,12 +563,51 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 	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 {
-		kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+		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]
 	}
+	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":
@@ -759,12 +865,16 @@ 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 ", "mode", arch)
-		return cacheType == "f16"
+		slog.Warn("model only supports non-quantized cache types", "model", arch)
+		return false
 	}
-	return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
+	return slices.Contains([]string{"q8_0", "q4_0"}, cacheType)
 }
 
 // SupportsFlashAttention checks if the model supports flash attention
@@ -774,6 +884,10 @@ 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()
@@ -794,6 +908,8 @@ 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)
 	}

integration/api_test.go

@@ -410,3 +410,99 @@ 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")
+	}
+}

integration/concurrency_test.go

@@ -121,6 +121,7 @@ func TestMultiModelStress(t *testing.T) {
 	// 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)
@@ -142,6 +143,13 @@ func TestMultiModelStress(t *testing.T) {
 				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) {

integration/context_test.go

@@ -36,7 +36,7 @@ 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", "individuals", "coalition", "conflict"}, 120*time.Second, 10*time.Second)
+	DoGenerate(ctx, t, client, req, []string{"russia", "germany", "france", "england", "austria", "prussia", "europe", "individuals", "coalition", "conflict"}, 120*time.Second, 10*time.Second)
 }
 
 func TestContextExhaustion(t *testing.T) {
@@ -50,7 +50,7 @@ func TestContextExhaustion(t *testing.T) {
 	// Set up the test data
 	req := api.GenerateRequest{
 		Model:  smol,
-		Prompt: "Write me a story with a ton of emojis?",
+		Prompt: "Write me a story in english with a lot of emojis",
 		Stream: &stream,
 		Options: map[string]any{
 			"temperature": 0,

integration/embed_test.go

@@ -8,6 +8,7 @@ import (
 	"testing"
 	"time"
 
+	"github.com/google/go-cmp/cmp"
 	"github.com/ollama/ollama/api"
 )
 
@@ -38,14 +39,14 @@ func TestAllMiniLMEmbeddings(t *testing.T) {
 	defer cleanup()
 
 	req := api.EmbeddingRequest{
-		Model:  "all-minilm",
-		Prompt: "why is the sky blue?",
+		Model:     "all-minilm",
+		Prompt:    "why is the sky blue?",
+		KeepAlive: &api.Duration{Duration: 10 * time.Second},
 	}
 
 	res, err := embeddingTestHelper(ctx, client, t, req)
-
 	if err != nil {
-		t.Fatalf("error: %v", err)
+		t.Fatal(err)
 	}
 
 	if len(res.Embedding) != 384 {
@@ -73,9 +74,8 @@ func TestAllMiniLMEmbed(t *testing.T) {
 	}
 
 	res, err := embedTestHelper(ctx, client, t, req)
-
 	if err != nil {
-		t.Fatalf("error: %v", err)
+		t.Fatal(err)
 	}
 
 	if len(res.Embeddings) != 1 {
@@ -111,9 +111,8 @@ func TestAllMiniLMBatchEmbed(t *testing.T) {
 	}
 
 	res, err := embedTestHelper(ctx, client, t, req)
-
 	if err != nil {
-		t.Fatalf("error: %v", err)
+		t.Fatal(err)
 	}
 
 	if len(res.Embeddings) != 2 {
@@ -155,93 +154,135 @@ func TestAllMiniLMEmbedTruncate(t *testing.T) {
 
 	truncTrue, truncFalse := true, false
 
-	type testReq struct {
-		Name    string
-		Request api.EmbedRequest
+	want, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
+		Model: "all-minilm",
+		Input: "why",
+	})
+	if err != nil {
+		t.Fatal(err)
 	}
 
-	reqs := []testReq{
+	cases := []struct {
+		name    string
+		request api.EmbedRequest
+		check   func(*api.EmbedResponse, error)
+	}{
 		{
-			Name: "Target Truncation",
-			Request: api.EmbedRequest{
+			name: "target truncation",
+			request: api.EmbedRequest{
 				Model: "all-minilm",
 				Input: "why",
 			},
-		},
-		{
-			Name: "Default Truncate",
-			Request: api.EmbedRequest{
-				Model:   "all-minilm",
-				Input:   "why is the sky blue?",
-				Options: map[string]any{"num_ctx": 1},
+			check: func(got *api.EmbedResponse, err error) {
+				if err != nil {
+					t.Fatal(err)
+				}
+
+				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
+					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
+				}
 			},
 		},
 		{
-			Name: "Explicit Truncate",
-			Request: api.EmbedRequest{
+			name: "default truncate",
+			request: api.EmbedRequest{
+				Model:   "all-minilm",
+				Input:   "why is the sky blue?",
+				Options: map[string]any{"num_ctx": 3},
+			},
+			check: func(got *api.EmbedResponse, err error) {
+				if err != nil {
+					t.Fatal(err)
+				}
+				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
+					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
+				}
+			},
+		},
+		{
+			name: "explicit truncate",
+			request: api.EmbedRequest{
+				Model:    "all-minilm",
+				Input:    "why is the sky blue?",
+				Truncate: &truncTrue,
+				Options:  map[string]any{"num_ctx": 3},
+			},
+			check: func(got *api.EmbedResponse, err error) {
+				if err != nil {
+					t.Fatal(err)
+				}
+				if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
+					t.Errorf("embedding mismatch (-want +got):\n%s", diff)
+				}
+			},
+		},
+		{
+			name: "truncate error",
+			request: api.EmbedRequest{
+				Model:    "all-minilm",
+				Input:    "why is the sky blue?",
+				Truncate: &truncFalse,
+				Options:  map[string]any{"num_ctx": 3},
+			},
+			check: func(res *api.EmbedResponse, err error) {
+				if err.Error() != "input exceeds maximum context length" {
+					t.Fatalf("expected truncation error, got: %v", err)
+				}
+			},
+		},
+		{
+			name: "input after truncate error",
+			request: api.EmbedRequest{
 				Model:    "all-minilm",
 				Input:    "why is the sky blue?",
 				Truncate: &truncTrue,
 				Options:  map[string]any{"num_ctx": 1},
 			},
+			check: func(res *api.EmbedResponse, err error) {
+				if err.Error() != "input after truncation exceeds maximum context length" {
+					t.Fatalf("expected truncation error, got: %v", err)
+				}
+			},
+		},
+		{
+			name: "input after truncate error",
+			request: api.EmbedRequest{
+				Model:    "all-minilm",
+				Input:    "why is the sky blue?",
+				Truncate: &truncTrue,
+				Options:  map[string]any{"num_ctx": 0},
+			},
+			check: func(res *api.EmbedResponse, err error) {
+				if err.Error() != "input after truncation exceeds maximum context length" {
+					t.Fatalf("expected truncation error, got: %v", err)
+				}
+			},
 		},
 	}
 
-	res := make(map[string]*api.EmbedResponse)
-
-	for _, req := range reqs {
-		response, err := embedTestHelper(ctx, client, t, req.Request)
-		if err != nil {
-			t.Fatalf("error: %v", err)
-		}
-		res[req.Name] = response
-	}
-
-	if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
-		t.Fatal("expected default request to truncate correctly")
-	}
-
-	if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
-		t.Fatal("expected default request and truncate true request to be the same")
-	}
-
-	// check that truncate set to false returns an error if context length is exceeded
-	_, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
-		Model:    "all-minilm",
-		Input:    "why is the sky blue?",
-		Truncate: &truncFalse,
-		Options:  map[string]any{"num_ctx": 1},
-	})
-
-	if err == nil {
-		t.Fatal("expected error, got nil")
+	for _, req := range cases {
+		t.Run(req.name, func(t *testing.T) {
+			req.check(embedTestHelper(ctx, client, t, req.request))
+		})
 	}
 }
 
 func embeddingTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbeddingRequest) (*api.EmbeddingResponse, error) {
+	t.Helper()
+
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatalf("failed to pull model %s: %v", req.Model, err)
+		t.Fatal(err)
 	}
 
-	response, err := client.Embeddings(ctx, &req)
-
-	if err != nil {
-		return nil, err
-	}
-
-	return response, nil
+	return client.Embeddings(ctx, &req)
 }
 
 func embedTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
+	t.Helper()
+
 	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatalf("failed to pull model %s: %v", req.Model, err)
+		t.Fatal(err)
 	}
 
-	response, err := client.Embed(ctx, &req)
-
-	if err != nil {
-		return nil, err
-	}
-
-	return response, nil
+	return client.Embed(ctx, &req)
 }

integration/utils_test.go

@@ -502,6 +502,22 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
 		done <- 0
 	}()
 
+	var response string
+	verify := func() {
+		// Verify the response contains the expected data
+		response = buf.String()
+		atLeastOne := false
+		for _, resp := range anyResp {
+			if strings.Contains(strings.ToLower(response), resp) {
+				atLeastOne = true
+				break
+			}
+		}
+		if !atLeastOne {
+			t.Fatalf("%s: none of %v found in %s", genReq.Model, anyResp, response)
+		}
+	}
+
 	select {
 	case <-stallTimer.C:
 		if buf.Len() == 0 {
@@ -517,21 +533,14 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
 		if genErr != nil {
 			t.Fatalf("%s failed with %s request prompt %s", genErr, genReq.Model, genReq.Prompt)
 		}
-		// Verify the response contains the expected data
-		response := buf.String()
-		atLeastOne := false
-		for _, resp := range anyResp {
-			if strings.Contains(strings.ToLower(response), resp) {
-				atLeastOne = true
-				break
-			}
-		}
-		if !atLeastOne {
-			t.Fatalf("%s: none of %v found in %s", genReq.Model, anyResp, response)
-		}
+		verify()
 		slog.Info("test pass", "model", genReq.Model, "prompt", genReq.Prompt, "contains", anyResp, "response", response)
 	case <-ctx.Done():
-		t.Error("outer test context done while waiting for generate")
+		// On slow systems, we might timeout before some models finish rambling, so check what we have so far to see
+		// if it's considered a pass - the stallTimer will detect hangs, but we want to consider slow systems a pass
+		// if they are still generating valid responses
+		slog.Warn("outer test context done while waiting for generate")
+		verify()
 	}
 	return context
 }
@@ -552,7 +561,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
 			}, {
 				Model:     smol,
-				Prompt:    "what is the origin of the US thanksgiving holiday? Be brief but factual in your reply",
+				Prompt:    "how do rainbows form? Be brief but factual in your reply",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
 			}, {
@@ -570,9 +579,9 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 		[][]string{
 			{"sunlight", "scattering", "interact", "color", "surface", "depth", "red", "orange", "yellow", "absorbs", "wavelength"},
 			{"soil", "organic", "earth", "black", "tan", "chemical", "processes", "pigments", "particles", "iron oxide", "rust", "air", "water", "mixture", "mixing"},
-			{"england", "english", "massachusetts", "pilgrims", "colonists", "independence", "british", "feast", "family", "gatherings", "traditions", "turkey", "colonial", "period", "harvest", "agricultural", "european settlers", "american revolution", "civil war", "16th century", "17th century", "native american", "united states", "cultural", "hardship", "autumn", "festival"},
+			{"water", "droplet", "refracted", "reflect", "color", "spectrum"},
 			{"fourth", "july", "declaration", "independence"},
-			{"nitrogen", "oxygen", "carbon", "dioxide"},
+			{"nitrogen", "oxygen", "carbon", "dioxide", "water", "vapor"},
 		}
 }
 
@@ -599,6 +608,22 @@ func DoChat(ctx context.Context, t *testing.T, client *api.Client, req api.ChatR
 		done <- 0
 	}()
 
+	var response string
+	verify := func() {
+		// Verify the response contains the expected data
+		response = buf.String()
+		atLeastOne := false
+		for _, resp := range anyResp {
+			if strings.Contains(strings.ToLower(response), resp) {
+				atLeastOne = true
+				break
+			}
+		}
+		if !atLeastOne {
+			t.Fatalf("%s: none of %v found in \"%s\" -- request was:%v", req.Model, anyResp, response, req.Messages)
+		}
+	}
+
 	select {
 	case <-stallTimer.C:
 		if buf.Len() == 0 {
@@ -614,23 +639,14 @@ func DoChat(ctx context.Context, t *testing.T, client *api.Client, req api.ChatR
 		if genErr != nil {
 			t.Fatalf("%s failed with %s request prompt %v", genErr, req.Model, req.Messages)
 		}
-
-		// Verify the response contains the expected data
-		response := buf.String()
-		atLeastOne := false
-		for _, resp := range anyResp {
-			if strings.Contains(strings.ToLower(response), resp) {
-				atLeastOne = true
-				break
-			}
-		}
-		if !atLeastOne {
-			t.Fatalf("%s: none of %v found in \"%s\" -- request was:%v", req.Model, anyResp, response, req.Messages)
-		}
-
+		verify()
 		slog.Info("test pass", "model", req.Model, "messages", req.Messages, "contains", anyResp, "response", response)
 	case <-ctx.Done():
-		t.Error("outer test context done while waiting for generate")
+		// On slow systems, we might timeout before some models finish rambling, so check what we have so far to see
+		// if it's considered a pass - the stallTimer will detect hangs, but we want to consider slow systems a pass
+		// if they are still generating valid responses
+		slog.Warn("outer test context done while waiting for chat")
+		verify()
 	}
 	return &api.Message{Role: role, Content: buf.String()}
 }

llama/llama.go

@@ -515,33 +515,34 @@ func (c *MtmdContext) NewEmbed(llamaContext *Context, data []byte) ([][]float32,
 	}
 	nChunks := C.mtmd_input_chunks_size(ic)
 	numEmbed := llamaContext.Model().NEmbd()
-	lastChunkSize := 0
+	embed := make([][]float32, 0)
 	for i := range int(nChunks) {
 		chunk := C.mtmd_input_chunks_get(ic, C.size_t(i))
 		numTokens := int(C.mtmd_input_chunk_get_n_tokens(chunk))
-		lastChunkSize = numTokens
+		slog.Debug("chunk tokens", "index", i, "numTokens", numTokens)
 
 		// Encode the chunk
 		if C.int32_t(0) != C.mtmd_encode_chunk(c.c, chunk) {
 			return nil, errors.New("unable to encode mtmd image chunk")
 		}
-	}
 
-	// Get the embeddings
-	embed := make([][]float32, lastChunkSize)
-	embd := C.mtmd_get_output_embd(c.c)
-	if nil == embd {
-		return nil, errors.New("failed to get image embedding")
-	}
+		// Get the embeddings for this chunk
+		chunkEmbed := make([][]float32, numTokens)
+		chunkEmbd := C.mtmd_get_output_embd(c.c)
+		if nil == chunkEmbd {
+			continue
+		}
 
-	// Extend the embedding array for each token
-	s := unsafe.Slice((*float32)(embd), numEmbed*lastChunkSize)
-	rows := make([]float32, len(s))
-	copy(rows, s)
-	for i := range lastChunkSize {
-		embed[i] = rows[i*numEmbed : (i+1)*numEmbed]
+		// Extend the embedding array for each token
+		s := unsafe.Slice((*float32)(chunkEmbd), numTokens*numEmbed)
+		rows := make([]float32, len(s))
+		copy(rows, s)
+		for i := range numTokens {
+			chunkEmbed[i] = rows[i*numEmbed : (i+1)*numEmbed]
+		}
+		embed = append(embed, chunkEmbed...)
 	}
-
+	slog.Debug("image embeddings", "totalEmbeddings", len(embed))
 	return embed, nil
 }
 

llm/memory.go

@@ -202,7 +202,7 @@ func estimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 	var kvct string
 	if useFlashAttention {
 		requested := strings.ToLower(envconfig.KvCacheType())
-		if requested != "" && f.SupportsKVCacheType(requested) {
+		if f.SupportsKVCacheType(requested) {
 			kvct = requested
 		}
 	}

llm/server.go

@@ -148,7 +148,11 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 	var textProcessor model.TextProcessor
 	var err error
 	if envconfig.NewEngine() || f.KV().OllamaEngineRequired() {
-		textProcessor, err = model.NewTextProcessor(modelPath)
+		if len(projectors) == 0 {
+			textProcessor, err = model.NewTextProcessor(modelPath)
+		} else {
+			err = errors.New("split vision models aren't supported")
+		}
 		if err != nil {
 			// To prepare for opt-out mode, instead of treating this as an error, we fallback to the old runner
 			slog.Debug("model not yet supported by Ollama engine, switching to compatibility mode", "model", modelPath, "error", err)
@@ -161,11 +165,6 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 		}
 	}
 
-	newEstimates := textProcessor != nil && envconfig.NewMemoryEstimates()
-	if newEstimates {
-		slog.Info("enabling new memory estimates")
-	}
-
 	// Verify the requested context size is <= the model training size
 	trainCtx := f.KV().ContextLength()
 	if opts.NumCtx > int(trainCtx) && trainCtx > 0 {
@@ -173,6 +172,8 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 		opts.NumCtx = int(trainCtx)
 	}
 
+	opts.NumBatch = min(opts.NumBatch, opts.NumCtx)
+
 	loadRequest := LoadRequest{LoraPath: adapters, KvSize: opts.NumCtx * numParallel, BatchSize: opts.NumBatch, Parallel: numParallel, MultiUserCache: envconfig.MultiUserCache()}
 
 	defaultThreads := discover.GetSystemInfo().GetOptimalThreadCount()
@@ -218,7 +219,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 
 		// Flash Attention also supports kv cache quantization
 		// Enable if the requested and kv cache type is supported by the model
-		if kvct != "" && f.SupportsKVCacheType(kvct) {
+		if f.SupportsKVCacheType(kvct) {
 			loadRequest.KvCacheType = kvct
 		} else {
 			slog.Warn("kv cache type not supported by model", "type", kvct)
@@ -431,7 +432,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 			}
 		}()
 
-		if newEstimates {
+		if textProcessor != nil {
 			return &ollamaServer{llmServer: s}, nil
 		} else {
 			return &llamaServer{llmServer: s, ggml: f}, nil

logutil/logutil.go

@@ -5,6 +5,8 @@ import (
 	"io"
 	"log/slog"
 	"path/filepath"
+	"runtime"
+	"time"
 )
 
 const LevelTrace slog.Level = -8
@@ -29,10 +31,18 @@ func NewLogger(w io.Writer, level slog.Level) *slog.Logger {
 	}))
 }
 
+type key string
+
 func Trace(msg string, args ...any) {
-	slog.Log(context.TODO(), LevelTrace, msg, args...)
+	TraceContext(context.WithValue(context.TODO(), key("skip"), 1), msg, args...)
 }
 
 func TraceContext(ctx context.Context, msg string, args ...any) {
-	slog.Log(ctx, LevelTrace, msg, args...)
+	if logger := slog.Default(); logger.Enabled(ctx, LevelTrace) {
+		skip, _ := ctx.Value(key("skip")).(int)
+		pc, _, _, _ := runtime.Caller(1 + skip)
+		record := slog.NewRecord(time.Now(), LevelTrace, msg, pc)
+		record.Add(args...)
+		logger.Handler().Handle(ctx, record)
+	}
 }

ml/backend.go

@@ -416,6 +416,7 @@ type Tensor interface {
 	AddID(ctx Context, t2, ids Tensor) Tensor
 
 	Softmax(ctx Context) Tensor
+	L2Norm(ctx Context, eps float32) Tensor
 	LayerNorm(ctx Context, weight, bias Tensor, eps float32) Tensor
 	RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
 	Scale(ctx Context, s float64) Tensor
@@ -429,12 +430,13 @@ type Tensor interface {
 	Sin(ctx Context) Tensor
 	Cos(ctx Context) Tensor
 	Tanh(ctx Context) Tensor
-	GELU(ctx Context) Tensor
-	QuickGELU(ctx Context) Tensor
-	SILU(ctx Context) Tensor
-	RELU(ctx Context) Tensor
+	GELU(ctx Context, up ...Tensor) Tensor
+	SILU(ctx Context, up ...Tensor) Tensor
+	RELU(ctx Context, up ...Tensor) Tensor
 	Sigmoid(ctx Context) Tensor
-	SwiGLU(ctx Context, up Tensor, alpha, limit float32) Tensor
+
+	// AlphaLimitSILU is a variant of SILU that clamps the input to the range [-limit, limit]
+	SILUAlphaLimit(ctx Context, up Tensor, alpha, limit float32) Tensor
 
 	Reshape(ctx Context, shape ...int) Tensor
 	View(ctx Context, offset int, shape ...int) Tensor

ml/backend/ggml/ggml.go

@@ -1205,6 +1205,13 @@ func (t *Tensor) AddID(ctx ml.Context, t2, ids ml.Tensor) ml.Tensor {
 	}
 }
 
+func (t *Tensor) L2Norm(ctx ml.Context, eps float32) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_l2_norm(ctx.(*Context).ctx, t.t, C.float(eps)),
+	}
+}
+
 func (t *Tensor) LayerNorm(ctx ml.Context, w, b ml.Tensor, eps float32) ml.Tensor {
 	tt := C.ggml_norm(ctx.(*Context).ctx, t.t, C.float(eps))
 	if w != nil {
@@ -1424,35 +1431,46 @@ func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
 	}
 }
 
-func (t *Tensor) GELU(ctx ml.Context) ml.Tensor {
+func (t *Tensor) GELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
+	if len(t2) > 0 {
+		return &Tensor{
+			b: t.b,
+			t: C.ggml_geglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
+		}
+	}
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_gelu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) QuickGELU(ctx ml.Context) ml.Tensor {
-	return &Tensor{
-		b: t.b,
-		t: C.ggml_gelu_quick_inplace(ctx.(*Context).ctx, t.t),
+func (t *Tensor) SILU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
+	if len(t2) > 0 {
+		return &Tensor{
+			b: t.b,
+			t: C.ggml_swiglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
+		}
 	}
-}
-
-func (t *Tensor) SILU(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_silu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) RELU(ctx ml.Context) ml.Tensor {
+func (t *Tensor) RELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
+	if len(t2) > 0 {
+		return &Tensor{
+			b: t.b,
+			t: C.ggml_reglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
+		}
+	}
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_relu_inplace(ctx.(*Context).ctx, t.t),
 	}
 }
 
-func (t *Tensor) SwiGLU(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor {
+func (t *Tensor) SILUAlphaLimit(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor {
 	return &Tensor{
 		b: t.b,
 		t: C.ggml_swiglu_oai(ctx.(*Context).ctx, t.t, up.(*Tensor).t, C.float(alpha), C.float(limit)),

ml/nn/attention.go

@@ -26,6 +26,7 @@ func Attention(ctx ml.Context, query, key, value ml.Tensor, scale float64, cache
 }
 
 func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scale float64, cache kvcache.Cache) ml.Tensor {
+	ctx.Forward(query)
 	if key != nil && value != nil {
 		if query.Dim(0) != key.Dim(0) {
 			panic(fmt.Errorf("d_k in attention operation does not match between query(%v) and key(%v)", query.Dim(0), key.Dim(0)))
@@ -39,6 +40,7 @@ func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scal
 			panic(fmt.Errorf("seq_len_k in attention operation does not match between key(%v) and value(%v)", key.Dim(2), value.Dim(2)))
 		}
 
