From 7a312a177bcb736f201debc33271f8e2dabcd723 Mon Sep 17 00:00:00 2001
From: rltakashige <rl.takashige@gmail.com>
Date: Wed, 22 Apr 2026 16:43:27 +0100
Subject: [PATCH] Misc fixes: upstream JACCL all_sum, API, etc. + Add Kimi K2.6
 (#1952)

## Motivation

This fixes a bunch of observed model quality issues introduced upstream
in JACCL, as well as API issues and prefix cache calculation.


## Test Plan

### Manual Testing
Tested a bunch

### Automated Testing
Added a test, automated eval tool calls on Kimi K2.6, Minimax M2.7, GPT
OSS and Qwen3.6 models.

---------

Co-authored-by: Evan <evanev7@gmail.com>
---
 pyproject.toml                                |  18 +-
 python/parts.nix                              | 130 ++-
 .../moonshotai--Kimi-K2.6.toml                |  32 +
 src/exo/api/adapters/responses.py             | 132 ++-
 src/exo/download/coordinator.py               |  24 +-
 src/exo/download/download_utils.py            |  30 +-
 src/exo/download/impl_shard_downloader.py     | 144 +++-
 src/exo/worker/engines/mlx/cache.py           |   8 +-
 src/exo/worker/engines/mlx/utils_mlx.py       |  17 +-
 src/exo/worker/engines/mlx/vision.py          | 153 ++--
 src/exo/worker/main.py                        |   2 +-
 uv.lock                                       | 762 ++----------------
 12 files changed, 525 insertions(+), 927 deletions(-)
 create mode 100644 resources/inference_model_cards/moonshotai--Kimi-K2.6.toml

diff --git a/pyproject.toml b/pyproject.toml
index 7819a70d5..655410276 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,7 +3,7 @@ name = "exo"
 version = "0.3.70"
 description = "Exo"
 readme = "README.md"
-requires-python = ">=3.13"
+requires-python = "==3.13.*"
 dependencies = [
   "aiofiles>=24.1.0",
   "aiohttp>=3.12.14",
@@ -17,8 +17,8 @@ dependencies = [
   "loguru>=0.7.3",
   "exo-pyo3-bindings",                       # rust bindings
   "anyio==4.11.0",
-  "mlx==0.31.1; sys_platform == 'darwin'",
-  "mlx-lm",
+  "mlx==0.31.2; sys_platform == 'darwin'",
+  "mlx-lm; sys_platform=='darwin'",
   "tiktoken>=0.12.0",                        # required for kimi k2 tokenizer
   "hypercorn>=0.18.0",
   "openai-harmony>=0.0.8",
@@ -49,15 +49,21 @@ dev = [
 [project.optional-dependencies]
 build = ["nanobind"]
 cpu = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cpu==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 cuda12 = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cuda-12==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 cuda13 = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cuda-13==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 
@@ -75,7 +81,7 @@ mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-arra
 torch = [
   { index = "pytorch-cu130", marker = "sys_platform == 'linux' and extra == 'cuda13' and extra != 'cpu' and extra != 'cuda12'" },
   { index = "pytorch-cu120", marker = "sys_platform == 'linux' and extra == 'cuda12' and extra != 'cpu' and extra != 'cuda13'" },
-  { index = "pytorch-cpu", marker = "sys_platform == 'linux' and extra == 'cpu' and extra != 'cuda12' and extra != 'cuda13'" },
+  { index = "pytorch-cpu", marker = "(extra != 'cuda12' and extra != 'cuda13' and sys_platform == 'linux') or sys_platform == 'darwin'" },
 ]
 vllm = { git = "https://github.com/hmellor/vllm.git", branch = "transformers-v5" }
 
@@ -149,6 +155,10 @@ prerelease = "allow"
 environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
 conflicts = [[{ extra = "cuda12" }, { extra = "cuda13" }, { extra = "cpu" }]]
 constraint-dependencies = ["transformers>=5.0.0,<5.4.0"]
+override-dependencies = [
+  "mlx==0.31.1; sys_platform=='linux'",
+  "mlx; sys_platform=='darwin'",
+]
 
 [tool.uv.extra-build-dependencies]
 miniaudio = ["setuptools", "cffi", "pycparser"]
diff --git a/python/parts.nix b/python/parts.nix
index b5d6db622..ed5eb0b94 100644
--- a/python/parts.nix
+++ b/python/parts.nix
@@ -5,14 +5,13 @@ let
     workspaceRoot = ../.;
   };
 