+		ctx.Forward(key, value)
 		if cache != nil {
 			cache.Put(ctx, key, value)
 		}

ml/nn/pooling/pooling.go

@@ -0,0 +1,42 @@
+package pooling
+
+import (
+	"github.com/ollama/ollama/ml"
+)
+
+type Type uint32
+
+const (
+	TypeNone Type = iota
+	TypeMean
+	TypeCLS
+	TypeLast
+)
+
+func (t Type) String() string {
+	switch t {
+	case TypeMean:
+		return "Mean"
+	case TypeCLS:
+		return "CLS"
+	case TypeLast:
+		return "Last"
+	default:
+		return "Unknown"
+	}
+}
+
+func (t Type) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
+	switch t {
+	case TypeMean:
+		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
+		return hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	case TypeCLS:
+		return hiddenStates.View(ctx, 0, hiddenStates.Dim(0))
+	case TypeLast:
+		hiddenStates = hiddenStates.View(ctx, (hiddenStates.Dim(1)-1)*hiddenStates.Stride(1), hiddenStates.Dim(0))
+		return hiddenStates
+	default:
+		panic("unknown pooling type")
+	}
+}

ml/nn/pooling/pooling_test.go

@@ -0,0 +1,79 @@
+package pooling_test
+
+import (
+	"bytes"
+	"os"
+	"slices"
+	"testing"
+
+	"github.com/google/go-cmp/cmp"
+	"github.com/ollama/ollama/discover"
+	fsggml "github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/backend/ggml"
+	"github.com/ollama/ollama/ml/nn/pooling"
+)
+
+func setup(tb testing.TB, n int) ml.Backend {
+	tb.Helper()
+
+	f, err := os.CreateTemp(tb.TempDir(), "*.bin")
+	if err != nil {
+		tb.Fatal(err)
+	}
+	defer f.Close()
+
+	if err := fsggml.WriteGGUF(f, fsggml.KV{
+		"general.architecture": "test",
+		"test.block_count":     uint32(1),
+	}, []*fsggml.Tensor{
+		{Name: "blk.0.weight", Shape: []uint64{1}, WriterTo: bytes.NewBuffer(make([]byte, 4))},
+	}); err != nil {
+		tb.Fatal(err)
+	}
+
+	var gpuLayers ml.GPULayersList
+	if gpus := discover.GetGPUInfo(); len(gpus) > 0 {
+		gpuLayers = append(gpuLayers, ml.GPULayers{
+			ID: gpus[0].ID,
+			Layers: slices.Collect(func(yield func(int) bool) {
+				for i := range n {
+					if !yield(i) {
+						return
+					}
+				}
+			}),
+		})
+	}
+	b, err := ggml.New(f.Name(), ml.BackendParams{AllocMemory: true, GPULayers: gpuLayers})
+	if err != nil {
+		tb.Fatal(err)
+	}
+
+	return b
+}
+
+func TestForward(t *testing.T) {
+	cases := map[pooling.Type][]float32{
+		pooling.TypeMean: {4, 5, 6, 7, 8, 9, 10, 11},
+		pooling.TypeCLS:  {0, 1, 2, 3, 4, 5, 6, 7},
+		pooling.TypeLast: {8, 9, 10, 11, 12, 13, 14, 15},
+	}
+	for typ, want := range cases {
+		t.Run(typ.String(), func(t *testing.T) {
+			b := setup(t, 99)
+			defer b.Close()
+
+			ctx := b.NewContext()
+			defer ctx.Close()
+
+			tt := ctx.Input().Arange(0, 16, 1, ml.DTypeF32).Reshape(ctx, 8, 2)
+			tt = typ.Forward(ctx, tt)
+
+			ctx.Forward(tt).Compute(tt)
+			if diff := cmp.Diff(want, tt.Floats()); diff != "" {
+				t.Error(diff)
+			}
+		})
+	}
+}

model/input/input.go

@@ -54,10 +54,9 @@ type Batch struct {
 	// Inputs is the input tokens, including placeholders for multimodal inputs.
 	Inputs ml.Tensor
 
-	// Multimodal is a set of multimodal embeddings previously created by
-	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
-	// models or for batches without multimodal elements.
-	Multimodal []MultimodalIndex
+	// Outputs are the set of indicies into Inputs for which output data should
+	// be returned.
+	Outputs ml.Tensor
 
 	// Positions is the position for each Input, relative to its sequence. Equal
 	// in length to Inputs.
@@ -66,7 +65,8 @@ type Batch struct {
 	// Sequences is the sequence for each Input. Equal in length to Inputs.
 	Sequences []int
 
-	// Outputs are the set of indicies into Inputs for which output data should
-	// be returned.
-	Outputs []int32
+	// Multimodal is a set of multimodal embeddings previously created by
+	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
+	// models or for batches without multimodal elements.
+	Multimodal []MultimodalIndex
 }

model/model.go

@@ -5,7 +5,6 @@ import (
 	"fmt"
 	_ "image/jpeg"
 	_ "image/png"
-	"math"
 	"os"
 	"reflect"
 	"strconv"
@@ -21,10 +20,15 @@ import (
 	"github.com/ollama/ollama/logutil"
 	"github.com/ollama/ollama/ml"
 	_ "github.com/ollama/ollama/ml/backend"
+	"github.com/ollama/ollama/ml/nn/pooling"
 	"github.com/ollama/ollama/model/input"
 )
 
-var ErrNoVisionModel = errors.New("this model is missing data required for image input")
+var (
+	ErrNoVisionModel        = errors.New("this model is missing data required for image input")
+	ErrUnsupportedModel     = errors.New("model not supported")
+	ErrUnsupportedTokenizer = errors.New("tokenizer not supported")
+)
 
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
@@ -103,23 +107,12 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
 		return nil, err
 	}
 
-	arch := b.Config().Architecture()
-	if b.Config().Uint("pooling_type", math.MaxUint32) != math.MaxUint32 {
-		arch = arch + "_embed"
-	}
-
-	f, ok := models[arch]
-	if !ok {
-		return nil, fmt.Errorf("unsupported model architecture %q", arch)
-	}
-
-	m, err := f(b.Config())
+	m, err := modelForArch(b.Config())
 	if err != nil {
 		return nil, err
 	}
 
 	base := Base{b: b, config: m.Config()}
-
 	v := reflect.ValueOf(m)
 	v.Elem().Set(populateFields(base, v.Elem()))
 	return m, nil
@@ -131,30 +124,38 @@ func NewTextProcessor(s string) (TextProcessor, error) {
 		return nil, err
 	}
 	defer r.Close()
+
 	meta, err := fsggml.Decode(r, -1)
 	if err != nil {
 		return nil, err
 	}
-	return getTextProcessor(meta.KV())
-}
 
-func getTextProcessor(kv fsggml.KV) (TextProcessor, error) {
-	arch := kv.Architecture()
-	f, ok := models[arch]
-	if !ok {
-		return nil, fmt.Errorf("unsupported model architecture %q", arch)
-	}
-	m, err := f(kv)
+	m, err := modelForArch(meta.KV())
 	if err != nil {
 		return nil, err
 	}
+
 	tp, ok := m.(TextProcessor)
 	if !ok {
-		return nil, fmt.Errorf("%v is not a TextProcessor", m)
+		return nil, ErrUnsupportedTokenizer
 	}
 	return tp, nil
 }
 
+func modelForArch(c fs.Config) (Model, error) {
+	arch := c.Architecture()
+	if pooling.Type(c.Uint("pooling_type")) != pooling.TypeNone {
+		arch = arch + "_embed"
+	}
+
+	f, ok := models[arch]
+	if !ok {
+		return nil, ErrUnsupportedModel
+	}
+
+	return f(c)
+}
+
 func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value {
 	t := v.Type()
 
@@ -242,7 +243,7 @@ func setPointer(base Base, v reflect.Value, tags []Tag) {
 		vv = vv.Elem()
 	}
 
-	vv = vv.Elem()
+	vv = reflect.Indirect(vv)
 	if v.IsNil() {
 		vv = reflect.New(v.Type().Elem()).Elem()
 	}

model/model_test.go

@@ -1,9 +1,9 @@
 package model
 
 import (
+	"errors"
 	"reflect"
 	"slices"
-	"strings"
 	"testing"
 
 	"github.com/google/go-cmp/cmp"
@@ -12,7 +12,6 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/backend/ggml"
 	"github.com/ollama/ollama/ml/nn"
-	"github.com/ollama/ollama/model/input"
 )
 
 func TestParseTags(t *testing.T) {
@@ -148,39 +147,58 @@ func TestPopulateFieldsAlternateName(t *testing.T) {
 	}
 }
 
-func TestGetTextProcessor(t *testing.T) {
-	tp, err := getTextProcessor(fsggml.KV{})
-	if err == nil {
-		t.Error("expected error")
-	} else if !strings.Contains(err.Error(), "unsupported model architecture") {
-		t.Errorf("unexpected error: %v", err)
-	} else if tp != nil {
-		t.Error("expected nil tp")
+func TestModelForArch(t *testing.T) {
+	type fakeModel struct {
+		Model
 	}
 
-	models["dummy"] = func(fs.Config) (Model, error) {
-		return notTextProcessorModel{}, nil
+	type fakeEmbeddingModel struct {
+		Model
 	}
-	tp, err = getTextProcessor(fsggml.KV{"general.architecture": "dummy"})
-	if err == nil {
-		t.Error("expected error")
-	} else if !strings.Contains(err.Error(), "not a TextProcessor") {
-		t.Errorf("unexpected error: %v", err)
-	} else if tp != nil {
-		t.Error("expected nil tp")
+
+	models["model"] = func(c fs.Config) (Model, error) { return fakeModel{}, nil }
+	models["model_embed"] = func(c fs.Config) (Model, error) { return fakeEmbeddingModel{}, nil }
+
+	cases := []struct {
+		name   string
+		config fs.Config
+		want   any
+		err    error
+	}{
+		{
+			name: "model",
+			config: fsggml.KV{
+				"general.architecture": "model",
+			},
+			want: fakeModel{},
+		},
+		{
+			name: "embedding",
+			config: fsggml.KV{
+				"general.architecture": "model",
+				"model.pooling_type":   uint32(1),
+			},
+			want: fakeEmbeddingModel{},
+		},
+		{
+			name: "unsupported",
+			config: fsggml.KV{
+				"general.architecture": "unsupported",
+			},
+			err: ErrUnsupportedModel,
+		},
+	}
+
+	for _, tt := range cases {
+		t.Run(tt.name, func(t *testing.T) {
+			got, err := modelForArch(tt.config)
+			if !errors.Is(err, tt.err) {
+				t.Fatal(err)
+			}
+
+			if diff := cmp.Diff(tt.want, got); diff != "" {
+				t.Errorf("modelForArch() returned unexpected values (-want +got):\n%s", diff)
+			}
+		})
 	}
 }
-
-type notTextProcessorModel struct{}
-
-func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) {
-	panic("unimplemented")
-}
-
-func (notTextProcessorModel) Backend() ml.Backend {
-	panic("unimplemented")
-}
-
-func (notTextProcessorModel) Config() config {
-	panic("unimplemented")
-}

model/models/bert/embed.go

@@ -0,0 +1,181 @@
+package bert
+
+import (
+	"cmp"
+	"math"
+
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/ml/nn/pooling"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type Model struct {
+	model.Base
+	model.TextProcessor
+
+	TokenEmbedding     *nn.Embedding `gguf:"token_embd"`
+	TypeEmbedding      *nn.Embedding `gguf:"token_types"`
+	PositionEmbedding  *nn.Embedding `gguf:"position_embd"`
+	TokenEmbeddingNorm *nn.LayerNorm `gguf:"token_embd_norm"`
+
+	Layers []EncoderLayer `gguf:"blk"`
+
+	Options
+}
+
+// Forward implements model.Model.
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
+	hiddenStates = hiddenStates.Add(ctx, m.TypeEmbedding.Weight.View(ctx, 0, m.hiddenSize))
+	hiddenStates = hiddenStates.Add(ctx, m.PositionEmbedding.Forward(ctx, ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))))
+	hiddenStates = m.TokenEmbeddingNorm.Forward(ctx, hiddenStates, m.eps)
+
+	for _, layer := range m.Layers {
+		hiddenStates = layer.Forward(ctx, hiddenStates, &m.Options)
+	}
+
+	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
+	if m.normalize {
+		hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
+	}
+
+	return hiddenStates, nil
+}
+
+type EncoderLayer struct {
+	*Attention
+	AttentionNorm *nn.LayerNorm `gguf:"attn_output_norm"`
+
+	*MLP
+	MLPNorm *nn.LayerNorm `gguf:"layer_output_norm"`
+}
+
+func (e *EncoderLayer) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
+	// Attention
+	residual := hiddenStates
+	hiddenStates = e.Attention.Forward(ctx, hiddenStates, opts)
+	hiddenStates = hiddenStates.Add(ctx, residual)
+	hiddenStates = e.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
+
+	// MLP
+	residual = hiddenStates
+	hiddenStates = e.MLP.Forward(ctx, hiddenStates, opts)
+	hiddenStates = hiddenStates.Add(ctx, residual)
+	hiddenStates = e.MLPNorm.Forward(ctx, hiddenStates, opts.eps)
+
+	return hiddenStates
+}
+
+type Attention struct {
+	Query     *nn.Linear    `gguf:"attn_q"`
+	QueryNorm *nn.LayerNorm `gguf:"attn_q_norm"`
+
+	Key     *nn.Linear    `gguf:"attn_k"`
+	KeyNorm *nn.LayerNorm `gguf:"attn_k_norm"`
+
+	Value *nn.Linear `gguf:"attn_v"`
+
+	Output *nn.Linear `gguf:"attn_output"`
+}
+
+func (a *Attention) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
+	batchSize := hiddenStates.Dim(1)
+
+	query := a.Query.Forward(ctx, hiddenStates)
+	if a.QueryNorm != nil {
+		query = a.QueryNorm.Forward(ctx, query, opts.eps)
+	}
+	query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
+
+	key := a.Key.Forward(ctx, hiddenStates)
+	if a.KeyNorm != nil {
+		key = a.KeyNorm.Forward(ctx, key, opts.eps)
+	}
+	key = key.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
+
+	value := a.Value.Forward(ctx, hiddenStates)
+	value = value.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
+
+	attention := nn.Attention(ctx, query, key, value, 1/math.Sqrt(float64(opts.headDim())), nil)
+	attention = attention.Reshape(ctx, opts.hiddenSize, batchSize)
+	return a.Output.Forward(ctx, attention)
+}
+
+type MLP struct {
+	Up   *nn.Linear `gguf:"ffn_up"`
+	Down *nn.Linear `gguf:"ffn_down"`
+}
+
+func (m *MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
+	return m.Down.Forward(ctx, m.Up.Forward(ctx, hiddenStates).GELU(ctx))
+}
+
+type Options struct {
+	hiddenSize,
+	numHeads,
+	numKVHeads,
+	keyLength,
+	valueLength int
+	poolingType pooling.Type
+	eps         float32
+	normalize   bool
+}
+
+func (o Options) headDim() int {
+	return cmp.Or(o.keyLength, o.valueLength, o.hiddenSize/o.numHeads)
+}
+
+func New(c fs.Config) (model.Model, error) {
+	var processor model.TextProcessor
+	switch c.String("tokenizer.ggml.model", "bert") {
+	case "bert":
+		processor = model.NewWordPiece(
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Scores: c.Floats("tokenizer.ggml.scores"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
+				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
+				BOS: []int32{
+					int32(cmp.Or(
+						c.Uint("tokenizer.ggml.cls_token_id"),
+						c.Uint("tokenizer.ggml.bos_token_id"),
+					)),
+				},
+				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", true),
+				EOS: []int32{
+					int32(cmp.Or(
+						c.Uint("tokenizer.ggml.separator_token_id"),
+						//nolint:misspell
+						// NOTE: "seperator_token_id" is a typo in model metadata but we need to
+						// support it for compatibility.
+						c.Uint("tokenizer.ggml.seperator_token_id"),
+						c.Uint("tokenizer.ggml.eos_token_id"),
+					)),
+				},
+			},
+		)
+	default:
+		return nil, model.ErrUnsupportedTokenizer
+	}
+
+	return &Model{
+		TextProcessor: processor,
+		Layers:        make([]EncoderLayer, c.Uint("block_count")),
+		Options: Options{
+			hiddenSize:  int(c.Uint("embedding_length")),
+			numHeads:    int(c.Uint("attention.head_count")),
+			numKVHeads:  int(c.Uint("attention.head_count_kv")),
+			eps:         c.Float("attention.layer_norm_epsilon"),
+			poolingType: pooling.Type(c.Uint("pooling_type")),
+			normalize:   c.Bool("normalize_embeddings", true),
+		},
+	}, nil
+}
+
+func init() {
+	model.Register("bert", New)
+	model.Register("bert_embed", New)
+}

model/models/gemma2/model.go

@@ -24,7 +24,7 @@ type Options struct {
 
 type Model struct {
 	model.Base
-	model.SentencePieceModel
+	model.SentencePiece
 
 	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
 	Layers         []Layer       `gguf:"blk"`
@@ -40,7 +40,7 @@ const (
 
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
-		SentencePieceModel: model.NewSentencePieceModel(
+		SentencePiece: model.NewSentencePiece(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -63,7 +63,7 @@ func New(c fs.Config) (model.Model, error) {
 			attnValLen:        int(c.Uint("attention.value_length")),
 			eps:               c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:          c.Float("rope.freq_base", 10000.0),
-			ropeScale:         c.Float("rope.freq_scale", 1.0),
+			ropeScale:         c.Float("rope.scaling.factor", 1.0),
 			attnLogitSoftcap:  c.Float("attn_logit_softcapping"),
 			finalLogitSoftcap: c.Float("final_logit_softcapping"),
 		},
@@ -88,7 +88,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	if opts.largeModelScaling {
 		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -98,7 +98,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -128,7 +128,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, m.Options.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, 1/m.Options.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type MLP struct {
@@ -138,7 +138,7 @@ type MLP struct {
 }
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -176,7 +176,6 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
@@ -193,7 +192,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var lastLayerOutputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			lastLayerOutputs = outputs
+			lastLayerOutputs = batch.Outputs
 		}
 
 		hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, m.Cache, m.Options)

model/models/gemma3/embed.go

@@ -1,49 +1,38 @@
 package gemma3
 
 import (
-	"errors"
-
 	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/ml/nn/pooling"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
 )
 
 type embedModel struct {
 	model.Base
-	model.SentencePieceModel
+	model.SentencePiece
 
 	*TextModel
-	PoolingType uint32
+	poolingType pooling.Type
 
 	Dense [2]*nn.Linear `gguf:"dense"`
 }
 
 func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	batch.Outputs = batch.Positions // return all positions
 	hiddenStates := m.TextModel.Forward(ctx, batch, m.Cache)
-
-	switch m.PoolingType {
-	case 0: // None
-	case 1: // Mean
-		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
-		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	default:
-		return nil, errors.New("unsupported pooling type")
-	}
-
+	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
 	for _, dense := range m.Dense {
 		hiddenStates = dense.Forward(ctx, hiddenStates)
 	}
-
+	hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
 	return hiddenStates, nil
 }
 
 func newEmbedModel(c fs.Config) (model.Model, error) {
 	m := &embedModel{
-		SentencePieceModel: model.NewSentencePieceModel(
+		SentencePiece: model.NewSentencePiece(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -61,7 +50,7 @@ func newEmbedModel(c fs.Config) (model.Model, error) {
 			},
 		),
 		TextModel:   newTextModel(c),
-		PoolingType: c.Uint("pooling_type", 0),
+		poolingType: pooling.Type(c.Uint("pooling_type", 0)),
 	}
 
 	m.Cache = kvcache.NewWrapperCache(

model/models/gemma3/model.go

@@ -16,7 +16,7 @@ import (
 
 type Model struct {
 	model.Base
-	model.SentencePieceModel
+	model.SentencePiece
 
 	*VisionModel `gguf:"v"`
 	*TextModel
@@ -55,7 +55,7 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
 
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
-		SentencePieceModel: model.NewSentencePieceModel(
+		SentencePiece: model.NewSentencePiece(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),

model/models/gemma3/model_text.go

@@ -53,7 +53,10 @@ func newTextModel(c fs.Config) *TextModel {
 			eps:            c.Float("attention.layer_norm_rms_epsilon", 1e-06),
 			ropeLocalBase:  c.Float("rope.local.freq_base", 10000.0),
 			ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
-			ropeScale:      c.Float("rope.freq_scale", 1.0),
+			ropeScale:      1,
+			// NOTE: the rope.scaling.factor is set incorrectly in the official QAT weights
+			//       (8 instead of 1)
+			// ropeScale:      c.Float("rope.scaling.factor", 1.0),
 		},
 	}
 
@@ -84,7 +87,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
 	q = sa.QueryNorm.Forward(ctx, q, opts.eps)
-	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	if opts.largeModelScaling {
 		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -95,7 +98,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
 	k = sa.KeyNorm.Forward(ctx, k, opts.eps)
-	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -113,7 +116,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
 		ropeBase = m.TextConfig.ropeGlobalBase
 	}
 
-	return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, 1/m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type TextMLP struct {
@@ -123,7 +126,7 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextConfig) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -161,7 +164,6 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 
 func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cache) ml.Tensor {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextConfig.hiddenSize)))
@@ -194,7 +196,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
 
 		var lastLayerOutputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			lastLayerOutputs = outputs
+			lastLayerOutputs = batch.Outputs
 		}
 
 		hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextConfig)

model/models/gemma3n/model.go

@@ -10,7 +10,7 @@ import (
 
 type Model struct {
 	model.Base
-	model.SentencePieceModel
+	model.SentencePiece
 
 	*TextModel
 }
@@ -23,7 +23,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 func New(c fs.Config) (model.Model, error) {
 	m := Model{
 		TextModel: newTextModel(c),
-		SentencePieceModel: model.NewSentencePieceModel(
+		SentencePiece: model.NewSentencePiece(
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),

model/models/gemma3n/model_text.go

@@ -83,7 +83,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
 
 	hiddenStates = hiddenStates.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx).Mean(ctx)
 	hiddenStates = hiddenStates.Permute(ctx, 2, 0, 1, 3).Contiguous(ctx)
-	hiddenStates = hiddenStates.Rows(ctx, ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)))
+	hiddenStates = hiddenStates.Rows(ctx, batch.Outputs)
 
 	hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
 	return m.Output.Forward(ctx, hiddenStates), nil
@@ -95,7 +95,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
 		ropeBase = m.ropeBaseLocal
 	}
 
-	return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 type TextScaledWordEmbedding struct {
@@ -170,8 +170,7 @@ func (d TextLayer) Forward(ctx ml.Context, hiddenStates, perLayerInput, position
 	}
 
 	active = d.PerLayerInputGate.Forward(ctx, active)
-	active = active.GELU(ctx)
-	active = active.Mul(ctx, perLayerInput)
+	active = active.GELU(ctx, perLayerInput)
 
 	active = d.PerLayerProjection.Forward(ctx, active)
 	active = d.PostPerLayerNorm.Forward(ctx, active, opts.eps)
@@ -257,14 +256,14 @@ func (attn TextAttention) Forward(ctx ml.Context, hiddenStates, positions ml.Ten
 	query := attn.Query.Forward(ctx, hiddenStates)
 	query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
 	query = attn.QueryNorm.Forward(ctx, query, opts.eps)
-	query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	var key, value ml.Tensor
 	if !sharedKV {
 		key = attn.Key.Forward(ctx, hiddenStates)
 		key = key.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
 		key = attn.KeyNorm.Forward(ctx, key, opts.eps)
-		key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+		key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 		value = attn.Value.Forward(ctx, hiddenStates)
 		value = value.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
@@ -292,7 +291,7 @@ func (mlp TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, activationSpa
 		hiddenStates = hiddenStates.Sub(ctx, cutoff).RELU(ctx)
 	}
 
-	hiddenStates = hiddenStates.GELU(ctx).Mul(ctx, upStates)
+	hiddenStates = hiddenStates.GELU(ctx, upStates)
 	hiddenStates = mlp.Down.Forward(ctx, hiddenStates)
 	return hiddenStates
 }
@@ -350,7 +349,7 @@ func newTextModel(c fs.Config) *TextModel {
 			eps:           c.Float("attention.layer_norm_rms_epsilon", 1e-06),
 			ropeBase:      c.Float("rope.freq_base", 1_000_000),
 			ropeBaseLocal: c.Float("rope.freq_base_local", 10_000),
-			ropeScale:     c.Float("rope.freq_scale", 1.0),
+			ropeScale:     c.Float("rope.scaling.factor", 1.0),
 
 			slidingWindowPattern:    c.Bools("attention.sliding_window_pattern"),
 			activationSparsityScale: c.Floats("activation_sparsity_scale"),

model/models/gptoss/model.go

@@ -41,8 +41,8 @@ func (m *Transformer) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, err
 		}
 
 		var outputs ml.Tensor
-		if len(batch.Outputs) > 0 && i == len(m.TransformerBlocks)-1 {
-			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+		if i == len(m.TransformerBlocks)-1 {
+			outputs = batch.Outputs
 		}
 
 		hiddenStates = block.Forward(ctx, hiddenStates, positions, outputs, one, m.Cache, &m.Options)
@@ -210,7 +210,7 @@ func (mlp *MLPBlock) Forward(ctx ml.Context, hiddenStates, one ml.Tensor, opts *
 		up = mlp.Up.Forward(ctx, hiddenStates, selectedExperts)
 	}
 
-	hiddenStates = gate.SwiGLU(ctx, up, 1.702, 7)
+	hiddenStates = gate.SILUAlphaLimit(ctx, up, 1.702, 7)
 
 	experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
 	experts = experts.Mul(ctx, routingWeights)

model/models/llama/model.go

@@ -2,7 +2,6 @@ package llama
 
 import (
 	"cmp"
-	"fmt"
 	"math"
 
 	"github.com/ollama/ollama/fs"
@@ -23,51 +22,60 @@ type Options struct {
 
 type Model struct {
 	model.Base
-	model.BytePairEncoding
+	model.TextProcessor
 
 	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
 	Layers         []Layer       `gguf:"blk"`
 	OutputNorm     *nn.RMSNorm   `gguf:"output_norm"`
 	Output         *nn.Linear    `gguf:"output,alt:token_embd"`
 
-	*Options
+	Options
 }
 
 func New(c fs.Config) (model.Model, error) {
-	// This model currently only supports the gpt2 tokenizer
-	if c.String("tokenizer.ggml.model") == "llama" {
-		return nil, fmt.Errorf("unsupported tokenizer: llama")
+	if c.Uint("expert_count") > 0 {
+		// TODO: support mixtures of experts
+		return nil, model.ErrUnsupportedModel
 	}
-	// Best effort detection of library/deepseek-coder model(s) which are incompatible
-	if c.String("general.name") == "deepseek-ai" {
-		return nil, fmt.Errorf("unsupported model: %s", c.String("general.name"))
-	}
-	m := Model{
-		BytePairEncoding: model.NewBytePairEncoding(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
-			&model.Vocabulary{
-				Values: c.Strings("tokenizer.ggml.tokens"),
-				Types:  c.Ints("tokenizer.ggml.token_type"),
-				Merges: c.Strings("tokenizer.ggml.merges"),
-				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
-				BOS:    []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
-				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
-				EOS: append(
-					[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
-					c.Ints("tokenizer.ggml.eos_token_ids")...,
-				),
-			},
+
+	var processor model.TextProcessor
+	vocabulary := model.Vocabulary{
+		Values: c.Strings("tokenizer.ggml.tokens"),
+		Scores: c.Floats("tokenizer.ggml.scores"),
+		Types:  c.Ints("tokenizer.ggml.token_type"),
+		Merges: c.Strings("tokenizer.ggml.merges"),
+		AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
+		BOS:    []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
+		AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
+		EOS: append(
+			[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
+			c.Ints("tokenizer.ggml.eos_token_ids")...,
 		),
-		Layers: make([]Layer, c.Uint("block_count")),
-		Options: &Options{
+	}
+	switch c.String("tokenizer.ggml.model") {
+	case "gpt2":
+		processor = model.NewBytePairEncoding(
+			`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
+			&vocabulary,
+		)
+	case "llama":
+		processor = model.NewSentencePiece(&vocabulary)
+	default:
+		return nil, model.ErrUnsupportedTokenizer
+	}
+
+	m := Model{
+		TextProcessor: processor,
+		Layers:        make([]Layer, c.Uint("block_count")),
+		Options: Options{
 			hiddenSize: int(c.Uint("embedding_length")),
 			numHeads:   int(c.Uint("attention.head_count")),
 			numKVHeads: int(c.Uint("attention.head_count_kv")),
 			headDim:    int(c.Uint("attention.key_length")),
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
-			ropeBase:   c.Float("rope.freq_base"),
-			ropeScale:  c.Float("rope.freq_scale", 1),
+			ropeBase:   c.Float("rope.freq_base", 1e5),
+			ropeScale:  c.Float("rope.scaling.factor", 1),
 		},
 	}
 
@@ -98,8 +106,8 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
-	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
-	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
 	attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -108,7 +116,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
-	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil
+	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil
 }
 
 type MLP struct {
@@ -118,7 +126,7 @@ type MLP struct {
 }
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -160,10 +168,10 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+			outputs = batch.Outputs
 		}
 
-		hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, m.Options)
+		hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, &m.Options)
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)

model/models/llama4/model.go

@@ -176,9 +176,7 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
-
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
 }
 
 func init() {

model/models/llama4/model_text.go

@@ -33,8 +33,8 @@ func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, positions, attent
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
 	if useRope {
-		query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
-		key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+		query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+		key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 	}
 
 	if opts.useQKNorm {
@@ -58,14 +58,14 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
 type TextExperts struct {
-	Gate *nn.Linear `gguf:"ffn_gate_exps"`
-	Up   *nn.Linear `gguf:"ffn_up_exps"`
-	Down *nn.Linear `gguf:"ffn_down_exps"`
+	Gate *nn.LinearBatch `gguf:"ffn_gate_exps"`
+	Up   *nn.LinearBatch `gguf:"ffn_up_exps"`
+	Down *nn.LinearBatch `gguf:"ffn_down_exps"`
 }
 
 func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tensor, opts *TextOptions) ml.Tensor {
@@ -76,9 +76,9 @@ func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tens
 	hiddenStates = hiddenStates.Repeat(ctx, 1, opts.numExpertsUsed)
 	hiddenStates = hiddenStates.Mul(ctx, scores)
 
-	upStates := e.Up.Weight.MulmatID(ctx, hiddenStates, experts)
-	gateStates := e.Gate.Weight.MulmatID(ctx, hiddenStates, experts)
-	downStates := e.Down.Weight.MulmatID(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts)
+	upStates := e.Up.Forward(ctx, hiddenStates, experts)
+	gateStates := e.Gate.Forward(ctx, hiddenStates, experts)
+	downStates := e.Down.Forward(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts)
 
 	nextStates := downStates.View(ctx, 0, hiddenStates.Dim(0), downStates.Stride(2), hiddenStates.Dim(2))
 	for i := 1; i < opts.numExpertsUsed; i++ {
@@ -96,7 +96,7 @@ type TextSharedExpert struct {
 }
 
 func (mlp *TextSharedExpert) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -196,7 +196,7 @@ func newTextModel(c fs.Config) *TextModel {
 			numExpertsUsed:             int(c.Uint("expert_used_count")),
 			ropeDim:                    int(c.Uint("rope.dimension_count")),
 			ropeBase:                   c.Float("rope.freq_base"),
-			ropeScale:                  c.Float("rope.freq_scale", 1),
+			ropeScale:                  c.Float("rope.scaling.factor", 1),
 			eps:                        c.Float("attention.layer_norm_rms_epsilon"),
 			interleaveLayerStep:        int(c.Uint("interleave_moe_layer_step", 1)),
 			noRopeInterval:             int(c.Uint("no_rope_interval", 4)),
@@ -248,5 +248,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil
 }

model/models/mistral3/model.go

@@ -159,9 +159,8 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
 }
 
 func init() {

model/models/mistral3/model_text.go

@@ -40,11 +40,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -55,7 +55,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale), nil
 }
 
 type MLP struct {
@@ -65,7 +65,7 @@ type MLP struct {
 }
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -132,7 +132,7 @@ func newTextModel(c fs.Config) *TextModel {
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:   c.Float("rope.freq_base"),
-			ropeScale:  c.Float("rope.freq_scale", 1),
+			ropeScale:  c.Float("rope.scaling.factor", 1),
 		},
 	}
 }

model/models/mistral3/model_vision.go

@@ -51,7 +51,7 @@ type VisionMLP struct {
 }
 
 func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 

model/models/mllama/model.go

@@ -107,10 +107,9 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	}
 
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
 	// TODO: attention mask, cross attention mask
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
 }
 
 func init() {

model/models/mllama/model_text.go

@@ -26,11 +26,11 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
 
 	query := sa.Query.Forward(ctx, hiddenState)
 	query = query.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	key := sa.Key.Forward(ctx, hiddenState)
 	key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors))
+	key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
 
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -45,7 +45,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	// This will only get called for layers in the cache, which are just the self attention layers
 	if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok {
-		return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil
+		return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil
 	}
 
 	return key, nil
@@ -58,7 +58,7 @@ type TextMLP struct {
 }
 
 func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextModelOptions) ml.Tensor {
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
 
@@ -244,7 +244,7 @@ func newTextModel(c fs.Config) *TextModel {
 			ropeDim:              int(c.Uint("rope.dimension_count")),
 			eps:                  c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:             c.Float("rope.freq_base"),
-			ropeScale:            c.Float("rope.freq_scale", 1),
+			ropeScale:            c.Float("rope.scaling.factor", 1),
 			crossAttentionLayers: c.Ints("attention.cross_attention_layers"),
 		},
 	}

model/models/models.go

@@ -1,6 +1,7 @@
 package models
 
 import (
+	_ "github.com/ollama/ollama/model/models/bert"
 	_ "github.com/ollama/ollama/model/models/gemma2"
 	_ "github.com/ollama/ollama/model/models/gemma3"
 	_ "github.com/ollama/ollama/model/models/gemma3n"

model/models/qwen2/model.go

@@ -43,8 +43,8 @@ func (attn Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
 	value := attn.Value.Forward(ctx, hiddenStates)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
 
-	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
-	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
 	attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -59,7 +59,7 @@ type MLP struct {
 }
 
 func (mlp MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -111,7 +111,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+			outputs = batch.Outputs
 		}
 
 		hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, &m.Options)
@@ -124,7 +124,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 
 func (m Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
-	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 func New(c fs.Config) (model.Model, error) {
@@ -160,7 +160,7 @@ func New(c fs.Config) (model.Model, error) {
 			headDim:    int(c.Uint("attention.key_length")),
 			ropeDim:    int(c.Uint("rope.dimension_count")),
 			ropeBase:   c.Float("rope.freq_base"),
-			ropeScale:  c.Float("rope.freq_scale", 1),
+			ropeScale:  c.Float("rope.scaling.factor", 1),
 			eps:        c.Float("attention.layer_norm_rms_epsilon"),
 		},
 	}

model/models/qwen25vl/model.go

@@ -140,9 +140,8 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
-	outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 
-	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache)
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache)
 }
 
 func init() {

model/models/qwen25vl/model_text.go

@@ -38,7 +38,7 @@ func NewTextModel(c fs.Config) *TextModel {
 			originalContextLength: int(c.Uint("context_length", 128000)),
 			eps:                   c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:              c.Float("rope.freq_base"),
-			ropeScale:             c.Float("rope.freq_scale", 1),
+			ropeScale:             c.Float("rope.scaling.factor", 1),
 		},
 	}
 
@@ -60,11 +60,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
+	q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
+	k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -78,7 +78,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 // Shift applies rotary position embeddings to the key tensor for causal attention caching
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil
 }
 
 // MLP implements the feed-forward network component with SwiGLU activation
@@ -90,7 +90,7 @@ type MLP struct {
 
 func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
 	// Apply SwiGLU activation gating
-	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
 	// Project back to hidden dimension
 	return mlp.Down.Forward(ctx, hiddenState)
 }

model/models/qwen25vl/model_vision.go

@@ -100,8 +100,7 @@ type VisionMLP struct {
 func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
 	// Using activation as specified in config (likely GELU or SiLU/Swish)
 	gateOutput := mlp.Gate.Forward(ctx, hiddenStates)
-	upOutput := mlp.Up.Forward(ctx, hiddenStates)
-	hiddenStates = gateOutput.SILU(ctx).Mul(ctx, upOutput)
+	hiddenStates = gateOutput.SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 
 	return mlp.Down.Forward(ctx, hiddenStates)
 }

model/models/qwen3/embed.go

@@ -0,0 +1,73 @@
+package qwen3
+
+import (
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn/pooling"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type embedModel struct {
+	model.Base
+	model.BytePairEncoding
+
+	*Model
+	poolingType pooling.Type
+}
+
+func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	hiddenStates, err := m.forward(ctx, batch)
+	if err != nil {
+		return nil, err
+	}
+
+	hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
+	hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
+	return hiddenStates, nil
+}
+
+func newEmbed(c fs.Config) (model.Model, error) {
+	layers := make([]Layer, c.Uint("block_count"))
+	for i := range layers {
+		layers[i].MLP = &dense{}
+	}
+	m := embedModel{
+		BytePairEncoding: model.NewBytePairEncoding(
+			`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
+				Merges: c.Strings("tokenizer.ggml.merges"),
+				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
+				BOS:    []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
+				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
+				EOS: append(
+					[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
+					c.Ints("tokenizer.ggml.eos_token_ids")...,
+				),
+			},
+		),
+		Model: &Model{
+			Layers: layers,
+			Options: &Options{
+				hiddenSize:     int(c.Uint("embedding_length")),
+				numHeads:       int(c.Uint("attention.head_count")),
+				numKVHeads:     int(c.Uint("attention.head_count_kv")),
+				keyLength:      int(c.Uint("attention.key_length")),
+				valueLength:    int(c.Uint("attention.value_length")),
+				eps:            c.Float("attention.layer_norm_rms_epsilon"),
+				ropeBase:       c.Float("rope.freq_base"),
+				ropeScale:      c.Float("rope.freq_scale", 1),
+				numExperts:     int(c.Uint("expert_count")),
+				numExpertsUsed: int(c.Uint("expert_used_count")),
+				normTopKProb:   c.Bool("norm_top_k_prob", true),
+			},
+		},
+		poolingType: pooling.Type(c.Uint("pooling_type")),
+	}
+
+	m.Cache = kvcache.NewCausalCache(m.Shift)
+	return &m, nil
+}

model/models/qwen3/model.go

@@ -30,10 +30,10 @@ func (o Options) headDim() int {
 }
 
 type Attention struct {
-	QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
 	Query     *nn.Linear  `gguf:"attn_q"`
-	KeyNorm   *nn.RMSNorm `gguf:"attn_k_norm"`
+	QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
 	Key       *nn.Linear  `gguf:"attn_k"`
+	KeyNorm   *nn.RMSNorm `gguf:"attn_k_norm"`
 	Value     *nn.Linear  `gguf:"attn_v"`
 	Output    *nn.Linear  `gguf:"attn_output"`
 }
@@ -52,8 +52,8 @@ func (sa *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
 	query = sa.QueryNorm.Forward(ctx, query, opts.eps)
 	key = sa.KeyNorm.Forward(ctx, key, opts.eps)
 
-	query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
-	key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX())
+	query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
+	key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
 
 	attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache)
 	attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize)
@@ -65,10 +65,10 @@ type MLP interface {
 }
 
 type sparse struct {
-	Router *nn.Linear `gguf:"ffn_gate_inp"`
-	Gate   *nn.Linear `gguf:"ffn_gate_exps"`
-	Up     *nn.Linear `gguf:"ffn_up_exps"`
-	Down   *nn.Linear `gguf:"ffn_down_exps"`
+	Router *nn.Linear      `gguf:"ffn_gate_inp"`
+	Gate   *nn.LinearBatch `gguf:"ffn_gate_exps"`
+	Up     *nn.LinearBatch `gguf:"ffn_up_exps"`
+	Down   *nn.LinearBatch `gguf:"ffn_down_exps"`
 }
 
 func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
@@ -87,13 +87,9 @@ func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options
 
 	hiddenStates = hiddenStates.Reshape(ctx, hiddenStates.Dim(0), 1, hiddenStates.Dim(1))
 
-	upStates := mlp.Up.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates, selectedExperts).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates, selectedExperts))
 
-	hiddenStates = mlp.Gate.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
-	hiddenStates = hiddenStates.SILU(ctx)
-	hiddenStates = hiddenStates.Mul(ctx, upStates)
-
-	experts := mlp.Down.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
+	experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
 	experts = experts.Mul(ctx, routingWeights)
 
 	nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2))
@@ -111,7 +107,8 @@ type dense struct {
 }
 
 func (mlp *dense) Forward(ctx ml.Context, hiddenStates ml.Tensor, _ *Options) ml.Tensor {
-	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).
+		SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
 	return mlp.Down.Forward(ctx, hiddenStates)
 }
 
@@ -154,29 +151,39 @@ type Model struct {
 	*Options
 }
 
-// Forward implements model.Model.
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	hiddenStates, err := m.forward(ctx, batch)
+	if err != nil {
+		return nil, err
+	}
+
+	return m.Output.Forward(ctx, hiddenStates), nil
+}
+
+// Forward implements model.Model.
+func (m *Model) forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 
 	hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 
 	for i, layer := range m.Layers {
-		m.Cache.SetLayer(i)
+		if m.Cache != nil {
+			m.Cache.SetLayer(i)
+		}
 
 		var outputs ml.Tensor
 		if i == len(m.Layers)-1 {
-			outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+			outputs = batch.Outputs
 		}
 
 		hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options)
 	}
 
-	hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
-	return m.Output.Forward(ctx, hiddenStates), nil
+	return m.OutputNorm.Forward(ctx, hiddenStates, m.eps), nil
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil
+	return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
 }
 
 var _ model.Model = (*Model)(nil)
@@ -216,7 +223,7 @@ func New(c fs.Config) (model.Model, error) {
 			valueLength:    int(c.Uint("attention.value_length")),
 			eps:            c.Float("attention.layer_norm_rms_epsilon"),
 			ropeBase:       c.Float("rope.freq_base"),
-			ropeScale:      c.Float("rope.freq_scale", 1),
+			ropeScale:      c.Float("rope.scaling.factor", 1),
 			numExperts:     int(c.Uint("expert_count")),
 			numExpertsUsed: int(c.Uint("expert_used_count")),
 			normTopKProb:   c.Bool("norm_top_k_prob", true),
@@ -230,4 +237,5 @@ func New(c fs.Config) (model.Model, error) {
 func init() {
 	model.Register("qwen3", New)
 	model.Register("qwen3moe", New)
+	model.Register("qwen3_embed", newEmbed)
 }

model/parsers/parsers.go

@@ -0,0 +1,37 @@
+package parsers
+
+import (
+	"github.com/ollama/ollama/api"
+)
+
+type Parser interface {
+	Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error)
+	HasToolSupport() bool
+	HasThinkingSupport() bool
+}
+
+func ParserForName(name string) Parser {
+	switch name {
+	case "qwen3-coder":
+		parser := &Qwen3CoderParser{}
+		return parser
+	case "passthrough":
+		return &PassthroughParser{}
+	default:
+		return nil
+	}
+}
+
+type PassthroughParser struct{}
+
+func (p *PassthroughParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
+	return s, "", nil, nil
+}
+
+func (p *PassthroughParser) HasToolSupport() bool {
+	return false
+}
+
+func (p *PassthroughParser) HasThinkingSupport() bool {
+	return false
+}

model/parsers/qwen3coder.go

@@ -0,0 +1,447 @@
+package parsers
+
+import (
+	"context"
+	"encoding/json"
+	"encoding/xml"
+	"fmt"
+	"log/slog"
+	"math"
+	"regexp"
+	"strconv"
+	"strings"
+	"unicode"
+
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/logutil"
+)
+
+type qwenParserState int
+
+const (
+	toolOpenTag  = "<tool_call>"
+	toolCloseTag = "</tool_call>"
+)
+
+const (
+	qwenParserState_LookingForToolStart qwenParserState = iota
+	qwenParserState_CollectingToolContent
+)
+
+type Qwen3CoderParser struct {
+	state qwenParserState
+	acc   strings.Builder
+}
+
+func (p *Qwen3CoderParser) HasToolSupport() bool {
+	return true
+}
+
+func (p *Qwen3CoderParser) HasThinkingSupport() bool {
+	return false
+}
+
+func (p *Qwen3CoderParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
+	p.acc.WriteString(s)
+
+	events := p.parseEvents()
+
+	var toolCalls []api.ToolCall
+	var sb strings.Builder
+	for _, event := range events {
+		switch event := event.(type) {
+		case qwenEventRawToolCall:
+			toolCall, err := parseToolCall(event, tools)
+			if err != nil {
+				slog.Warn("qwen tool call parsing failed", "error", err)
+				return "", "", nil, err
+			}
+			toolCalls = append(toolCalls, toolCall)
+		case qwenEventContent:
+			// TODO(drifkin): if the same turn contains multiple interleaved content
+			// events, we naively append them together here. See the note below about
+			// `qwenEvent`s for more details
+			sb.WriteString(event.content)
+		}
+	}
+
+	return sb.String(), "", toolCalls, nil
+}
+
+func (p *Qwen3CoderParser) parseEvents() []qwenEvent {
+	var all []qwenEvent
+
+	keepLooping := true
+	for keepLooping {
+		var events []qwenEvent
+		events, keepLooping = eat(p)
+		if len(events) > 0 {
+			all = append(all, events...)
+		}
+	}
+
+	if len(all) > 0 {
+		slog.Log(context.TODO(), logutil.LevelTrace, "qwen events parsed", "events", all, "state", p.state, "acc", p.acc.String())
+	}
+
+	return all
+}
+
+// we use some internal event types in order to communicate between `Add` and
+// `eat`. We do this to support interleaving content and parallel tool calls in
+// the parser, even though qwen3-coder isn't supposed to do this. Our API
+// doesn't currently support models outputting multiple messages in a turn, so
+// we wouldn't be able to represent it yet, but there's no reason to prevent the
+// parser from supporting it, especially for future models if they end up using
+// a similar format.
+type qwenEvent interface {
+	isQwenEvent()
+}
+
+type qwenEventRawToolCall struct {
+	raw string
+}
+
+type qwenEventContent struct {
+	content string
+}
+
+func (qwenEventContent) isQwenEvent()     {}
+func (qwenEventRawToolCall) isQwenEvent() {}
+
+// eat consumes the parser's buffer, and returns a list of any unambiguous
+// events from the current parser state. If the parser transitions to another
+// state, it may have additional events to emit on the next call, which is what
+// the second return value indicates
+func eat(p *Qwen3CoderParser) ([]qwenEvent, bool) {
+	var events []qwenEvent
+
+	switch p.state {
+	case qwenParserState_LookingForToolStart:
+		if strings.Contains(p.acc.String(), toolOpenTag) {
+			// we found a full tool open tag, so we can emit the content before the
+			// tag, being sure to trim any trailing whitespace
+			split := strings.SplitN(p.acc.String(), toolOpenTag, 2)
+			before := split[0]
+			before = strings.TrimRightFunc(before, unicode.IsSpace)
+			if len(before) > 0 {
+				events = append(events, qwenEventContent{content: before})
+			}
+			after := split[1]
+			p.acc.Reset()
+			p.acc.WriteString(after)
+			p.state = qwenParserState_CollectingToolContent
+			return events, true
+		} else if overlap := overlap(p.acc.String(), toolOpenTag); overlap > 0 {
+			// we found a partial tool open tag, so we can emit the unambiguous part,
+			// which is the (trailing-whitespace trimmed) content before the partial
+			// tool open tag
+			beforePartialTag := p.acc.String()[:len(p.acc.String())-overlap]
+			trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
+			ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
+			unambiguous := p.acc.String()[:ambiguousStart]
+			ambiguous := p.acc.String()[ambiguousStart:]
+			p.acc.Reset()
+			p.acc.WriteString(ambiguous)
+			events = append(events, qwenEventContent{content: unambiguous})
+			return events, false
+		} else {
+			// we found content that is entirely not a tool call. We should withhold
+			// any trailing whitespace in case this is the end of the content
+			whitespaceLen := trailingWhitespaceLen(p.acc.String())
+			ambiguousStart := len(p.acc.String()) - whitespaceLen
+			unambiguous := p.acc.String()[:ambiguousStart]
+			ambiguous := p.acc.String()[ambiguousStart:]
+			p.acc.Reset()
+			p.acc.WriteString(ambiguous)
+			if len(unambiguous) > 0 {
+				events = append(events, qwenEventContent{content: unambiguous})
+			}
+			return events, false
+		}
+	case qwenParserState_CollectingToolContent:
+		if strings.Contains(p.acc.String(), toolCloseTag) {
+			split := strings.SplitN(p.acc.String(), toolCloseTag, 2)
+			before := split[0]
+			if len(before) == 0 {
+				slog.Warn("qwen tool call closing tag found but no content before it")
+			}
+			// remove any whitespace between the tool call and any content after it
+			after := strings.TrimLeftFunc(split[1], unicode.IsSpace)
+			p.acc.Reset()
+			p.acc.WriteString(after)
+			events = append(events, qwenEventRawToolCall{raw: before})
+			p.state = qwenParserState_LookingForToolStart
+			return events, true
+		} else {
+			// note that we don't need to check the overlap here because we only plan
+			// on parsing the tool call once we see the full closing tag. We don't
+			// stream back the unparsed tool content, so there's no need to be eager
+			// here
+			return events, false
+		}
+	default:
+		panic("unreachable")
+	}
+}
+
+// TODO(drifkin): move this to a shared location
+// 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
+}
+
+func trailingWhitespaceLen(s string) int {
+	for i := len(s) - 1; i >= 0; i-- {
+		if !unicode.IsSpace(rune(s[i])) {
+			return len(s) - i - 1
+		}
+	}
+	return len(s)
+}
+
+type XMLFunctionCall struct {
+	XMLName    xml.Name       `xml:"function"`
+	Name       string         `xml:"name,attr"`
+	Parameters []XMLParameter `xml:"parameter"`
+}
+
+type XMLParameter struct {
+	Name  string `xml:"name,attr"`
+	Value string `xml:",chardata"`
+}
+
+// parseToolCall parses a raw tool call string into an api.ToolCall.
+// The raw string follows an xml-like format, here's an example:
+//
+// <function=get_current_temperature>
+// <parameter=location>
+// San Francisco
+// </parameter>
+// <parameter=unit>
+// celsius
+// </parameter>
+// </function>
+func parseToolCall(raw qwenEventRawToolCall, tools []api.Tool) (api.ToolCall, error) {
+	toolCall := api.ToolCall{}
+
+	xmlString := transformToXML(raw.raw)
+
+	var functionCall XMLFunctionCall
+	err := xml.Unmarshal([]byte(xmlString), &functionCall)
+	if err != nil {
+		return api.ToolCall{}, err
+	}
+
+	toolCall.Function = api.ToolCallFunction{
+		Name: functionCall.Name,
+	}
+
+	// Find the matching tool to get parameter types
+	var matchedTool *api.Tool
+	for i := range tools {
+		if tools[i].Function.Name == functionCall.Name {
+			matchedTool = &tools[i]
+			break
+		}
+	}
+
+	toolCall.Function.Arguments = make(api.ToolCallFunctionArguments)
+	for _, parameter := range functionCall.Parameters {
+		// Look up the parameter type if we found the tool
+		var paramType api.PropertyType
+		if matchedTool != nil && matchedTool.Function.Parameters.Properties != nil {
+			if prop, ok := matchedTool.Function.Parameters.Properties[parameter.Name]; ok {
+				paramType = prop.Type
+			}
+		}
+
+		toolCall.Function.Arguments[parameter.Name] = parseValue(parameter.Value, paramType)
+	}
+
+	return toolCall, nil
+}
+
+// parseValue converts a raw string value to the appropriate type based on the parameter type specification.
+//
+// For union types (multiple types in PropertyType, which we support but doesn't
+// seem as though the reference parser does type coercion with those types in
+// mind) we use a type precedence approach:
+// 1. null - checked first regardless of declared types (matches reference implementation)
+// 2. boolean - only "true"/"false" are valid booleans
+// 3. integer - must parse as a whole number
+// 4. number - must parse as numeric (returns int if no decimal part)
+// 5. array - must parse as valid JSON array
+// 6. object - must parse as valid JSON object
+// 7. string - always succeeds (least specific type)
+//
+// This precedence ensures we return the most specific type that successfully parses,
+// following the principle of least surprise. For example, with PropertyType{"string", "number"},
+// "123" becomes 123 (number), while "hello" becomes "hello" (string).
+func parseValue(raw string, paramType api.PropertyType) any {
+	// first remove a single leading newlines, and a single trailing newline (if
+	// they exist). This follows the reference implementation
+	raw = strings.TrimPrefix(raw, "\n")
+	raw = strings.TrimSuffix(raw, "\n")
+
+	// Check for null first (case-insensitive) - this takes precedence over any type
+	if strings.ToLower(raw) == "null" {
+		return nil
+	}
+
+	// If no type is specified, default to string
+	if len(paramType) == 0 {
+		return raw
+	}
+
+	// Check if any of the specified types match, using type precedence
+	// Order: boolean -> integer -> number -> array -> object -> string
+	typeSet := make(map[string]bool)
+	for _, t := range paramType {
+		typeSet[t] = true
+	}
+
+	// Try boolean first (most restrictive)
+	if typeSet["boolean"] {
+		lower := strings.ToLower(raw)
+		switch lower {
+		case "true":
+			return true
+		case "false":
+			return false
+		}
+		// If not a valid boolean but boolean is the only type, return false (matching reference)
+		if len(paramType) == 1 {
+			return false
+		}
+		// Otherwise try other types
+	}
+
+	// Try integer
+	if typeSet["integer"] {
+		if i, err := strconv.ParseInt(raw, 10, 64); err == nil {
+			// Return as int if it fits in int32, otherwise int64
+			if i >= math.MinInt32 && i <= math.MaxInt32 {
+				return int(i)
+			}
+			return i
+		}
+		// If integer is the only type and parsing failed, fall back to string
+		if len(paramType) == 1 {
+			return raw
+		}
+	}
+
+	// Try number (float)
+	if typeSet["number"] {
+		if f, err := strconv.ParseFloat(raw, 64); err == nil {
+			// If the number has no decimal part, return as int (matching reference)
+			if f == math.Trunc(f) {
+				i := int64(f)
+				if i >= math.MinInt32 && i <= math.MaxInt32 {
+					return int(i)
+				}
+				return i
+			}
+			return f
+		}
+		// If number is the only type and parsing failed, fall back to string
+		if len(paramType) == 1 {
+			return raw
+		}
+	}
+
+	// Try array
+	if typeSet["array"] {
+		var arr []interface{}
+		if err := json.Unmarshal([]byte(raw), &arr); err == nil {
+			return arr
+		}
+		// If array is the only type and parsing failed, fall back to string
+		if len(paramType) == 1 {
+			return raw
+		}
+	}
+
+	// Try object
+	if typeSet["object"] {
+		var obj map[string]interface{}
+		if err := json.Unmarshal([]byte(raw), &obj); err == nil {
+			return obj
+		}
+		// If object is the only type and parsing failed, fall back to string
+		if len(paramType) == 1 {
+			return raw
+		}
+	}
+
+	// String always succeeds (or if "string" is in the type set)
+	if typeSet["string"] {
+		return raw
+	}
+
+	// If we get here, none of the types matched and string wasn't an option
+	// We return string as a fallback. The reference implementation will attempt
+	// to parse the value as a python literal, but we purposefully don't support
+	// that
+	return raw
+}
+
+var (
+	qwenTagRegex    = regexp.MustCompile(`<(\w+)=([^>]+)>`)
+	qwenXMLTagRegex = regexp.MustCompile(`</?(?:function|parameter)(?:\s+name="[^"]*")?>`)
+)
+
+// transformToXML transforms a raw qwen tool call with xml-like tags into valid
+// xml so that it can be parsed by any xml parser
+func transformToXML(raw string) string {
+	// take the form `<tag=abc>` and transform it to `<tag name="abc">`, taking
+	// care to properly escape the string that becomes the attribute value
+	transformed := qwenTagRegex.ReplaceAllStringFunc(raw, func(match string) string {
+		groups := qwenTagRegex.FindStringSubmatch(match)
+		tag := groups[1]
+		var escapedValue strings.Builder
+		xml.EscapeText(&escapedValue, []byte(groups[2]))
+		return fmt.Sprintf(`<%s name="%s">`, tag, escapedValue.String())
+	})
+
+	// Walk the resulting string, escaping any character data that sits between the
+	// xml tags we just emitted
+	var out strings.Builder
+	lastIdx := 0
+	for _, loc := range qwenXMLTagRegex.FindAllStringIndex(transformed, -1) {
+		if loc[0] > lastIdx {
+			escapeTextNode(&out, transformed[lastIdx:loc[0]])
+		}
+		out.WriteString(transformed[loc[0]:loc[1]])
+		lastIdx = loc[1]
+	}
+	if lastIdx < len(transformed) {
+		escapeTextNode(&out, transformed[lastIdx:])
+	}
+
+	return out.String()
+}
+
+// escapeTextNode escapes XML character data without altering other characters
+// like newlines or tabs (which is why we don't use xml.EscapeText for this)
+func escapeTextNode(sb *strings.Builder, s string) {
+	for _, r := range s {
+		switch r {
+		case '&':
+			sb.WriteString("&amp;")
+		case '<':
+			sb.WriteString("&lt;")
+		case '>':
+			sb.WriteString("&gt;")
+		default:
+			sb.WriteRune(r)
+		}
+	}
+}

model/parsers/qwen3coder_test.go

@@ -0,0 +1,878 @@
+package parsers
+
+import (
+	"reflect"
+	"testing"
+
+	"github.com/ollama/ollama/api"
+)
+
+// tool creates a test tool with the given name and properties
+func tool(name string, props map[string]api.ToolProperty) api.Tool {
+	t := api.Tool{Type: "function", Function: api.ToolFunction{Name: name}}
+	t.Function.Parameters.Type = "object"
+	t.Function.Parameters.Properties = props
+	return t
+}
+
+func TestQwenParserStreaming(t *testing.T) {
+	type step struct {
+		input      string
+		wantEvents []qwenEvent
+	}
+
+	cases := []struct {
+		desc  string
+		steps []step
+		only  bool
+	}{
+		{
+			desc: "simple message streamed word by word",
+			steps: []step{
+				{
+					input:      "hi",
+					wantEvents: []qwenEvent{qwenEventContent{content: "hi"}},
+				},
+				{
+					input:      " there",
+					wantEvents: []qwenEvent{qwenEventContent{content: " there"}},
+				},
+			},
+		},
+		{
+			desc: "content before tool call",
+			steps: []step{
+				{
+					input:      "hi there<tool_call>",
+					wantEvents: []qwenEvent{qwenEventContent{content: "hi there"}},
+				},
+			},
+		},
+		{
+			desc: "multiple tool calls in one message",
+			steps: []step{
+				{
+					input: "before1<tool_call>in tool call</tool_call>after1<tool_call>in tool call 2</tool_call>after2",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "before1"},
+						qwenEventRawToolCall{raw: "in tool call"},
+						qwenEventContent{content: "after1"},
+						qwenEventRawToolCall{raw: "in tool call 2"},
+						qwenEventContent{content: "after2"},
+					},
+				},
+			},
+		},
+		{
+			desc: "tool calls with split tags",
+			steps: []step{
+				{
+					input: "before<tool",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "before"},
+					},
+				},
+				{
+					input:      "_call>in tool call</tool",
+					wantEvents: []qwenEvent{},
+				},
+				{
+					input: "_call>af",
+					wantEvents: []qwenEvent{
+						qwenEventRawToolCall{raw: "in tool call"},
+						qwenEventContent{content: "af"},
+					},
+				},
+				{
+					input: "ter",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "ter"},
+					},
+				},
+			},
+		},
+		{
+			desc: "trailing whitespace between content and tool call",
+			steps: []step{
+				{
+					input: "abc\n<tool_call>def</tool_call>",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "abc"},
+						qwenEventRawToolCall{raw: "def"},
+					},
+				},
+			},
+		},
+		{
+			desc: "trailing whitespace between tool call and content",
+			steps: []step{
+				{
+					input: "<tool_call>abc</tool_call>\ndef",
+					wantEvents: []qwenEvent{
+						qwenEventRawToolCall{raw: "abc"},
+						qwenEventContent{content: "def"},
+					},
+				},
+			},
+		},
+		{
+			desc: "empty content before tool call",
+			steps: []step{
+				{
+					input: "\n<tool_call>abc</tool_call>",
+					wantEvents: []qwenEvent{
+						qwenEventRawToolCall{raw: "abc"},
+					},
+				},
+			},
+		},
+		{
+			desc: "partial tool open tag fakeout",
+			steps: []step{
+				{
+					input: "abc\n<tool_call",
+					wantEvents: []qwenEvent{
+						// \n should not be emitted yet because `<tool_call` might be a tool
+						// open tag, in which case the whitespace should be trimmed
+						qwenEventContent{content: "abc"},
+					},
+				},
+				{
+					input: " fakeout",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "\n<tool_call fakeout"},
+					},
+				},
+			},
+		},
+		{
+			desc: "token-by-token whitespace handling",
+			steps: []step{
+				{
+					input: "a",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "a"},
+					},
+				},
+				{
+					input:      "\n",
+					wantEvents: []qwenEvent{},
+				},
+				{
+					input: "b",
+					wantEvents: []qwenEvent{
+						qwenEventContent{content: "\nb"},
+					},
+				},
+			},
+		},
+	}
+
+	anyOnlies := false
+	for _, tc := range cases {
+		if tc.only {
+			anyOnlies = true
+		}
+	}
+
+	for _, tc := range cases {
+		if anyOnlies && !tc.only {
+			continue
+		}
+
+		t.Run(tc.desc, func(t *testing.T) {
+			parser := Qwen3CoderParser{}
+
+			for i, step := range tc.steps {
+				parser.acc.WriteString(step.input)
+				gotEvents := parser.parseEvents()
+
+				if len(gotEvents) == 0 && len(step.wantEvents) == 0 {
+					// avoid deep equal on empty vs. nil slices
+					continue
+				}
+
+				if !reflect.DeepEqual(gotEvents, step.wantEvents) {
+					t.Errorf("step %d: input %q: got events %#v, want %#v", i, step.input, gotEvents, step.wantEvents)
+				}
+			}
+		})
+	}
+}
+
+func TestQwenToolParser(t *testing.T) {
+	type step struct {
+		name         string
+		rawToolCall  string
+		tools        []api.Tool
+		wantToolCall api.ToolCall
+	}
+
+	steps := []step{
+		{
+			name:  "simple tool call",
+			tools: []api.Tool{},
+			rawToolCall: `<function=get_current_temperature>
+<parameter=location>
+San Francisco
+</parameter>
+<parameter=unit>
+celsius
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "get_current_temperature",
+					Arguments: map[string]any{
+						"location": "San Francisco",
+						"unit":     "celsius",
+					},
+				},
+			},
+		},
+		{
+			name:  "names with spaces",
+			tools: []api.Tool{},
+			rawToolCall: `<function=get current temperature>
+<parameter=location with spaces>
+San Francisco
+</parameter>
+<parameter=unit with spaces>
+celsius
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "get current temperature",
+					Arguments: map[string]any{
+						"location with spaces": "San Francisco",
+						"unit with spaces":     "celsius",
+					},
+				},
+			},
+		},
+		// this mirrors the reference implementation's behavior, but unclear if it
+		// ever happens. If so, then we should probably remove them instead, this
+		// test is to just document the current behavior and test that we don't get
+		// xml errors
+		{
+			name:  "names with quotes",
+			tools: []api.Tool{},
+			rawToolCall: `<function="get current temperature">
+<parameter="location with spaces">
+San Francisco
+</parameter>
+<parameter="unit with spaces">
+"celsius"
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "\"get current temperature\"",
+					Arguments: map[string]any{
+						"\"location with spaces\"": "San Francisco",
+						"\"unit with spaces\"":     "\"celsius\"",
+					},
+				},
+			},
+		},
+		{
+			name: "tool call with typed parameters",
+			tools: []api.Tool{
+				tool("calculate", map[string]api.ToolProperty{
+					"x":       {Type: api.PropertyType{"number"}},
+					"y":       {Type: api.PropertyType{"integer"}},
+					"enabled": {Type: api.PropertyType{"boolean"}},
+					"items":   {Type: api.PropertyType{"array"}},
+				}),
+			},
+			rawToolCall: `<function=calculate>
+<parameter=x>
+3.14
+</parameter>
+<parameter=y>
+42
+</parameter>
+<parameter=enabled>
+true
+</parameter>
+<parameter=items>
+["a", "b", "c"]
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "calculate",
+					Arguments: map[string]any{
+						"x":       3.14,
+						"y":       42,
+						"enabled": true,
+						"items":   []any{"a", "b", "c"},
+					},
+				},
+			},
+		},
+		// regression test for <https://github.com/ollama/ollama/issues/12357>
+		{
+			name:  "ampersands in parameter values",
+			tools: []api.Tool{},
+			rawToolCall: `<function=exec>
+<parameter=command>
+ls && echo "done"
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "exec",
+					Arguments: map[string]any{
+						"command": "ls && echo \"done\"",
+					},
+				},
+			},
+		},
+		{
+			name:  "angle brackets in parameter values",
+			tools: []api.Tool{},
+			rawToolCall: `<function=exec>
+<parameter=command>
+ls && echo "a > b and a < b"
+</parameter>
+</function>`,
+			wantToolCall: api.ToolCall{
+				Function: api.ToolCallFunction{
+					Name: "exec",
+					Arguments: map[string]any{
+						"command": "ls && echo \"a > b and a < b\"",
+					},
+				},
+			},
+		},
+	}
+
+	for i, step := range steps {
+		gotToolCall, err := parseToolCall(qwenEventRawToolCall{raw: step.rawToolCall}, step.tools)
+		if err != nil {
+			t.Errorf("step %d (%s): %v", i, step.name, err)
+		}
+		if !reflect.DeepEqual(gotToolCall, step.wantToolCall) {
+			t.Errorf("step %d (%s): got tool call %#v, want %#v", i, step.name, gotToolCall, step.wantToolCall)
+		}
+	}
+}
+
+func TestQwenToolCallValueParsing(t *testing.T) {
+	cases := []struct {
+		desc      string
+		raw       string
+		paramType api.PropertyType
+		want      any
+	}{
+		{
+			desc:      "default string value (no type specified)",
+			paramType: api.PropertyType{},
+			raw:       "some-string",
+			want:      "some-string",
+		},
+		{
+			desc:      "trim a single leading and trailing newline",
+			paramType: api.PropertyType{},
+			raw:       "\nsome-string\n",
+			want:      "some-string",
+		},
+		{
+			desc:      "trim at most one leading and trailing newline",
+			paramType: api.PropertyType{},
+			raw:       "\n\nsome-string\n\n",
+			want:      "\nsome-string\n",
+		},
+		{
+			desc:      "newline really has to be the first character to be trimmed",
+			paramType: api.PropertyType{},
+			raw:       " \nsome-string\n ",
+			want:      " \nsome-string\n ",
+		},
+		{
+			desc:      "numeric type",
+			paramType: api.PropertyType{"number"},
+			raw:       "123",
+			want:      123,
+		},
+		// Integer parsing tests
+		{
+			desc:      "integer type",
+			paramType: api.PropertyType{"integer"},
+			raw:       "42",
+			want:      42,
+		},
+		{
+			desc:      "negative integer",
+			paramType: api.PropertyType{"integer"},
+			raw:       "-100",
+			want:      -100,
+		},
+		{
+			desc:      "zero integer",
+			paramType: api.PropertyType{"integer"},
+			raw:       "0",
+			want:      0,
+		},
+		{
+			desc:      "integer with leading zeros",
+			paramType: api.PropertyType{"integer"},
+			raw:       "007",
+			want:      7,
+		},
+		{
+			desc:      "large integer",
+			paramType: api.PropertyType{"integer"},
+			raw:       "2147483648", // Just beyond int32 max
+			want:      int64(2147483648),
+		},
+		// Float/number parsing tests
+		{
+			desc:      "float type",
+			paramType: api.PropertyType{"number"},
+			raw:       "3.14",
+			want:      3.14,
+		},
+		{
+			desc:      "negative float",
+			paramType: api.PropertyType{"number"},
+			raw:       "-273.15",
+			want:      -273.15,
+		},
+		{
+			desc:      "float without decimal part",
+			paramType: api.PropertyType{"number"},
+			raw:       "100.0",
+			want:      100,
+		},
+		{
+			desc:      "scientific notation positive",
+			paramType: api.PropertyType{"number"},
+			raw:       "1.23e5",
+			want:      123000, // Will be int since it has no decimal part
+		},
+		{
+			desc:      "scientific notation negative",
+			paramType: api.PropertyType{"number"},
+			raw:       "1.5e-3",
+			want:      0.0015,
+		},
+		{
+			desc:      "very small float",
+			paramType: api.PropertyType{"number"},
+			raw:       "0.00000001",
+			want:      0.00000001,
+		},
+		// String parsing tests
+		{
+			desc:      "explicit string type",
+			paramType: api.PropertyType{"string"},
+			raw:       "hello world",
+			want:      "hello world",
+		},
+		{
+			desc:      "string with special characters",
+			paramType: api.PropertyType{"string"},
+			raw:       "/usr/local/bin/test-file_v2.0.sh",
+			want:      "/usr/local/bin/test-file_v2.0.sh",
+		},
+		{
+			desc:      "string with quotes",
+			paramType: api.PropertyType{"string"},
+			raw:       `He said "hello" to me`,
+			want:      `He said "hello" to me`,
+		},
+		{
+			desc:      "multiline string",
+			paramType: api.PropertyType{"string"},
+			raw:       "line one\nline two\nline three",
+			want:      "line one\nline two\nline three",
+		},
+		{
+			desc:      "empty string",
+			paramType: api.PropertyType{"string"},
+			raw:       "",
+			want:      "",
+		},
+		{
+			desc:      "string that looks like a number",
+			paramType: api.PropertyType{"string"},
+			raw:       "12345",
+			want:      "12345",
+		},
+		// Boolean parsing tests
+		{
+			desc:      "boolean true",
+			paramType: api.PropertyType{"boolean"},
+			raw:       "true",
+			want:      true,
+		},
+		{
+			desc:      "boolean false",
+			paramType: api.PropertyType{"boolean"},
+			raw:       "false",
+			want:      false,
+		},
+		{
+			desc:      "boolean case insensitive true",
+			paramType: api.PropertyType{"boolean"},
+			raw:       "True",
+			want:      true,
+		},
+		{
+			desc:      "boolean case insensitive false",
+			paramType: api.PropertyType{"boolean"},
+			raw:       "FALSE",
+			want:      false,
+		},
+		// Null parsing tests
+		{
+			desc:      "null value lowercase",
+			paramType: api.PropertyType{"string"},
+			raw:       "null",
+			want:      nil,
+		},
+		{
+			desc:      "null value case insensitive",
+			paramType: api.PropertyType{"integer"},
+			raw:       "NULL",
+			want:      nil,
+		},
+		// Array parsing tests
+		{
+			desc:      "array of strings",
+			paramType: api.PropertyType{"array"},
+			raw:       `["foo", "bar", "baz"]`,
+			want:      []any{"foo", "bar", "baz"},
+		},
+		{
+			desc:      "array of numbers",
+			paramType: api.PropertyType{"array"},
+			raw:       `[1, 2.5, 3]`,
+			want:      []any{float64(1), 2.5, float64(3)},
+		},
+		{
+			desc:      "array of mixed types",
+			paramType: api.PropertyType{"array"},
+			raw:       `["string", 123, true, null]`,
+			want:      []any{"string", float64(123), true, nil},
+		},
+		{
+			desc:      "empty array",
+			paramType: api.PropertyType{"array"},
+			raw:       `[]`,
+			want:      []any{},
+		},
+		// Object parsing tests
+		{
+			desc:      "simple object",
+			paramType: api.PropertyType{"object"},
+			raw:       `{"key": "value", "number": 42}`,
+			want:      map[string]any{"key": "value", "number": float64(42)},
+		},
+		{
+			desc:      "nested object",
+			paramType: api.PropertyType{"object"},
+			raw:       `{"outer": {"inner": "value"}}`,
+			want:      map[string]any{"outer": map[string]any{"inner": "value"}},
+		},
+		{
+			desc:      "empty object",
+			paramType: api.PropertyType{"object"},
+			raw:       `{}`,
+			want:      map[string]any{},
+		},
+		// Error cases and fallback behavior
+		{
+			desc:      "invalid integer falls back to string",
+			paramType: api.PropertyType{"integer"},
+			raw:       "not-a-number",
+			want:      "not-a-number",
+		},
+		{
+			desc:      "invalid float falls back to string",
+			paramType: api.PropertyType{"number"},
+			raw:       "3.14.159",
+			want:      "3.14.159",
+		},
+		{
+			desc:      "invalid boolean falls back to false",
+			paramType: api.PropertyType{"boolean"},
+			raw:       "yes",
+			want:      false,
+		},
+		{
+			desc:      "invalid JSON array falls back to string",
+			paramType: api.PropertyType{"array"},
+			raw:       "[1, 2, unclosed",
+			want:      "[1, 2, unclosed",
+		},
+		{
+			desc:      "invalid JSON object falls back to string",
+			paramType: api.PropertyType{"object"},
+			raw:       `{"key": unclosed`,
+			want:      `{"key": unclosed`,
+		},
+		// Edge cases
+		{
+			desc:      "integer overflow should use int64",
+			paramType: api.PropertyType{"integer"},
+			raw:       "2147483648", // Beyond int32 max
+			want:      int64(2147483648),
+		},
+		{
+			desc:      "float with many decimal places",
+			paramType: api.PropertyType{"number"},
+			raw:       "3.141592653589793",
+			want:      3.141592653589793,
+		},
+		{
+			desc:      "string with JSON-like content",
+			paramType: api.PropertyType{"string"},
+			raw:       `{"this": "is", "just": "a string"}`,
+			want:      `{"this": "is", "just": "a string"}`,
+		},
+		{
+			desc:      "whitespace-only string",
+			paramType: api.PropertyType{"string"},
+			raw:       "   ",
+			want:      "   ",
+		},
+		// Unknown parameter (no type specified in tools)
+		{
+			desc:      "parameter not in tool definition defaults to string",
+			paramType: api.PropertyType{},
+			raw:       "some value",
+			want:      "some value",
+		},
+		// Union type tests
+		{
+			desc:      "string or number union - valid number",
+			paramType: api.PropertyType{"string", "number"},
+			raw:       "42.5",
+			want:      42.5,
+		},
+		{
+			desc:      "string or number union - non-numeric string",
+			paramType: api.PropertyType{"string", "number"},
+			raw:       "hello",
+			want:      "hello",
+		},
+		{
+			desc:      "number or string union - valid number (order shouldn't matter)",
+			paramType: api.PropertyType{"number", "string"},
+			raw:       "42.5",
+			want:      42.5,
+		},
+		{
+			desc:      "integer or null union - valid integer",
+			paramType: api.PropertyType{"integer", "null"},
+			raw:       "123",
+			want:      123,
+		},
+		{
+			desc:      "integer or null union - null value",
+			paramType: api.PropertyType{"integer", "null"},
+			raw:       "null",
+			want:      nil,
+		},
+		{
+			desc:      "null or integer union - null value (order shouldn't matter)",
+			paramType: api.PropertyType{"null", "integer"},
+			raw:       "null",
+			want:      nil,
+		},
+		{
+			desc:      "boolean or string union - valid boolean",
+			paramType: api.PropertyType{"boolean", "string"},
+			raw:       "true",
+			want:      true,
+		},
+		{
+			desc:      "boolean or string union - non-boolean becomes string",
+			paramType: api.PropertyType{"boolean", "string"},
+			raw:       "yes",
+			want:      "yes",
+		},
+		{
+			desc:      "string or boolean union - valid boolean (precedence test)",
+			paramType: api.PropertyType{"string", "boolean"},
+			raw:       "false",
+			want:      false, // Should be boolean, not string "false"
+		},
+		{
+			desc:      "integer or number union - integer value",
+			paramType: api.PropertyType{"integer", "number"},
+			raw:       "42",
+			want:      42,
+		},
+		{
+			desc:      "integer or number union - float value",
+			paramType: api.PropertyType{"integer", "number"},
+			raw:       "42.5",
+			want:      42.5,
+		},
+		{
+			desc:      "number or integer union - integer value (precedence test)",
+			paramType: api.PropertyType{"number", "integer"},
+			raw:       "42",
+			want:      42, // Should try integer first due to precedence
+		},
+		{
+			desc:      "array or object union - valid array",
+			paramType: api.PropertyType{"array", "object"},
+			raw:       `[1, 2, 3]`,
+			want:      []any{float64(1), float64(2), float64(3)},
+		},
+		{
+			desc:      "array or object union - valid object",
+			paramType: api.PropertyType{"array", "object"},
+			raw:       `{"key": "value"}`,
+			want:      map[string]any{"key": "value"},
+		},
+		{
+			desc:      "object or array union - valid array (precedence test)",
+			paramType: api.PropertyType{"object", "array"},
+			raw:       `[1, 2, 3]`,
+			want:      []any{float64(1), float64(2), float64(3)},
+		},
+		{
+			desc:      "complex multi-type union - null",
+			paramType: api.PropertyType{"string", "number", "boolean", "null"},
+			raw:       "null",
+			want:      nil,
+		},
+		{
+			desc:      "complex multi-type union - boolean",
+			paramType: api.PropertyType{"string", "number", "boolean", "null"},
+			raw:       "true",
+			want:      true,
+		},
+		{
+			desc:      "complex multi-type union - number",
+			paramType: api.PropertyType{"string", "number", "boolean", "null"},
+			raw:       "3.14",
+			want:      3.14,
+		},
+		{
+			desc:      "complex multi-type union - string",
+			paramType: api.PropertyType{"string", "number", "boolean", "null"},
+			raw:       "hello",
+			want:      "hello",
+		},
+		{
+			desc:      "integer string union - integer string becomes integer",
+			paramType: api.PropertyType{"integer", "string"},
+			raw:       "123",
+			want:      123,
+		},
+		{
+			desc:      "string integer union - integer string becomes integer (precedence)",
+			paramType: api.PropertyType{"string", "integer"},
+			raw:       "123",
+			want:      123, // Integer has higher precedence than string
+		},
+	}
+
+	for _, tc := range cases {
+		t.Run(tc.desc, func(t *testing.T) {
+			got := parseValue(tc.raw, tc.paramType)
+			if !reflect.DeepEqual(got, tc.want) {
+				t.Errorf("got %v (type %T), want %v (type %T)", got, got, tc.want, tc.want)
+			}
+		})
+	}
+}
+
+func TestQwenXMLTransform(t *testing.T) {
+	cases := []struct {
+		desc string
+		raw  string
+		want string
+	}{
+		{
+			desc: "simple example",
+			raw: `<function=get_current_temperature>
+<parameter=location>
+San Francisco
+</parameter>
+<parameter=unit>
+celsius
+</parameter>
+</function>`,
+			want: `<function name="get_current_temperature">
+<parameter name="location">
+San Francisco
+</parameter>
+<parameter name="unit">
+celsius
+</parameter>
+</function>`,
+		},
+		// even though quotes aren't expected in these tags, we have these tests to
+		// make sure they're escaped so they don't blow up the xml parser in case
+		// they happen
+		{
+			desc: "names with quotes",
+			raw: `<function="get current temperature">
+<parameter="location with spaces">
+San Francisco
+</parameter>
+<parameter="unit with spaces">
+celsius
+</parameter>
+</function>`,
+			want: `<function name="&#34;get current temperature&#34;">
+<parameter name="&#34;location with spaces&#34;">
+San Francisco
+</parameter>
+<parameter name="&#34;unit with spaces&#34;">
+celsius
+</parameter>
+</function>`,
+		},
+		{
+			desc: "ampersands in parameter values",
+			raw: `<function=get_current_temperature>
+		<parameter=location>
+		San Francisco & San Jose
+		</parameter>
+		</function>`,
+			want: `<function name="get_current_temperature">
+		<parameter name="location">
+		San Francisco &amp; San Jose
+		</parameter>
+		</function>`,
+		},
+	}
+
+	for _, tc := range cases {
+		got := transformToXML(tc.raw)
+		if got != tc.want {
+			t.Errorf("got %q, want %q", got, tc.want)
+		}
+	}
+}
+
+func TestTrailingWhitespaceLen(t *testing.T) {
+	cases := []struct {
+		desc string
+		s    string
+		want int
+	}{
+		{desc: "no whitespace", s: "abc", want: 0},
+		{desc: "trailing whitespace", s: "abc ", want: 1},
+		{desc: "trailing whitespace with newlines", s: "abc \n", want: 2},
+		{desc: "only whitespace", s: " \n  ", want: 4},
+		{desc: "leading whitespace doesn't count", s: " \n abc", want: 0},
+	}
+
+	for _, tc := range cases {
+		got := trailingWhitespaceLen(tc.s)
+		if got != tc.want {
+			t.Errorf("got %d, want %d", got, tc.want)
+		}
+	}
+}

model/renderers/qwen3coder.go

@@ -0,0 +1,217 @@
+package renderers
+
+import (
+	"encoding/json"
+	"fmt"
+	"reflect"
+	"strings"
+
+	"github.com/ollama/ollama/api"
+)
+
+var (
+	imStartTag = "<|im_start|>"
+	imEndTag   = "<|im_end|>"
+)
+
+// renderAdditionalKeys renders all JSON fields except the ones in handledKeys
+// This follows the same approach from the reference implementation, which gives
+// a particular key ordering
+func renderAdditionalKeys(obj any, handledKeys map[string]bool) string {
+	data, err := json.Marshal(obj)
+	if err != nil {
+		return ""
+	}
+
+	var m map[string]any
+	if err := json.Unmarshal(data, &m); err != nil {
+		return ""
+	}
+
+	var sb strings.Builder
+	for key, value := range m {
+		if handledKeys[key] {
+			continue
+		}
+
+		// Check if value is a map or array (needs JSON serialization)
+		switch v := value.(type) {
+		case map[string]any, []any:
+			jsonBytes, _ := json.Marshal(v)
+			// TODO(drifkin): it would be nice to format the JSON here similarly to
+			// python's default json.dumps behavior (spaces after commas and colons).
+			// This would let us be byte-for-byte compatible with the reference
+			// implementation for most common inputs
+			jsonStr := string(jsonBytes)
+			sb.WriteString("\n<" + key + ">" + jsonStr + "</" + key + ">")
+		case nil:
+			continue
+		default:
+			// Simple types, convert to string
+			sb.WriteString("\n<" + key + ">" + fmt.Sprintf("%v", value) + "</" + key + ">")
+		}
+	}
+
+	return sb.String()
+}
+
+func Qwen3CoderRenderer(messages []api.Message, tools []api.Tool, _ *api.ThinkValue) (string, error) {
+	var sb strings.Builder
+
+	// filter out system messages and choose the first (if any) to win
+	var systemMessage string
+	var filteredMessages []api.Message
+	for _, message := range messages {
+		if message.Role != "system" {
+			filteredMessages = append(filteredMessages, message)
+			continue
+		}
+
+		if systemMessage == "" {
+			systemMessage = message.Content
+		}
+	}
+
+	if systemMessage != "" || len(tools) > 0 {
+		sb.WriteString(imStartTag + "system\n")
+
+		// if we have tools but no system message, match the reference implementation by providing a default system message
+		if systemMessage == "" {
+			systemMessage = "You are Qwen, a helpful AI assistant that can interact with a computer to solve tasks."
+		}
+
+		sb.WriteString(systemMessage)
+
+		if len(tools) > 0 {
+			sb.WriteString("\n\n# Tools\n\nYou have access to the following functions:\n\n")
+			sb.WriteString("<tools>")
+			for _, tool := range tools {
+				sb.WriteString("\n")
+				sb.WriteString("<function>\n")
+				sb.WriteString("<name>" + tool.Function.Name + "</name>")
+				if tool.Function.Description != "" {
+					sb.WriteString("\n<description>" + tool.Function.Description + "</description>")
+				}
+				sb.WriteString("\n<parameters>")
+
+				for name, prop := range tool.Function.Parameters.Properties {
+					sb.WriteString("\n<parameter>")
+					sb.WriteString("\n<name>" + name + "</name>")
+
+					if len(prop.Type) > 0 {
+						// TODO(!!!)(drifkin): we should match the reference implementation for
+						// more complex types here instead of using this format
+						sb.WriteString("\n<type>" + prop.ToTypeScriptType() + "</type>")
+					}
+
+					if prop.Description != "" {
+						sb.WriteString("\n<description>" + prop.Description + "</description>")
+					}
+
+					// Render any additional keys not already handled
+					handledKeys := map[string]bool{
+						"type":        true,
+						"description": true,
+					}
+					sb.WriteString(renderAdditionalKeys(prop, handledKeys))
+
+					sb.WriteString("\n</parameter>")
+				}
+
+				// Render extra keys for parameters (everything except 'type' and 'properties')
+				paramHandledKeys := map[string]bool{
+					"type":       true,
+					"properties": true,
+				}
+				sb.WriteString(renderAdditionalKeys(tool.Function.Parameters, paramHandledKeys))
+
+				sb.WriteString("\n</parameters>")
+				sb.WriteString("\n</function>")
+			}
+			sb.WriteString("\n</tools>")
+			sb.WriteString("\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>")
+		}
+
+		sb.WriteString(imEndTag + "\n")
+	}
+
+	for i, message := range filteredMessages {
+		lastMessage := i == len(filteredMessages)-1
+		prefill := lastMessage && message.Role == "assistant"
+		switch message.Role {
+		case "assistant":
+			if len(message.ToolCalls) > 0 {
+				sb.WriteString(imStartTag + "assistant\n")
+				if message.Content != "" {
+					sb.WriteString(message.Content + "\n")
+				}
+				for _, toolCall := range message.ToolCalls {
+					sb.WriteString("\n<tool_call>\n<function=" + toolCall.Function.Name + ">")
+					for name, value := range toolCall.Function.Arguments {
+						valueStr := formatToolCallArgument(value)
+						sb.WriteString("\n<parameter=" + name + ">\n" + valueStr + "\n</parameter>")
+					}
+					sb.WriteString("\n</function>\n</tool_call>")
+				}
+				sb.WriteString("<|im_end|>\n")
+			} else {
+				sb.WriteString(imStartTag + "assistant\n")
+				sb.WriteString(message.Content)
+				if !prefill {
+					sb.WriteString(imEndTag + "\n")
+				}
+			}
+		case "tool":
+			// consecutive tool responses should share a single `<im_start>user`, but
+			// have their own <tool_response> tags
+
+			// only start a new user block if this is the first tool response
+			if i == 0 || filteredMessages[i-1].Role != "tool" {
+				sb.WriteString(imStartTag + "user\n")
+			}
+
+			sb.WriteString("<tool_response>\n")
+			sb.WriteString(message.Content)
+			sb.WriteString("\n</tool_response>\n")
+
+			// close the user block only if this is the last tool response
+			if i == len(filteredMessages)-1 || filteredMessages[i+1].Role != "tool" {
+				sb.WriteString(imEndTag + "\n")
+			}
+		default:
+			sb.WriteString(imStartTag + message.Role + "\n")
+			sb.WriteString(message.Content)
+			sb.WriteString(imEndTag + "\n")
+		}
+
+		if lastMessage && !prefill {
+			sb.WriteString(imStartTag + "assistant\n")
+		}
+	}
+
+	return sb.String(), nil
+}
+
+func formatToolCallArgument(value any) string {
+	if value == nil {
+		return "null"
+	}
+
+	switch v := value.(type) {
+	case string:
+		return v
+	case []byte:
+		return string(v)
+	}
+
+	if reflect.TypeOf(value) != nil {
+		kind := reflect.TypeOf(value).Kind()
+		if kind == reflect.Map || kind == reflect.Slice || kind == reflect.Array {
+			if marshalled, err := json.Marshal(value); err == nil {
+				return string(marshalled)
+			}
+		}
+	}
+
+	return fmt.Sprintf("%v", value)
+}

model/renderers/qwen3coder_test.go

@@ -0,0 +1,338 @@
+package renderers
+
+import (
+	"testing"
+
+	"github.com/google/go-cmp/cmp"
+	"github.com/ollama/ollama/api"
+)
+
+func TestQwen3CoderRenderer(t *testing.T) {
+	tests := []struct {
+		name     string
+		msgs     []api.Message
+		tools    []api.Tool
+		expected string
+	}{
+		{
+			name: "basic",
+			msgs: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant."},
+				{Role: "user", Content: "Hello, how are you?"},
+			},
+			expected: `<|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Hello, how are you?<|im_end|>
+<|im_start|>assistant
+`,
+		},
+		{
+			name: "with tools and response",
+			msgs: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant with access to tools."},
+				{Role: "user", Content: "What is the weather like in San Francisco?"},
+				{
+					Role:    "assistant",
+					Content: "I'll check the weather in San Francisco for you.",
+					ToolCalls: []api.ToolCall{
+						{
+							Function: api.ToolCallFunction{
+								Name: "get_weather",
+								Arguments: map[string]any{
+									"unit": "fahrenheit",
+								},
+							},
+						},
+					},
+				},
+				{Role: "tool", Content: "{\"location\": \"San Francisco, CA\", \"temperature\": 68, \"condition\": \"partly cloudy\", \"humidity\": 65, \"wind_speed\": 12}", ToolName: "get_weather"},
+				{Role: "user", Content: "That sounds nice! What about New York?"},
+			},
+			tools: []api.Tool{
+				{Function: api.ToolFunction{
+					Name:        "get_weather",
+					Description: "Get the current weather in a given location",
+					Parameters: api.ToolFunctionParameters{
+						Required: []string{"unit"},
+						Properties: map[string]api.ToolProperty{
+							"unit": {Type: api.PropertyType{"string"}, Enum: []any{"celsius", "fahrenheit"}, Description: "The unit of temperature"},
+							// TODO(drifkin): add multiple params back once we have predictable
+							// order via some sort of ordered map type (see
+							// <https://github.com/ollama/ollama/issues/12244>)
+							/*
+								"location": {Type: api.PropertyType{"string"}, Description: "The city and state, e.g. San Francisco, CA"},
+							*/
+						},
+					},
+				}},
+			},
+			expected: `<|im_start|>system
+You are a helpful assistant with access to tools.
+
+# Tools
+
+You have access to the following functions:
+
+<tools>
+<function>
+<name>get_weather</name>
+<description>Get the current weather in a given location</description>
+<parameters>
+<parameter>
+<name>unit</name>
+<type>string</type>
+<description>The unit of temperature</description>
+<enum>["celsius","fahrenheit"]</enum>
+</parameter>
+<required>["unit"]</required>
+</parameters>
+</function>
+</tools>
+
+If you choose to call a function ONLY reply in the following format with NO suffix:
+
+<tool_call>
+<function=example_function_name>
+<parameter=example_parameter_1>
+value_1
+</parameter>
+<parameter=example_parameter_2>
+This is the value for the second parameter
+that can span
+multiple lines
+</parameter>
+</function>
+</tool_call>
+
+<IMPORTANT>
+Reminder:
+- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
+- Required parameters MUST be specified
+- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
+- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
+</IMPORTANT><|im_end|>
+<|im_start|>user
+What is the weather like in San Francisco?<|im_end|>
+<|im_start|>assistant
+I'll check the weather in San Francisco for you.
+
+<tool_call>
+<function=get_weather>
+<parameter=unit>
+fahrenheit
+</parameter>
+</function>
+</tool_call><|im_end|>
+<|im_start|>user
+<tool_response>
+{"location": "San Francisco, CA", "temperature": 68, "condition": "partly cloudy", "humidity": 65, "wind_speed": 12}
+</tool_response>
+<|im_end|>
+<|im_start|>user
+That sounds nice! What about New York?<|im_end|>
+<|im_start|>assistant
+`,
+		},
+		{
+			name: "parallel tool calls",
+			msgs: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant with access to tools."},
+				{Role: "user", Content: "call double(1) and triple(2)"},
+				{Role: "assistant", Content: "I'll call double(1) and triple(2) for you.", ToolCalls: []api.ToolCall{
+					{Function: api.ToolCallFunction{Name: "double", Arguments: map[string]any{"number": "1"}}},
+					{Function: api.ToolCallFunction{Name: "triple", Arguments: map[string]any{"number": "2"}}},
+				}},
+				{Role: "tool", Content: "{\"number\": 2}", ToolName: "double"},
+				{Role: "tool", Content: "{\"number\": 6}", ToolName: "triple"},
+			},
+			tools: []api.Tool{
+				{Function: api.ToolFunction{Name: "double", Description: "Double a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
+					"number": {Type: api.PropertyType{"string"}, Description: "The number to double"},
+				}}}},
+				{Function: api.ToolFunction{Name: "triple", Description: "Triple a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
+					"number": {Type: api.PropertyType{"string"}, Description: "The number to triple"},
+				}}}},
+			},
+			expected: `<|im_start|>system
+You are a helpful assistant with access to tools.
+
+# Tools
+
+You have access to the following functions:
+
+<tools>
+<function>
+<name>double</name>
+<description>Double a number</description>
+<parameters>
+<parameter>
+<name>number</name>
+<type>string</type>
+<description>The number to double</description>
+</parameter>
+</parameters>
+</function>
+<function>
+<name>triple</name>
+<description>Triple a number</description>
+<parameters>
+<parameter>
+<name>number</name>
+<type>string</type>
+<description>The number to triple</description>
+</parameter>
+</parameters>
+</function>
+</tools>
+
+If you choose to call a function ONLY reply in the following format with NO suffix:
+
+<tool_call>
+<function=example_function_name>
+<parameter=example_parameter_1>
+value_1
+</parameter>
+<parameter=example_parameter_2>
+This is the value for the second parameter
+that can span
+multiple lines
+</parameter>
+</function>
+</tool_call>
+
+<IMPORTANT>
+Reminder:
+- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
+- Required parameters MUST be specified
+- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
+- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
+</IMPORTANT><|im_end|>
+<|im_start|>user
+call double(1) and triple(2)<|im_end|>
+<|im_start|>assistant
+I'll call double(1) and triple(2) for you.
+
+<tool_call>
+<function=double>
+<parameter=number>
+1
+</parameter>
+</function>
+</tool_call>
+<tool_call>
+<function=triple>
+<parameter=number>
+2
+</parameter>
+</function>
+</tool_call><|im_end|>
+<|im_start|>user
+<tool_response>
+{"number": 2}
+</tool_response>
+<tool_response>
+{"number": 6}
+</tool_response>
+<|im_end|>
+<|im_start|>assistant
+`,
+		},
+		{
+			name: "prefill",
+			msgs: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant."},
+				{Role: "user", Content: "Tell me something interesting."},
+				{Role: "assistant", Content: "I'll tell you something interesting about cats"},
+			},
+			expected: `<|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Tell me something interesting.<|im_end|>
+<|im_start|>assistant
+I'll tell you something interesting about cats`,
+		},
+		{
+			name: "complex tool call arguments should remain json encoded",
+			msgs: []api.Message{
+				{Role: "user", Content: "call tool"},
+				{Role: "assistant", ToolCalls: []api.ToolCall{
+					{Function: api.ToolCallFunction{
+						Name: "echo",
+						Arguments: map[string]any{
+							"payload": map[string]any{"foo": "bar"},
+						},
+					}},
+				}},
+				{Role: "tool", Content: "{\"payload\": {\"foo\": \"bar\"}}", ToolName: "echo"},
+			},
+			expected: `<|im_start|>user
+call tool<|im_end|>
+<|im_start|>assistant
+
+<tool_call>
+<function=echo>
+<parameter=payload>
+{"foo":"bar"}
+</parameter>
+</function>
+</tool_call><|im_end|>
+<|im_start|>user
+<tool_response>
+{"payload": {"foo": "bar"}}
+</tool_response>
+<|im_end|>
+<|im_start|>assistant
+`,
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			rendered, err := Qwen3CoderRenderer(tt.msgs, tt.tools, nil)
+			if err != nil {
+				t.Fatal(err)
+			}
+			if diff := cmp.Diff(rendered, tt.expected); diff != "" {
+				t.Errorf("mismatch (-got +want):\n%s", diff)
+			}
+		})
+	}
+}
+
+func TestFormatToolCallArgument(t *testing.T) {
+	tests := []struct {
+		name     string
+		arg      any
+		expected string
+	}{
+		{
+			name: "string",
+			arg:  "foo",
+			// notice no quotes around the string
+			expected: "foo",
+		},
+		{
+			name:     "map",
+			arg:      map[string]any{"foo": "bar"},
+			expected: "{\"foo\":\"bar\"}",
+		},
+		{
+			name:     "number",
+			arg:      1,
+			expected: "1",
+		},
+		{
+			name:     "boolean",
+			arg:      true,
+			expected: "true",
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got := formatToolCallArgument(tt.arg)
+			if got != tt.expected {
+				t.Errorf("formatToolCallArgument(%v) = %v, want %v", tt.arg, got, tt.expected)
+			}
+		})
+	}
+}

model/renderers/renderer.go

@@ -0,0 +1,26 @@
+package renderers
+
+import (
+	"fmt"
+
+	"github.com/ollama/ollama/api"
+)
+
+type rendererFunc func([]api.Message, []api.Tool, *api.ThinkValue) (string, error)
+
+func RenderWithRenderer(name string, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
+	renderer := rendererForName(name)
+	if renderer == nil {
+		return "", fmt.Errorf("unknown renderer %q", name)
+	}
+	return renderer(msgs, tools, think)
+}
+
+func rendererForName(name string) rendererFunc {
+	switch name {
+	case "qwen3-coder":
+		return Qwen3CoderRenderer
+	default:
+		return nil
+	}
+}

model/sentencepiece.go

@@ -12,18 +12,18 @@ import (
 
 const spmWhitespaceSep = "▁"
 
-type SentencePieceModel struct {
+type SentencePiece struct {
 	maxTokenLen int
 	vocab       *Vocabulary
 }
 
-var _ TextProcessor = (*SentencePieceModel)(nil)
+var _ TextProcessor = (*SentencePiece)(nil)
 
-func (spm SentencePieceModel) Vocabulary() *Vocabulary {
+func (spm SentencePiece) Vocabulary() *Vocabulary {
 	return spm.vocab
 }
 
-func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
+func NewSentencePiece(vocab *Vocabulary) SentencePiece {
 	logutil.Trace("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
 
 	counter := map[int]int{}
@@ -42,17 +42,17 @@ func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
 		"user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE],
 		"max token len", maxTokenLen)
 
-	return SentencePieceModel{
+	return SentencePiece{
 		maxTokenLen: maxTokenLen,
 		vocab:       vocab,
 	}
 }
 
-func (spm SentencePieceModel) Is(id int32, special Special) bool {
+func (spm SentencePiece) Is(id int32, special Special) bool {
 	return spm.vocab.Is(id, special)
 }
 
-func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) {
+func (spm SentencePiece) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range spm.vocab.SpecialVocabulary() {
 		id := spm.vocab.Encode(special)
@@ -218,7 +218,7 @@ func (q *queue) Pop() interface{} {
 	return item
 }
 
-func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
+func (spm SentencePiece) Decode(ids []int32) (string, error) {
 	var sb strings.Builder
 	for _, id := range ids {
 		data := spm.vocab.Decode(id)

model/sentencepiece_test.go

@@ -12,7 +12,7 @@ import (
 	"github.com/ollama/ollama/convert/sentencepiece"
 )
 
-func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
+func loadSentencePieceVocab(t *testing.T) SentencePiece {
 	t.Helper()
 
 	bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model"))
@@ -45,7 +45,7 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 		}
 	}
 
-	return NewSentencePieceModel(&v)
+	return NewSentencePiece(&v)
 }
 
 func TestSentencePieceEncode(t *testing.T) {
@@ -115,7 +115,7 @@ func TestSentencePieceEncode(t *testing.T) {
 	})
 }
 
-func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
+func TestSentencePieceDecodeByteTokens(t *testing.T) {
 	vocab := &Vocabulary{
 		Values: []string{
 			"normal",
@@ -134,7 +134,7 @@ func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
 		Scores: []float32{0, 0, 0, 0, 0},
 	}
 
-	spm := NewSentencePieceModel(vocab)
+	spm := NewSentencePiece(vocab)
 
 	tests := []struct {
 		name     string

model/wordpiece.go

@@ -0,0 +1,167 @@
+package model
+
+import (
+	"fmt"
+	"iter"
+	"strings"
+	"unicode"
+
+	"github.com/ollama/ollama/logutil"
+)
+
+type WordPiece struct {
+	vocab *Vocabulary
+}
+
+// ggmlPrefix is the prefix used by GGML vocabularies to indicate word boundaries.
+// this differs from original word piece which uses "##" to indicate subwords.
+const ggmlPrefix = "▁"
+
+var wordPieceReplacer = strings.NewReplacer(
+	" .", ".",
+	" ?", "?",
+	" !", "!",
+	" ,", ",",
+	" ' ", "'",
+	" n't", "n't",
+	" 'm", "'m",
+	" do not", " don't",
+	" 's", "'s",
+	" 've", "'ve",
+	" 're", "'re",
+)
+
+// Decode implements TextProcessor.
+func (wpm WordPiece) Decode(ids []int32) (string, error) {
+	var sb strings.Builder
+	for i, id := range ids {
+		if id < 0 || int(id) >= len(wpm.vocab.Values) {
+			return "", fmt.Errorf("invalid token id: %d", id)
+		}
+
+		var separator string
+		piece := wpm.vocab.Values[id]
+		if i > 0 &&
+			(strings.HasPrefix(piece, ggmlPrefix) ||
+				(strings.HasPrefix(piece, "[") && strings.HasSuffix(piece, "]"))) {
+			separator = " "
+		}
+
+		sb.WriteString(wordPieceReplacer.Replace(separator + strings.TrimPrefix(piece, ggmlPrefix)))
+	}
+
+	return sb.String(), nil
+}
+
+// words splits a string into words, treating CJK characters as separate words.
+// TODO: this is specifically for BERT and may need to be adjusted or refactored for other models.
+func (wpm WordPiece) words(s string) iter.Seq[string] {
+	return func(yield func(string) bool) {
+		runes := make([]rune, 0, len(s)*3)
+		for _, r := range s {
+			switch {
+			case r >= 0x4E00 && r <= 0x9FFF,
+				r >= 0x3400 && r <= 0x4DBF,
+				r >= 0x20000 && r <= 0x2A6DF,
+				r >= 0x2A700 && r <= 0x2B73F,
+				r >= 0x2B740 && r <= 0x2B81F,
+				r >= 0x2B820 && r <= 0x2CEAF,
+				r >= 0xF900 && r <= 0xFAFF,
+				r >= 0x2F800 && r <= 0x2FA1F:
+				runes = append(runes, ' ', r, ' ')
+			default:
+				runes = append(runes, r)
+			}
+		}
+
+		for w := range strings.FieldsFuncSeq(string(runes), unicode.IsSpace) {
+			// split on but keep punctuation
+			var start int
+			for start < len(w) {
+				end := strings.IndexFunc(w[start:], unicode.IsPunct)
+				if end < 0 {
+					end = len(w) - start
+				} else if end == 0 {
+					end = 1
+				}
+
+				if !yield(w[start : start+end]) {
+					return
+				}
+
+				start += end
+			}
+		}
+	}
+}
+
+// Encode implements TextProcessor.
+func (wpm WordPiece) Encode(s string, addSpecial bool) ([]int32, error) {
+	var ids []int32
+
+	// TODO: use [UNK] from config
+	unk := wpm.vocab.Encode("[UNK]")
+	for word := range wpm.words(s) {
+		var start int
+		var pieces []int32
+		for start < len(word) {
+			end := len(word)
+
+			var piece int32
+			for start < end {
+				subword := word[start:end]
+				if start == 0 {
+					subword = ggmlPrefix + subword
+				}
+
+				// TODO: some models might not want [ToLower]
+				piece = wpm.vocab.Encode(strings.ToLower(subword))
+				if piece >= 0 {
+					break
+				}
+
+				end--
+			}
+
+			if piece < 0 {
+				// Unknown token
+				pieces = pieces[:0]
+				break
+			}
+
+			pieces = append(pieces, piece)
+			start = end
+		}
+
+		if len(pieces) > 0 {
+			ids = append(ids, pieces...)
+		} else {
+			ids = append(ids, unk)
+		}
+	}
+
+	if addSpecial && len(ids) > 0 {
+		ids = wpm.vocab.addSpecials(ids)
+	}
+
+	logutil.Trace("encoded", "string", s, "ids", ids)
+	return ids, nil
+}
+
+// Is implements TextProcessor.
+func (wpm WordPiece) Is(id int32, special Special) bool {
+	return wpm.vocab.Is(id, special)
+}
+
+// Vocabulary implements TextProcessor.
+func (wpm WordPiece) Vocabulary() *Vocabulary {
+	return wpm.vocab
+}
+
+var _ TextProcessor = (*WordPiece)(nil)
+
+func NewWordPiece(vocab *Vocabulary) WordPiece {
+	return WordPiece{
+		vocab: vocab,
+	}
+}

model/wordpiece_test.go

@@ -0,0 +1,51 @@
+package model
+
+import (
+	"slices"
+	"testing"
+
+	"github.com/google/go-cmp/cmp"
+)
+
+func TestWordPiece(t *testing.T) {
+	wpm := NewWordPiece(
+		&Vocabulary{
+			Values: []string{"[UNK]", "[CLS]", "[SEP]", "▁hello", "▁world", "s", "▁!", "▁@", "▁#"},
+			AddBOS: true,
+			AddEOS: true,
+			BOS:    []int32{1},
+			EOS:    []int32{2},
+		})
+
+	ids, err := wpm.Encode("Hello world!", true)
+	if err != nil {
+		t.Fatal(err)
+	}
+
+	if diff := cmp.Diff([]int32{1, 3, 4, 6, 2}, ids); diff != "" {
+		t.Errorf("unexpected ids (-want +got):\n%s", diff)
+	}
+
+	words, err := wpm.Decode(ids)
+	if err != nil {
+		t.Fatal(err)
+	}
+
+	if diff := cmp.Diff("[CLS] hello world! [SEP]", words); diff != "" {
+		t.Errorf("unexpected words (-want +got):\n%s", diff)
+	}
+}
+
+func TestWordPieceWords(t *testing.T) {
+	var wpm WordPiece
+
+	basic := slices.Collect(wpm.words("Hey friend!     How are you?!?"))
+	if diff := cmp.Diff([]string{"Hey", "friend", "!", "How", "are", "you", "?", "!", "?"}, basic); diff != "" {
+		t.Errorf("unexpected words (-want +got):\n%s", diff)
+	}
+
+	chinese := slices.Collect(wpm.words("野口里佳 Noguchi Rika"))
+	if diff := cmp.Diff([]string{"野", "口", "里", "佳", "Noguchi", "Rika"}, chinese); diff != "" {
+		t.Errorf("unexpected words (-want +got):\n%s", diff)
+	}
+}

openai/openai.go

@@ -76,8 +76,9 @@ type JsonSchema struct {
 }
 
 type EmbedRequest struct {
-	Input any    `json:"input"`
-	Model string `json:"model"`
+	Input      any    `json:"input"`
+	Model      string `json:"model"`
+	Dimensions int    `json:"dimensions,omitempty"`
 }
 
 type StreamOptions struct {
@@ -104,16 +105,18 @@ type ChatCompletionRequest struct {
 	Tools            []api.Tool      `json:"tools"`
 	Reasoning        *Reasoning      `json:"reasoning,omitempty"`
 	ReasoningEffort  *string         `json:"reasoning_effort,omitempty"`
+	DebugRenderOnly  bool            `json:"_debug_render_only"`
 }
 
 type ChatCompletion struct {
-	Id                string   `json:"id"`
-	Object            string   `json:"object"`
-	Created           int64    `json:"created"`
-	Model             string   `json:"model"`
-	SystemFingerprint string   `json:"system_fingerprint"`
-	Choices           []Choice `json:"choices"`
-	Usage             Usage    `json:"usage,omitempty"`
+	Id                string         `json:"id"`
+	Object            string         `json:"object"`
+	Created           int64          `json:"created"`
+	Model             string         `json:"model"`
+	SystemFingerprint string         `json:"system_fingerprint"`
+	Choices           []Choice       `json:"choices"`
+	Usage             Usage          `json:"usage,omitempty"`
+	DebugInfo         *api.DebugInfo `json:"_debug_info,omitempty"`
 }
 
 type ChatCompletionChunk struct {
@@ -140,6 +143,7 @@ type CompletionRequest struct {
 	Temperature      *float32       `json:"temperature"`
 	TopP             float32        `json:"top_p"`
 	Suffix           string         `json:"suffix"`
+	DebugRenderOnly  bool           `json:"_debug_render_only"`
 }
 
 type Completion struct {
@@ -272,8 +276,8 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 				}
 				return nil
 			}(r.DoneReason),
-		}},
-		Usage: toUsage(r),
+		}}, Usage: toUsage(r),
+		DebugInfo: r.DebugInfo,
 	}
 }
 
@@ -567,13 +571,14 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 	}
 
 	return &api.ChatRequest{
-		Model:    r.Model,
-		Messages: messages,
-		Format:   format,
-		Options:  options,
-		Stream:   &r.Stream,
-		Tools:    r.Tools,
-		Think:    think,
+		Model:           r.Model,
+		Messages:        messages,
+		Format:          format,
+		Options:         options,
+		Stream:          &r.Stream,
+		Tools:           r.Tools,
+		Think:           think,
+		DebugRenderOnly: r.DebugRenderOnly,
 	}, nil
 }
 
@@ -647,11 +652,12 @@ func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
 	}
 
 	return api.GenerateRequest{
-		Model:   r.Model,
-		Prompt:  r.Prompt,
-		Options: options,
-		Stream:  &r.Stream,
-		Suffix:  r.Suffix,
+		Model:           r.Model,
+		Prompt:          r.Prompt,
+		Options:         options,
+		Stream:          &r.Stream,
+		Suffix:          r.Suffix,
+		DebugRenderOnly: r.DebugRenderOnly,
 	}, nil
 }
 
@@ -1005,7 +1011,7 @@ func EmbeddingsMiddleware() gin.HandlerFunc {
 		}
 
 		var b bytes.Buffer
-		if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input}); err != nil {
+		if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input, Dimensions: req.Dimensions}); err != nil {
 			c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
 			return
 		}

parser/parser.go

@@ -100,6 +100,10 @@ func (f Modelfile) CreateRequest(relativeDir string) (*api.CreateRequest, error)
 			req.System = c.Args
 		case "license":
 			licenses = append(licenses, c.Args)
+		case "renderer":
+			req.Renderer = c.Args
+		case "parser":
+			req.Parser = c.Args
 		case "message":
 			role, msg, _ := strings.Cut(c.Args, ": ")
 			messages = append(messages, api.Message{Role: role, Content: msg})
@@ -246,7 +250,7 @@ func filesForModel(path string) ([]string, error) {
 		for _, match := range matches {
 			if ct, err := detectContentType(match); err != nil {
 				return nil, err
-			} else if ct != contentType {
+			} else if len(contentType) > 0 && ct != contentType {
 				return nil, fmt.Errorf("invalid content type: expected %s for %s", ct, match)
 			}
 		}
@@ -255,7 +259,8 @@ func filesForModel(path string) ([]string, error) {
 	}
 
 	var files []string
-	if st, _ := glob(filepath.Join(path, "*.safetensors"), "application/octet-stream"); len(st) > 0 {
+	// some safetensors files do not properly match "application/octet-stream", so skip checking their contentType
+	if st, _ := glob(filepath.Join(path, "*.safetensors"), ""); len(st) > 0 {
 		// safetensors files might be unresolved git lfs references; skip if they are
 		// covers model-x-of-y.safetensors, model.fp32-x-of-y.safetensors, model.safetensors
 		files = append(files, st...)
@@ -319,7 +324,7 @@ func (c Command) String() string {
 	switch c.Name {
 	case "model":
 		fmt.Fprintf(&sb, "FROM %s", c.Args)
-	case "license", "template", "system", "adapter":
+	case "license", "template", "system", "adapter", "renderer", "parser":
 		fmt.Fprintf(&sb, "%s %s", strings.ToUpper(c.Name), quote(c.Args))
 	case "message":
 		role, message, _ := strings.Cut(c.Args, ": ")
@@ -345,7 +350,7 @@ const (
 var (
 	errMissingFrom        = errors.New("no FROM line")
 	errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"")
-	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
+	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"renderer\", \"parser\", \"parameter\", or \"message\"")
 )
 
 type ParserError struct {
@@ -605,7 +610,7 @@ func isValidMessageRole(role string) bool {
 
 func isValidCommand(cmd string) bool {
 	switch strings.ToLower(cmd) {
-	case "from", "license", "template", "system", "adapter", "parameter", "message":
+	case "from", "license", "template", "system", "adapter", "renderer", "parser", "parameter", "message":
 		return true
 	default:
 		return false

parser/parser_test.go

@@ -198,6 +198,34 @@ BADCOMMAND param1 value1
 	}
 }
 
+func TestParseFileRenderer(t *testing.T) {
+	input := `
+FROM foo
+RENDERER renderer1
+`
+
+	reader := strings.NewReader(input)
+
+	modelfile, err := ParseFile(reader)
+	require.NoError(t, err)
+
+	assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "renderer", Args: "renderer1"}}, modelfile.Commands)
+}
+
+func TestParseFileParser(t *testing.T) {
+	input := `
+FROM foo
+PARSER parser1
+`
+
+	reader := strings.NewReader(input)
+
+	modelfile, err := ParseFile(reader)
+	require.NoError(t, err)
+
+	assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "parser", Args: "parser1"}}, modelfile.Commands)
+}
+
 func TestParseFileMessages(t *testing.T) {
 	cases := []struct {
 		input    string

runner/llamarunner/cache.go

@@ -204,13 +204,8 @@ func (c *InputCache) ShiftDiscard(inputLen int, numKeep int) int {
 	targetFree = max(targetFree, 1)
 
 	currentFree := c.numCtx - inputLen
-	discard := targetFree - currentFree
 
-	if discard < 0 {
-		discard = 0
-	}
-
-	return discard
+	return max(targetFree-currentFree, 0)
 }
 
 type ErrReprocessInputs struct {

runner/ollamarunner/cache.go

@@ -34,8 +34,8 @@ type InputCache struct {
 func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, batchSize int, multiUserCache bool) (*InputCache, error) {
 	numCtx := kvSize / int32(numSlots)
 
-	if numCtx < 1 {
-		return nil, fmt.Errorf("must have at least one kv cache entry per parallel sequence (kv: %v parallel: %v)", kvSize, numSlots)
+	if int(numCtx) < batchSize {
+		return nil, fmt.Errorf("kv size must be at least as large as batch size * parallel (kv: %v batch: %v parallel: %v)", kvSize, batchSize, numSlots)
 	}
 
 	slots := make([]InputCacheSlot, numSlots)
@@ -70,11 +70,9 @@ func kvCacheTypeFromStr(s string) ml.DType {
 }
 
 func (c *InputCache) Close() {
-	if c == nil {
-		return
+	if c != nil && c.cache != nil {
+		c.cache.Close()
 	}
-
-	c.cache.Close()
 }
 
 // Locking: Operations on InputCacheSlot (including finding one
@@ -244,13 +242,8 @@ func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	targetFree = max(targetFree, 1)
 
 	currentFree := c.numCtx - inputLen
-	discard := targetFree - currentFree
 
-	if discard < 0 {
-		discard = 0
-	}
-
-	return discard
+	return max(targetFree-currentFree, 0)
 }
 
 type ErrReprocessInputs struct {

runner/ollamarunner/runner.go

@@ -11,14 +11,12 @@ import (
 	"image"
 	"log"
 	"log/slog"
-	"math"
 	"net"
 	"net/http"
 	"os"
 	"reflect"
 	"regexp"
 	"runtime"
-	"runtime/debug"
 	"strconv"
 	"strings"
 	"sync"
@@ -33,6 +31,7 @@ import (
 	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/logutil"
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn/pooling"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
 	"github.com/ollama/ollama/runner/common"
@@ -406,7 +405,7 @@ func (s *Server) removeSequence(seqIndex int, reason llm.DoneReason) {
 func (s *Server) run(ctx context.Context) {
 	s.ready.Wait()
 
-	supportsAsync := s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32
+	supportsAsync := pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone
 
 	var activeBatch batchState
 	for {
@@ -468,6 +467,7 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 
 	// Prepare the seqs and batch, but defer the input token values as we may not be ready yet
 	var batchInputs []*input.Input
+	var batchOutputs []int32
 	var batch input.Batch
 
 	resumeSeq := -1
@@ -550,9 +550,9 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 			batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
 			batch.Sequences = append(batch.Sequences, seq.cache.Id)
 
-			seq.iBatch = len(batch.Outputs)
-			if i+1 == len(seq.inputs) {
-				batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1))
+			seq.iBatch = len(batchOutputs)
+			if i+1 == len(seq.inputs) || seq.embeddingOnly {
+				batchOutputs = append(batchOutputs, int32(len(batchInputs)-1))
 			}
 			logutil.Trace("forwardBatch iBatch", "batchID", s.batchID, "seqIdx", seqIdx, "seq.iBatch", seq.iBatch, "i+1", i+1, "len(seq.inputs)", len(seq.inputs))
 			seq.pendingInputs = append(seq.pendingInputs, inp)
@@ -577,6 +577,7 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 
 	// Actual batchInputs values will be injected into the batch.Inputs tensor before calling Compute
 	batch.Inputs = nextBatch.ctx.Input().Empty(ml.DTypeI32, len(batchInputs))
+	batch.Outputs = nextBatch.ctx.Input().FromIntSlice(batchOutputs, len(batchOutputs))
 	nextBatch.modelOutput, err = model.Forward(nextBatch.ctx, s.model, batch)
 	if err != nil {
 		err = fmt.Errorf("failed to build graph: %w", err)
@@ -704,8 +705,8 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		}
 
 		// sample a token
-		vocabSize := len(outputs) / len(activeBatch.batch.Outputs)
-		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", len(activeBatch.batch.Outputs), "vocabSize", vocabSize, "iBatches", iBatches)
+		vocabSize := len(outputs) / activeBatch.batch.Outputs.Dim(0)
+		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", activeBatch.batch.Outputs.Dim(0), "vocabSize", vocabSize, "iBatches", iBatches)
 		token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize])
 		if err != nil {
 			s.hardErrCh <- fmt.Errorf("failed to sample token: %w", err)
@@ -899,7 +900,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 }
 
 func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
-	if s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32 {
+	if pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone {
 		http.Error(w, "this model does not support embeddings", http.StatusNotImplemented)
 		return
 	}
@@ -1047,12 +1048,8 @@ func (s *Server) reserveWorstCaseGraph() error {
 		batch.Positions[i] = int32(i)
 	}
 
-	batch.Outputs = make([]int32, s.parallel)
-	for i := range batch.Outputs {
-		batch.Outputs[i] = int32(i)
-	}
-
 	batch.Inputs = ctx.Input().FromIntSlice(batchInputs, len(batchInputs))
+	batch.Outputs = ctx.Input().Empty(ml.DTypeI32, s.parallel)
 
 	cache := s.model.Config().Cache
 	if cache != nil {
@@ -1086,9 +1083,13 @@ func (s *Server) allocModel(
 	// Convert memory allocation panics to errors
 	defer func() {
 		if r := recover(); r != nil {
-			debug.PrintStack()
 			if err, ok := r.(error); ok {
-				panicErr = err
+				var noMem ml.ErrNoMem
+				if errors.As(err, &noMem) {
+					panicErr = noMem
+				} else {
+					panic(r)
+				}
 			} else {
 				panic(r)
 			}

scripts/build_windows.ps1

@@ -78,7 +78,7 @@ function checkEnv() {
 }
 
 
-function buildOllama() {
+function buildCPU() {
     mkdir -Force -path "${script:DIST_DIR}\"
     if ($script:ARCH -ne "arm64") {
         Remove-Item -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}"
@@ -90,20 +90,72 @@ function buildOllama() {
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         & cmake --install build --component CPU --strip
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+    }
+}
 
+function buildCUDA11() {
+    # CUDA v11 claims to be compatible with MSVC 2022, but the latest updates are no longer compatible
+    # 19.40 is the last compiler version that works, but recent udpates are 19.43
+    # So this pins to MSVC 2019 for best compatibility
+    mkdir -Force -path "${script:DIST_DIR}\"
+    if ($script:ARCH -ne "arm64") {
         $hashEnv = @{}
         Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
-        if ("$script:CUDA_DIRS".Contains("v12")) {
-            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V12")) { $v12="$_" }}
-            $env:CUDAToolkit_ROOT=$hashEnv[$v12]
-            write-host "Building CUDA v12 backend libraries"
-            & cmake --fresh --preset "CUDA 12" --install-prefix $script:DIST_DIR
+        if ("$script:CUDA_DIRS".Contains("v11")) {
+            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V11")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
+            write-host "Building CUDA v11 backend libraries $cuda"
+            $env:CUDAToolkit_ROOT=$cuda
+            & cmake --fresh --preset "CUDA 11" -T cuda="$cuda" -DCMAKE_CUDA_COMPILER="$cuda\bin\nvcc.exe" -G "Visual Studio 16 2019" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v11"
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+            & cmake --build --preset "CUDA 11"  --config Release --parallel $script:JOBS
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+            & cmake --install build --component "CUDA" --strip
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+        }
+    }
+}
+
+function buildCUDA12() {
+    mkdir -Force -path "${script:DIST_DIR}\"
+    if ($script:ARCH -ne "arm64") {
+        $hashEnv = @{}
+        Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
+        if ("$script:CUDA_DIRS".Contains("v12.8")) {
+            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V12_8")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
+            write-host "Building CUDA v12 backend libraries $cuda"
+            $env:CUDAToolkit_ROOT=$cuda
+            & cmake --fresh --preset "CUDA 12" -T cuda="$cuda" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v12"
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --build --preset "CUDA 12"  --config Release --parallel $script:JOBS
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --install build --component "CUDA" --strip
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         }
+    }
+}
+
+function buildCUDA13() {
+    mkdir -Force -path "${script:DIST_DIR}\"
+    if ($script:ARCH -ne "arm64") {
+        $hashEnv = @{}
+        Get-ChildItem env: | foreach { $hashEnv[$_.Name] = $_.Value }
+        if ("$script:CUDA_DIRS".Contains("v13")) {
+            $hashEnv.Keys | foreach { if ($_.Contains("CUDA_PATH_V13")) { $x=$hashEnv[$_]; if (test-path -literalpath "$x\bin\nvcc.exe" ) { $cuda=$x}  }}
+            $env:CUDAToolkit_ROOT=$cuda
+            write-host "Building CUDA v13 backend libraries $cuda"
+            & cmake --fresh --preset "CUDA 13" -T cuda="$cuda" --install-prefix $script:DIST_DIR -DOLLAMA_RUNNER_DIR="cuda_v13"
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+            & cmake --build --preset "CUDA 13"  --config Release --parallel $script:JOBS
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+            & cmake --install build --component "CUDA" --strip
+            if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
+        }
+    }
+}
+
+function buildROCm() {
+    mkdir -Force -path "${script:DIST_DIR}\"
+    if ($script:ARCH -ne "arm64") {
         if ($env:HIP_PATH) {
             write-host "Building ROCm backend libraries"
             if (-Not (get-command -ErrorAction silent ninja)) {
@@ -129,6 +181,10 @@ function buildOllama() {
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         }
     }
+}
+
+function buildOllama() {
+    mkdir -Force -path "${script:DIST_DIR}\"
     write-host "Building ollama CLI"
     & go build -trimpath -ldflags "-s -w -X=github.com/ollama/ollama/version.Version=$script:VERSION -X=github.com/ollama/ollama/server.mode=release" .
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -236,6 +292,10 @@ function distZip() {
 checkEnv
 try {
     if ($($args.count) -eq 0) {
+        buildCPU
+        buildCUDA12
+        buildCUDA13
+        buildROCm
         buildOllama
         buildApp
         gatherDependencies

scripts/env.sh

@@ -16,6 +16,7 @@ OLLAMA_COMMON_BUILD_ARGS="--build-arg=VERSION \
     --build-arg=OLLAMA_FAST_BUILD \
     --build-arg=CUSTOM_CPU_FLAGS \
     --build-arg=GPU_RUNNER_CPU_FLAGS \
+    --build-arg=PARALLEL \
     --build-arg=AMDGPU_TARGETS"
 
 echo "Building Ollama"

server/create.go

@@ -10,8 +10,11 @@ import (
 	"io"
 	"io/fs"
 	"log/slog"
+	"net"
 	"net/http"
+	"net/url"
 	"os"
+	"path"
 	"path/filepath"
 	"slices"
 	"strings"
@@ -39,6 +42,14 @@ var (
 )
 
 func (s *Server) CreateHandler(c *gin.Context) {
+	config := &ConfigV2{
+		OS:           "linux",
+		Architecture: "amd64",
+		RootFS: RootFS{
+			Type: "layers",
+		},
+	}
+
 	var r api.CreateRequest
 	if err := c.ShouldBindJSON(&r); errors.Is(err, io.EOF) {
 		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
@@ -48,6 +59,9 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		return
 	}
 
+	config.Renderer = r.Renderer
+	config.Parser = r.Parser
+
 	for v := range r.Files {
 		if !fs.ValidPath(v) {
 			c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": errFilePath.Error()})
@@ -77,20 +91,34 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		oldManifest, _ := ParseNamedManifest(name)
 
 		var baseLayers []*layerGGML
+		var err error
+		var remote bool
+
 		if r.From != "" {
-			slog.Debug("create model from model name")
+			slog.Debug("create model from model name", "from", r.From)
 			fromName := model.ParseName(r.From)
 			if !fromName.IsValid() {
 				ch <- gin.H{"error": errtypes.InvalidModelNameErrMsg, "status": http.StatusBadRequest}
 				return
 			}
+			if r.RemoteHost != "" {
+				ru, err := remoteURL(r.RemoteHost)
+				if err != nil {
+					ch <- gin.H{"error": "bad remote", "status": http.StatusBadRequest}
+					return
+				}
 
-			ctx, cancel := context.WithCancel(c.Request.Context())
-			defer cancel()
+				config.RemoteModel = r.From
+				config.RemoteHost = ru
+				remote = true
+			} else {
+				ctx, cancel := context.WithCancel(c.Request.Context())
+				defer cancel()
 
-			baseLayers, err = parseFromModel(ctx, fromName, fn)
-			if err != nil {
-				ch <- gin.H{"error": err.Error()}
+				baseLayers, err = parseFromModel(ctx, fromName, fn)
+				if err != nil {
+					ch <- gin.H{"error": err.Error()}
+				}
 			}
 		} else if r.Files != nil {
 			baseLayers, err = convertModelFromFiles(r.Files, baseLayers, false, fn)
@@ -110,7 +138,7 @@ func (s *Server) CreateHandler(c *gin.Context) {
 		}
 
 		var adapterLayers []*layerGGML
-		if r.Adapters != nil {
+		if !remote && r.Adapters != nil {
 			adapterLayers, err = convertModelFromFiles(r.Adapters, baseLayers, true, fn)
 			if err != nil {
 				for _, badReq := range []error{errNoFilesProvided, errOnlyOneAdapterSupported, errOnlyGGUFSupported, errUnknownType, errFilePath} {
@@ -128,7 +156,56 @@ func (s *Server) CreateHandler(c *gin.Context) {
 			baseLayers = append(baseLayers, adapterLayers...)
 		}
 
-		if err := createModel(r, name, baseLayers, fn); err != nil {
+		// Info is not currently exposed by Modelfiles, but allows overriding various
+		// config values
+		if r.Info != nil {
+			caps, ok := r.Info["capabilities"]
+			if ok {
+				switch tcaps := caps.(type) {
+				case []any:
+					caps := make([]string, len(tcaps))
+					for i, c := range tcaps {
+						str, ok := c.(string)
+						if !ok {
+							continue
+						}
+						caps[i] = str
+					}
+					config.Capabilities = append(config.Capabilities, caps...)
+				}
+			}
+
+			strFromInfo := func(k string) string {
+				v, ok := r.Info[k]
+				if ok {
+					val := v.(string)
+					return val
+				}
+				return ""
+			}
+
+			vFromInfo := func(k string) float64 {
+				v, ok := r.Info[k]
+				if ok {
+					val := v.(float64)
+					return val
+				}
+				return 0
+			}
+
+			config.ModelFamily = strFromInfo("model_family")
+			if config.ModelFamily != "" {
+				config.ModelFamilies = []string{config.ModelFamily}
+			}
+
+			config.BaseName = strFromInfo("base_name")
+			config.FileType = strFromInfo("quantization_level")
+			config.ModelType = strFromInfo("parameter_size")
+			config.ContextLen = int(vFromInfo("context_length"))
+			config.EmbedLen = int(vFromInfo("embedding_length"))
+		}
+
+		if err := createModel(r, name, baseLayers, config, fn); err != nil {
 			if errors.Is(err, errBadTemplate) {
 				ch <- gin.H{"error": err.Error(), "status": http.StatusBadRequest}
 				return
@@ -154,6 +231,51 @@ func (s *Server) CreateHandler(c *gin.Context) {
 	streamResponse(c, ch)
 }
 
+func remoteURL(raw string) (string, error) {
+	// Special‑case: user supplied only a path ("/foo/bar").
+	if strings.HasPrefix(raw, "/") {
+		return (&url.URL{
+			Scheme: "http",
+			Host:   net.JoinHostPort("localhost", "11434"),
+			Path:   path.Clean(raw),
+		}).String(), nil
+	}
+
+	if !strings.Contains(raw, "://") {
+		raw = "http://" + raw
+	}
+
+	if raw == "ollama.com" || raw == "http://ollama.com" {
+		raw = "https://ollama.com:443"
+	}
+
+	u, err := url.Parse(raw)
+	if err != nil {
+		return "", fmt.Errorf("parse error: %w", err)
+	}
+
+	if u.Host == "" {
+		u.Host = "localhost"
+	}
+
+	hostPart, portPart, err := net.SplitHostPort(u.Host)
+	if err == nil {
+		u.Host = net.JoinHostPort(hostPart, portPart)
+	} else {
+		u.Host = net.JoinHostPort(u.Host, "11434")
+	}
+
+	if u.Path != "" {
+		u.Path = path.Clean(u.Path)
+	}
+
+	if u.Path == "/" {
+		u.Path = ""
+	}
+
+	return u.String(), nil
+}
+
 func convertModelFromFiles(files map[string]string, baseLayers []*layerGGML, isAdapter bool, fn func(resp api.ProgressResponse)) ([]*layerGGML, error) {
 	switch detectModelTypeFromFiles(files) {
 	case "safetensors":
@@ -316,15 +438,7 @@ func kvFromLayers(baseLayers []*layerGGML) (ggml.KV, error) {
 	return ggml.KV{}, fmt.Errorf("no base model was found")
 }
 
-func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, fn func(resp api.ProgressResponse)) (err error) {
-	config := ConfigV2{
-		OS:           "linux",
-		Architecture: "amd64",
-		RootFS: RootFS{
-			Type: "layers",
-		},
-	}
-
+func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, config *ConfigV2, fn func(resp api.ProgressResponse)) (err error) {
 	var layers []Layer
 	for _, layer := range baseLayers {
 		if layer.GGML != nil {
@@ -404,7 +518,7 @@ func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML,
 		return err
 	}
 
-	configLayer, err := createConfigLayer(layers, config)
+	configLayer, err := createConfigLayer(layers, *config)
 	if err != nil {
 		return err
 	}

server/create_test.go

@@ -104,3 +104,154 @@ func TestConvertFromSafetensors(t *testing.T) {
 		})
 	}
 }
+
+func TestRemoteURL(t *testing.T) {
+	tests := []struct {
+		name     string
+		input    string
+		expected string
+		hasError bool
+	}{
+		{
+			name:     "absolute path",
+			input:    "/foo/bar",
+			expected: "http://localhost:11434/foo/bar",
+			hasError: false,
+		},
+		{
+			name:     "absolute path with cleanup",
+			input:    "/foo/../bar",
+			expected: "http://localhost:11434/bar",
+			hasError: false,
+		},
+		{
+			name:     "root path",
+			input:    "/",
+			expected: "http://localhost:11434/",
+			hasError: false,
+		},
+		{
+			name:     "host without scheme",
+			input:    "example.com",
+			expected: "http://example.com:11434",
+			hasError: false,
+		},
+		{
+			name:     "host with port",
+			input:    "example.com:8080",
+			expected: "http://example.com:8080",
+			hasError: false,
+		},
+		{
+			name:     "full URL",
+			input:    "https://example.com:8080/path",
+			expected: "https://example.com:8080/path",
+			hasError: false,
+		},
+		{
+			name:     "full URL with path cleanup",
+			input:    "https://example.com:8080/path/../other",
+			expected: "https://example.com:8080/other",
+			hasError: false,
+		},
+		{
+			name:     "ollama.com special case",
+			input:    "ollama.com",
+			expected: "https://ollama.com:443",
+			hasError: false,
+		},
+		{
+			name:     "http ollama.com special case",
+			input:    "http://ollama.com",
+			expected: "https://ollama.com:443",
+			hasError: false,
+		},
+		{
+			name:     "URL with only host",
+			input:    "http://example.com",
+			expected: "http://example.com:11434",
+			hasError: false,
+		},
+		{
+			name:     "URL with root path cleaned",
+			input:    "http://example.com/",
+			expected: "http://example.com:11434",
+			hasError: false,
+		},
+		{
+			name:     "invalid URL",
+			input:    "http://[::1]:namedport", // invalid port
+			expected: "",
+			hasError: true,
+		},
+		{
+			name:     "empty string",
+			input:    "",
+			expected: "http://localhost:11434",
+			hasError: false,
+		},
+		{
+			name:     "host with scheme but no port",
+			input:    "http://localhost",
+			expected: "http://localhost:11434",
+			hasError: false,
+		},
+		{
+			name:     "complex path cleanup",
+			input:    "/a/b/../../c/./d",
+			expected: "http://localhost:11434/c/d",
+			hasError: false,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result, err := remoteURL(tt.input)
+
+			if tt.hasError {
+				if err == nil {
+					t.Errorf("expected error but got none")
+				}
+				return
+			}
+
+			if err != nil {
+				t.Errorf("unexpected error: %v", err)
+				return
+			}
+
+			if result != tt.expected {
+				t.Errorf("expected %q, got %q", tt.expected, result)
+			}
+		})
+	}
+}
+
+func TestRemoteURL_Idempotent(t *testing.T) {
+	// Test that applying remoteURL twice gives the same result as applying it once
+	testInputs := []string{
+		"/foo/bar",
+		"example.com",
+		"https://example.com:8080/path",
+		"ollama.com",
+		"http://localhost:11434",
+	}
+
+	for _, input := range testInputs {
+		t.Run(input, func(t *testing.T) {
+			firstResult, err := remoteURL(input)
+			if err != nil {
+				t.Fatalf("first call failed: %v", err)
+			}
+
+			secondResult, err := remoteURL(firstResult)
+			if err != nil {
+				t.Fatalf("second call failed: %v", err)
+			}
+
+			if firstResult != secondResult {
+				t.Errorf("function is not idempotent: first=%q, second=%q", firstResult, secondResult)
+			}
+		})
+	}
+}

server/images.go

@@ -24,6 +24,7 @@ import (
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/fs/gguf"
+	"github.com/ollama/ollama/model/parsers"
 	"github.com/ollama/ollama/parser"
 	"github.com/ollama/ollama/template"
 	"github.com/ollama/ollama/thinking"
@@ -73,29 +74,38 @@ func (m *Model) Capabilities() []model.Capability {
 	capabilities := []model.Capability{}
 
 	// Check for completion capability
-	f, err := gguf.Open(m.ModelPath)
-	if err == nil {
-		defer f.Close()
+	if m.ModelPath != "" {
+		f, err := gguf.Open(m.ModelPath)
+		if err == nil {
+			defer f.Close()
 
-		if f.KeyValue("pooling_type").Valid() {
-			capabilities = append(capabilities, model.CapabilityEmbedding)
+			if f.KeyValue("pooling_type").Valid() {
+				capabilities = append(capabilities, model.CapabilityEmbedding)
+			} else {
+				// If no embedding is specified, we assume the model supports completion
+				capabilities = append(capabilities, model.CapabilityCompletion)
+			}
+			if f.KeyValue("vision.block_count").Valid() {
+				capabilities = append(capabilities, model.CapabilityVision)
+			}
 		} else {
-			// If no embedding is specified, we assume the model supports completion
-			capabilities = append(capabilities, model.CapabilityCompletion)
+			slog.Error("couldn't open model file", "error", err)
 		}
-		if f.KeyValue("vision.block_count").Valid() {
-			capabilities = append(capabilities, model.CapabilityVision)
+	} else if len(m.Config.Capabilities) > 0 {
+		for _, c := range m.Config.Capabilities {
+			capabilities = append(capabilities, model.Capability(c))
 		}
 	} else {
-		slog.Error("couldn't open model file", "error", err)
+		slog.Warn("unknown capabilities for model", "model", m.Name)
 	}
 
 	if m.Template == nil {
 		return capabilities
 	}
 
+	builtinParser := parsers.ParserForName(m.Config.Parser)
 	// Check for tools capability
-	if slices.Contains(m.Template.Vars(), "tools") {
+	if slices.Contains(m.Template.Vars(), "tools") || (builtinParser != nil && builtinParser.HasToolSupport()) {
 		capabilities = append(capabilities, model.CapabilityTools)
 	}
 
@@ -109,10 +119,16 @@ func (m *Model) Capabilities() []model.Capability {
 		capabilities = append(capabilities, model.CapabilityVision)
 	}
 
+	// Skip the thinking check if it's already set
+	if slices.Contains(capabilities, "thinking") {
+		return capabilities
+	}
+
 	// Check for thinking capability
 	openingTag, closingTag := thinking.InferTags(m.Template.Template)
 	hasTags := openingTag != "" && closingTag != ""
-	if hasTags || slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily) {
+	isGptoss := slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily)
+	if hasTags || isGptoss || (builtinParser != nil && builtinParser.HasThinkingSupport()) {
 		capabilities = append(capabilities, model.CapabilityThinking)
 	}
 
@@ -198,6 +214,20 @@ func (m *Model) String() string {
 		})
 	}
 
+	if m.Config.Renderer != "" {
+		modelfile.Commands = append(modelfile.Commands, parser.Command{
+			Name: "renderer",
+			Args: m.Config.Renderer,
+		})
+	}
+
+	if m.Config.Parser != "" {
+		modelfile.Commands = append(modelfile.Commands, parser.Command{
+			Name: "parser",
+			Args: m.Config.Parser,
+		})
+	}
+
 	for k, v := range m.Options {
 		switch v := v.(type) {
 		case []any:
@@ -236,8 +266,19 @@ type ConfigV2 struct {
 	ModelFormat   string   `json:"model_format"`
 	ModelFamily   string   `json:"model_family"`
 	ModelFamilies []string `json:"model_families"`
-	ModelType     string   `json:"model_type"`
-	FileType      string   `json:"file_type"`
+	ModelType     string   `json:"model_type"` // shown as Parameter Size
+	FileType      string   `json:"file_type"`  // shown as Quantization Level
+	Renderer      string   `json:"renderer,omitempty"`
+	Parser        string   `json:"parser,omitempty"`
+
+	RemoteHost  string `json:"remote_host,omitempty"`
+	RemoteModel string `json:"remote_model,omitempty"`
+
+	// used for remotes
+	Capabilities []string `json:"capabilities,omitempty"`
+	ContextLen   int      `json:"context_length,omitempty"`
+	EmbedLen     int      `json:"embedding_length,omitempty"`
+	BaseName     string   `json:"base_name,omitempty"`
 
 	// required by spec
 	Architecture string `json:"architecture"`

server/internal/internal/backoff/backoff.go

@@ -25,10 +25,7 @@ func Loop(ctx context.Context, maxBackoff time.Duration) iter.Seq2[int, error] {
 
 			// n^2 backoff timer is a little smoother than the
 			// common choice of 2^n.
-			d := time.Duration(n*n) * 10 * time.Millisecond
-			if d > maxBackoff {
-				d = maxBackoff
-			}
+			d := min(time.Duration(n*n)*10*time.Millisecond, maxBackoff)
 			// Randomize the delay between 0.5-1.5 x msec, in order
 			// to prevent accidental "thundering herd" problems.
 			d = time.Duration(float64(d) * (rand.Float64() + 0.5))

server/prompt.go

@@ -11,6 +11,7 @@ import (
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/llm"
+	"github.com/ollama/ollama/model/renderers"
 	"github.com/ollama/ollama/template"
 )
 
@@ -41,18 +42,12 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 			}
 		}
 
-		thinkVal := false
-		thinkLevel := ""
-		if think != nil {
-			thinkVal = think.Bool()
-			thinkLevel = think.String()
-		}
-		var b bytes.Buffer
-		if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
+		p, err := renderPrompt(m, append(system, msgs[i:]...), tools, think)
+		if err != nil {
 			return "", nil, err
 		}
 
-		s, err := tokenize(ctx, b.String())
+		s, err := tokenize(ctx, p)
 		if err != nil {
 			return "", nil, err
 		}
@@ -101,6 +96,23 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	}
 
 	// truncate any messages that do not fit into the context window
+	p, err := renderPrompt(m, append(system, msgs[currMsgIdx:]...), tools, think)
+	if err != nil {
+		return "", nil, err
+	}
+
+	return p, images, nil
+}
+
+func renderPrompt(m *Model, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
+	if m.Config.Renderer != "" {
+		rendered, err := renderers.RenderWithRenderer(m.Config.Renderer, msgs, tools, think)
+		if err != nil {
+			return "", err
+		}
+		return rendered, nil
+	}
+
 	var b bytes.Buffer
 	thinkVal := false
 	thinkLevel := ""
@@ -108,9 +120,8 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 		thinkVal = think.Bool()
 		thinkLevel = think.String()
 	}
-	if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[currMsgIdx:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
-		return "", nil, err
+	if err := m.Template.Execute(&b, template.Values{Messages: msgs, Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
+		return "", err
 	}
-
-	return b.String(), images, nil
+	return b.String(), nil
 }

server/routes.go

@@ -15,6 +15,7 @@ import (
 	"net"
 	"net/http"
 	"net/netip"
+	"net/url"
 	"os"
 	"os/signal"
 	"slices"
@@ -35,6 +36,7 @@ import (
 	"github.com/ollama/ollama/harmony"
 	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/logutil"
+	"github.com/ollama/ollama/model/parsers"
 	"github.com/ollama/ollama/openai"
 	"github.com/ollama/ollama/server/internal/client/ollama"
 	"github.com/ollama/ollama/server/internal/registry"
@@ -188,6 +190,83 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
+	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
+		origModel := req.Model
+
+		remoteURL, err := url.Parse(m.Config.RemoteHost)
+		if err != nil {
+			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+			return
+		}
+
+		if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
+			slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
+			c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
+			return
+		}
+
+		req.Model = m.Config.RemoteModel
+
+		if req.Template == "" && m.Template.String() != "" {
+			req.Template = m.Template.String()
+		}
+
+		if req.Options == nil {
+			req.Options = map[string]any{}
+		}
+
+		for k, v := range m.Options {
+			if _, ok := req.Options[k]; !ok {
+				req.Options[k] = v
+			}
+		}
+
+		// update the system prompt from the model if one isn't already specified
+		if req.System == "" && m.System != "" {
+			req.System = m.System
+		}
+
+		if len(m.Messages) > 0 {
+			slog.Warn("embedded messages in the model not supported with '/api/generate'; try '/api/chat' instead")
+		}
+
+		fn := func(resp api.GenerateResponse) error {
+			resp.Model = origModel
+			resp.RemoteModel = m.Config.RemoteModel
+			resp.RemoteHost = m.Config.RemoteHost
+
+			data, err := json.Marshal(resp)
+			if err != nil {
+				return err
+			}
+
+			if _, err = c.Writer.Write(append(data, '\n')); err != nil {
+				return err
+			}
+			c.Writer.Flush()
+			return nil
+		}
+
+		client := api.NewClient(remoteURL, http.DefaultClient)
+		err = client.Generate(c, &req, fn)
+		if err != nil {
+			var authError api.AuthorizationError
+			if errors.As(err, &authError) {
+				c.JSON(authError.StatusCode, gin.H{"error": "unauthorized", "public_key": authError.PublicKey})
+				return
+			}
+			var apiError api.StatusError
+			if errors.As(err, &apiError) {
+				c.JSON(apiError.StatusCode, apiError)
+				return
+			}
+			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+			return
+		}
+
+		return
+	}
+
 	// expire the runner
 	if req.Prompt == "" && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
 		s.sched.expireRunner(m)
@@ -329,10 +408,10 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	// If debug mode is enabled, return the rendered template instead of calling the model
 	if req.DebugRenderOnly {
-		c.JSON(http.StatusOK, api.DebugTemplateResponse{
+		c.JSON(http.StatusOK, api.GenerateResponse{
 			Model:     req.Model,
 			CreatedAt: time.Now().UTC(),
-			DebugInfo: api.DebugInfo{
+			DebugInfo: &api.DebugInfo{
 				RenderedTemplate: prompt,
 				ImageCount:       len(images),
 			},
@@ -348,6 +427,9 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				OpeningTag: openingTag,
 				ClosingTag: closingTag,
 			}
+			if strings.HasSuffix(strings.TrimSpace(prompt), openingTag) {
+				thinkingState.AddContent(openingTag)
+			}
 		}
 	}
 
@@ -488,7 +570,6 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 	}
 
 	truncate := true
-
 	if req.Truncate != nil && !*req.Truncate {
 		truncate = false
 	}
@@ -551,11 +632,27 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 		ctxLen := min(opts.NumCtx, int(kvData.ContextLength()))
 		if len(tokens) > ctxLen {
 			if !truncate {
-				c.JSON(http.StatusBadRequest, gin.H{"error": "input length exceeds maximum context length"})
+				c.JSON(http.StatusBadRequest, gin.H{"error": "input exceeds maximum context length"})
+				return
+			}
+
+			if bos := kvData.Uint("tokenizer.ggml.bos_token_id"); tokens[0] != int(bos) && kvData.Bool("add_bos_token", true) {
+				ctxLen--
+			}
+
+			if eos := kvData.Uint("tokenizer.ggml.eos_token_id"); tokens[len(tokens)-1] != int(eos) && kvData.Bool("add_eos_token", true) {
+				ctxLen--
+			}
+
+			slog.Info("", "ctxLen", ctxLen, "tokenCount", len(tokens))
+			if ctxLen <= 0 {
+				// return error if the truncated input would be empty or just special tokens
+				c.JSON(http.StatusBadRequest, gin.H{"error": "input after truncation exceeds maximum context length"})
 				return
 			}
 
 			tokens = tokens[:ctxLen]
+
 			s, err = r.Detokenize(c.Request.Context(), tokens)
 			if err != nil {
 				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
@@ -576,7 +673,12 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 			if err != nil {
 				return err
 			}
-			embeddings[i] = normalize(embedding)
+			// TODO: this first normalization should be done by the model
+			embedding = normalize(embedding)
+			if req.Dimensions > 0 && req.Dimensions < len(embedding) {
+				embedding = normalize(embedding[:req.Dimensions])
+			}
+			embeddings[i] = embedding
 			return nil
 		})
 	}
@@ -602,11 +704,7 @@ func normalize(vec []float32) []float32 {
 		sum += v * v
 	}
 
-	norm := float32(0.0)
-	if sum > 0 {
-		norm = float32(1.0 / math.Sqrt(float64(sum)))
-	}
-
+	norm := float32(1.0 / max(math.Sqrt(float64(sum)), 1e-12))
 	for i := range vec {
 		vec[i] *= norm
 	}
@@ -921,6 +1019,28 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 		ModifiedAt:   manifest.fi.ModTime(),
 	}
 
+	if m.Config.RemoteHost != "" {
+		resp.RemoteHost = m.Config.RemoteHost
+		resp.RemoteModel = m.Config.RemoteModel
+
+		if m.Config.ModelFamily != "" {
+			resp.ModelInfo = make(map[string]any)
+			resp.ModelInfo["general.architecture"] = m.Config.ModelFamily
+
+			if m.Config.BaseName != "" {
+				resp.ModelInfo["general.basename"] = m.Config.BaseName
+			}
+
+			if m.Config.ContextLen > 0 {
+				resp.ModelInfo[fmt.Sprintf("%s.context_length", m.Config.ModelFamily)] = m.Config.ContextLen
+			}
+
+			if m.Config.EmbedLen > 0 {
+				resp.ModelInfo[fmt.Sprintf("%s.embedding_length", m.Config.ModelFamily)] = m.Config.EmbedLen
+			}
+		}
+	}
+
 	var params []string
 	cs := 30
 	for k, v := range m.Options {
@@ -951,6 +1071,11 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	fmt.Fprint(&sb, m.String())
 	resp.Modelfile = sb.String()
 
+	// skip loading tensor information if this is a remote model
+	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
+		return resp, nil
+	}
+
 	kvData, tensors, err := getModelData(m.ModelPath, req.Verbose)
 	if err != nil {
 		return nil, err
@@ -1027,11 +1152,13 @@ func (s *Server) ListHandler(c *gin.Context) {
 
 		// tag should never be masked
 		models = append(models, api.ListModelResponse{
-			Model:      n.DisplayShortest(),
-			Name:       n.DisplayShortest(),
-			Size:       m.Size(),
-			Digest:     m.digest,
-			ModifiedAt: m.fi.ModTime(),
+			Model:       n.DisplayShortest(),
+			Name:        n.DisplayShortest(),
+			RemoteModel: cf.RemoteModel,
+			RemoteHost:  cf.RemoteHost,
+			Size:        m.Size(),
+			Digest:      m.digest,
+			ModifiedAt:  m.fi.ModTime(),
 			Details: api.ModelDetails{
 				Format:            cf.ModelFormat,
 				Family:            cf.ModelFamily,
@@ -1291,6 +1418,9 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
 	r.POST("/api/show", s.ShowHandler)
 	r.DELETE("/api/delete", s.DeleteHandler)
 
+	r.DELETE("/api/user/keys/:encodedKey", s.SignoutHandler)
+	r.POST("/api/me", s.WhoamiHandler)
+
 	// Create
 	r.POST("/api/create", s.CreateHandler)
 	r.POST("/api/blobs/:digest", s.CreateBlobHandler)
@@ -1487,6 +1617,49 @@ func streamResponse(c *gin.Context, ch chan any) {
 	})
 }
 
+func (s *Server) WhoamiHandler(c *gin.Context) {
+	// todo allow other hosts
+	u, err := url.Parse("https://ollama.com")
+	if err != nil {
+		slog.Error(err.Error())
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
+		return
+	}
+
+	client := api.NewClient(u, http.DefaultClient)
+	user, err := client.Whoami(c)
+	if err != nil {
+		slog.Error(err.Error())
+	}
+	c.JSON(http.StatusOK, user)
+}
+
+func (s *Server) SignoutHandler(c *gin.Context) {
+	encodedKey := c.Param("encodedKey")
+
+	// todo allow other hosts
+	u, err := url.Parse("https://ollama.com")
+	if err != nil {
+		slog.Error(err.Error())
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
+		return
+	}
+
+	client := api.NewClient(u, http.DefaultClient)
+	err = client.Signout(c, encodedKey)
+	if err != nil {
+		slog.Error(err.Error())
+		if strings.Contains(err.Error(), "page not found") || strings.Contains(err.Error(), "invalid credentials") {
+			c.JSON(http.StatusNotFound, gin.H{"error": "you are not currently signed in"})
+			return
+		}
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "there was an error signing out"})
+		return
+	}
+
+	c.JSON(http.StatusOK, nil)
+}
+
 func (s *Server) PsHandler(c *gin.Context) {
 	models := []api.ProcessModelResponse{}
 
@@ -1543,21 +1716,34 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
-	// expire the runner
-	if len(req.Messages) == 0 && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
-		model, err := GetModel(req.Model)
-		if err != nil {
-			switch {
-			case os.IsNotExist(err):
-				c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Model)})
-			case err.Error() == errtypes.InvalidModelNameErrMsg:
-				c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
-			default:
-				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			}
-			return
+	name := model.ParseName(req.Model)
+	if !name.IsValid() {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
+		return
+	}
+
+	name, err := getExistingName(name)
+	if err != nil {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
+		return
+	}
+
+	m, err := GetModel(req.Model)
+	if err != nil {
+		switch {
+		case os.IsNotExist(err):
+			c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Model)})
+		case err.Error() == errtypes.InvalidModelNameErrMsg:
+			c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
+		default:
+			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
 		}
-		s.sched.expireRunner(model)
+		return
+	}
+
+	// expire the runner
+	if len(req.Messages) == 0 && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
+		s.sched.expireRunner(m)
 
 		c.JSON(http.StatusOK, api.ChatResponse{
 			Model:      req.Model,
@@ -1569,6 +1755,76 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
+	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
+		origModel := req.Model
+
+		remoteURL, err := url.Parse(m.Config.RemoteHost)
+		if err != nil {
+			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+			return
+		}
+
+		if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
+			slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
+			c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
+			return
+		}
+
+		req.Model = m.Config.RemoteModel
+		if req.Options == nil {
+			req.Options = map[string]any{}
+		}
+
+		msgs := append(m.Messages, req.Messages...)
+		if req.Messages[0].Role != "system" && m.System != "" {
+			msgs = append([]api.Message{{Role: "system", Content: m.System}}, msgs...)
+		}
+		msgs = filterThinkTags(msgs, m)
+		req.Messages = msgs
+
+		for k, v := range m.Options {
+			if _, ok := req.Options[k]; !ok {
+				req.Options[k] = v
+			}
+		}
+
+		fn := func(resp api.ChatResponse) error {
+			resp.Model = origModel
+			resp.RemoteModel = m.Config.RemoteModel
+			resp.RemoteHost = m.Config.RemoteHost
+
+			data, err := json.Marshal(resp)
+			if err != nil {
+				return err
+			}
+
+			if _, err = c.Writer.Write(append(data, '\n')); err != nil {
+				return err
+			}
+			c.Writer.Flush()
+			return nil
+		}
+
+		client := api.NewClient(remoteURL, http.DefaultClient)
+		err = client.Chat(c, &req, fn)
+		if err != nil {
+			var authError api.AuthorizationError
+			if errors.As(err, &authError) {
+				c.JSON(authError.StatusCode, gin.H{"error": "unauthorized", "public_key": authError.PublicKey})
+				return
+			}
+			var apiError api.StatusError
+			if errors.As(err, &apiError) {
+				c.JSON(apiError.StatusCode, apiError)
+				return
+			}
+			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+			return
+		}
+
+		return
+	}
+
 	caps := []model.Capability{model.CapabilityCompletion}
 	if len(req.Tools) > 0 {
 		caps = append(caps, model.CapabilityTools)
@@ -1577,17 +1833,6 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		caps = append(caps, model.CapabilityThinking)
 	}
 
-	name := model.ParseName(req.Model)
-	if !name.IsValid() {
-		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
-		return
-	}
-	name, err := getExistingName(name)
-	if err != nil {
-		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
-		return
-	}
-
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
 	if errors.Is(err, errCapabilityCompletion) {
 		c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support chat", req.Model)})
@@ -1616,10 +1861,15 @@ func (s *Server) ChatHandler(c *gin.Context) {
 	}
 	msgs = filterThinkTags(msgs, m)
 
+	var builtinParser parsers.Parser
+	if m.Config.Parser != "" {
+		builtinParser = parsers.ParserForName(m.Config.Parser)
+	}
+
 	var harmonyMessageHandler *harmony.HarmonyMessageHandler
 	var harmonyToolParser *harmony.HarmonyToolCallAccumulator
 
-	useHarmony := shouldUseHarmony(m)
+	useHarmony := shouldUseHarmony(m) || m.Config.Parser == "harmony"
 
 	processedTools := req.Tools
 	if useHarmony {
@@ -1649,10 +1899,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
 
 	// If debug mode is enabled, return the rendered template instead of calling the model
 	if req.DebugRenderOnly {
-		c.JSON(http.StatusOK, api.DebugTemplateResponse{
+		c.JSON(http.StatusOK, api.ChatResponse{
 			Model:     req.Model,
 			CreatedAt: time.Now().UTC(),
-			DebugInfo: api.DebugInfo{
+			DebugInfo: &api.DebugInfo{
 				RenderedTemplate: prompt,
 				ImageCount:       len(images),
 			},
@@ -1712,6 +1962,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
 				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 			}
 
+			// TODO(drifkin): fold this as much as possibleinto the generic m.Config.Parser logic
 			if useHarmony {
 				content, thinking, toolContent := harmonyMessageHandler.AddContent(r.Content, harmonyToolParser)
 				res.Message.Content = content
@@ -1738,6 +1989,27 @@ func (s *Server) ChatHandler(c *gin.Context) {
 					ch <- res
 				}
 
+				return
+			} else if builtinParser != nil {
+				slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser input", "parser", m.Config.Parser, "content", r.Content)
+
+				content, thinking, toolCalls, err := builtinParser.Add(r.Content, req.Tools)
+				if err != nil {
+					ch <- gin.H{"error": err.Error()}
+					return
+				}
+
+				res.Message.Content = content
+				res.Message.Thinking = thinking
+				res.Message.ToolCalls = toolCalls
+
+				if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || r.Done {
+					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser output", "parser", m.Config.Parser, "content", content, "thinking", thinking, "toolCalls", toolCalls, "done", r.Done)
+					ch <- res
+				} else {
+					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser empty output", "parser", m.Config.Parser)
+				}
+
 				return
 			}
 

server/routes_create_test.go

@@ -11,6 +11,7 @@ import (
 	"net/http/httptest"
 	"os"
 	"path/filepath"
+	"reflect"
 	"slices"
 	"strings"
 	"testing"
@@ -20,6 +21,7 @@ import (
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/types/model"
 )
 
 var stream bool = false
@@ -615,6 +617,78 @@ func TestCreateTemplateSystem(t *testing.T) {
 	})
 }
 
+func TestCreateAndShowRemoteModel(t *testing.T) {
+	gin.SetMode(gin.TestMode)
+
+	var s Server
+
+	w := createRequest(t, s.CreateHandler, api.CreateRequest{
+		Model:      "test",
+		From:       "bob",
+		RemoteHost: "https://ollama.com",
+		Info: map[string]any{
+			"capabilities":       []string{"completion", "tools", "thinking"},
+			"model_family":       "gptoss",
+			"context_length":     131072,
+			"embedding_length":   2880,
+			"quantization_level": "MXFP4",
+			"parameter_size":     "20.9B",
+		},
+		Stream: &stream,
+	})
+
+	if w.Code != http.StatusOK {
+		t.Fatalf("exected status code 200, actual %d", w.Code)
+	}
+
+	w = createRequest(t, s.ShowHandler, api.ShowRequest{Model: "test"})
+	if w.Code != http.StatusOK {
+		t.Fatalf("exected status code 200, actual %d", w.Code)
+	}
+
+	var resp api.ShowResponse
+	if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+		t.Fatal(err)
+	}
+
+	expectedDetails := api.ModelDetails{
+		ParentModel:       "",
+		Format:            "",
+		Family:            "gptoss",
+		Families:          []string{"gptoss"},
+		ParameterSize:     "20.9B",
+		QuantizationLevel: "MXFP4",
+	}
+
+	if !reflect.DeepEqual(resp.Details, expectedDetails) {
+		t.Errorf("model details: expected %#v, actual %#v", expectedDetails, resp.Details)
+	}
+
+	expectedCaps := []model.Capability{
+		model.Capability("completion"),
+		model.Capability("tools"),
+		model.Capability("thinking"),
+	}
+
+	if !slices.Equal(resp.Capabilities, expectedCaps) {
+		t.Errorf("capabilities: expected %#v, actual %#v", expectedCaps, resp.Capabilities)
+	}
+
+	v, ok := resp.ModelInfo["gptoss.context_length"]
+	ctxlen := v.(float64)
+	if !ok || int(ctxlen) != 131072 {
+		t.Errorf("context len: expected %d, actual %d", 131072, int(ctxlen))
+	}
+
+	v, ok = resp.ModelInfo["gptoss.embedding_length"]
+	embedlen := v.(float64)
+	if !ok || int(embedlen) != 2880 {
+		t.Errorf("embed len: expected %d, actual %d", 2880, int(embedlen))
+	}
+
+	fmt.Printf("resp = %#v\n", resp)
+}
+
 func TestCreateLicenses(t *testing.T) {
 	gin.SetMode(gin.TestMode)
 

server/routes_debug_test.go

@@ -180,7 +180,7 @@ func TestGenerateDebugRenderOnly(t *testing.T) {
 						t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
 					}
 
-					var response api.DebugTemplateResponse
+					var response api.GenerateResponse
 					if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
 						t.Fatalf("failed to unmarshal response: %v", err)
 					}
@@ -385,7 +385,7 @@ func TestChatDebugRenderOnly(t *testing.T) {
 						t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
 					}
 
-					var response api.DebugTemplateResponse
+					var response api.ChatResponse
 					if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
 						t.Fatalf("failed to unmarshal response: %v", err)
 					}

server/routes_test.go

@@ -126,7 +126,15 @@ func TestRoutes(t *testing.T) {
 			t.Fatalf("failed to create model: %v", err)
 		}
 
-		if err := createModel(r, modelName, baseLayers, fn); err != nil {
+		config := &ConfigV2{
+			OS:           "linux",
+			Architecture: "amd64",
+			RootFS: RootFS{
+				Type: "layers",
+			},
+		}
+
+		if err := createModel(r, modelName, baseLayers, config, fn); err != nil {
 			t.Fatal(err)
 		}
 	}

server/sched.go

@@ -382,10 +382,7 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
 // load creates a new model based on req and loads it. If requireFull is true then the model must be loaded fully onto GPUs
 // (if any). Returns whether the scheduler needs to evict a model to make this one fit.
 func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList, requireFull bool) bool {
-	numParallel := int(envconfig.NumParallel())
-	if numParallel < 1 {
-		numParallel = 1
-	}
+	numParallel := max(int(envconfig.NumParallel()), 1)
 
 	// Embedding models should always be loaded with parallel=1
 	if req.model.CheckCapabilities(model.CapabilityCompletion) != nil {