-  mkPythonSet = { pkgs, lib, self' }:
+  mkPythonSet = { pkgs, lib, self', members }:
     let
       inherit (pkgs.stdenv.hostPlatform) isLinux isDarwin isx86_64;
       inherit (pkgs.config) cudaSupport;
       inherit (pkgs) cudaPackages;
       cuda13Support = cudaSupport && cudaPackages.cudaMajorVersion == "13";
       libmlx_source = if cuda13Support then "mlx-cuda-13" else if cudaSupport then "mlx-cuda-12" else "mlx-cpu";
-      uv_extra = if cuda13Support then "cuda13" else if cudaSupport then "cuda12" else "cpu";
       python = pkgs.python313;
       cudaLibs = with cudaPackages; [
         cuda_cudart
@@ -51,7 +50,7 @@ let
           '';
         };
       };
-      buildSystemsOverlay = final: prev: { } //
+      buildSystemsOverlay = final: prev:
         lib.optionalAttrs isDarwin
           {
             mlx = prev.mlx.overrideAttrs (old:
@@ -81,7 +80,7 @@ let
                 nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [ pkgs.cmake self'.packages.metal-toolchain ];
                 # TODO: non-sdk_26 support
                 buildInputs = (old.buildInputs or [ ])
-                  ++ [ gguf-tools pkgs.fmt pkgs.nlohmann_json pkgs.apple-sdk_26 ];
+                ++ [ gguf-tools pkgs.fmt pkgs.nlohmann_json pkgs.apple-sdk_26 ];
                 patches = [
                   (pkgs.replaceVars ../nix/darwin-build-fixes.patch {
                     sdkVersion = pkgs.apple-sdk_26.version;
@@ -113,42 +112,42 @@ let
                 MACOSX_DEPLOYMENT_TARGET = pkgs.apple-sdk_26.version;
               });
           } // lib.optionalAttrs isLinux {
-        mlx = prev.mlx.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ lib.optionals cudaSupport cudaLibs;
-          autoPatchelfIgnoreMissingDeps = lib.optionals cudaSupport [ "libcuda.so.1" ];
-          postInstall = (old.postInstall or "") + ''
-            cp -r "${final.${libmlx_source}}/${final.python.sitePackages}/mlx" "$out/${final.python.sitePackages}/mlx/"
-          '';
-        });
-      } // lib.optionalAttrs cudaSupport {
-        "${libmlx_source}" = prev."${libmlx_source}".overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cufile = prev.nvidia-cufile.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ pkgs.rdma-core ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cusolver = prev.nvidia-cusolver.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-nvshmem-cu13 = prev.nvidia-nvshmem-cu13.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ pkgs.rdma-core pkgs.pmix pkgs.libfabric pkgs.ucx pkgs.openmpi ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cusparse = prev.nvidia-cusparse.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ cudaLibs ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        torch = prev.torch.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-      };
+          mlx = prev.mlx.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ lib.optionals cudaSupport cudaLibs;
+            autoPatchelfIgnoreMissingDeps = lib.optionals cudaSupport [ "libcuda.so.1" ];
+            postInstall = ''
+              cp -r "${final.${libmlx_source}}/${final.python.sitePackages}/mlx" "$out/${final.python.sitePackages}/mlx/"
+            '';
+          });
+        } // lib.optionalAttrs cudaSupport {
+          "${libmlx_source}" = prev."${libmlx_source}".overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cufile = prev.nvidia-cufile.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ pkgs.rdma-core ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cusolver = prev.nvidia-cusolver.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-nvshmem-cu13 = prev.nvidia-nvshmem-cu13.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ pkgs.rdma-core pkgs.pmix pkgs.libfabric pkgs.ucx pkgs.openmpi ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cusparse = prev.nvidia-cusparse.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ cudaLibs ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          torch = prev.torch.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+        };
       pyprojectOverlay = workspace.mkPyprojectOverlay {
         sourcePreference = "wheel";
-        dependencies = { exo = [ uv_extra ]; exo-bench = [ ]; };
+        dependencies = members;
       };
       editableOverlay = workspace.mkEditablePyprojectOverlay {
         # Use environment variable pointing to editable root directory
@@ -165,8 +164,8 @@ let
           buildSystemsOverlay
         ]
       );
-
-      mkApp = cmd: name: members: pkgs.writeShellApplication {
+      venv = name: (pythonSet.mkVirtualEnv "${name}-env" members).overrideAttrs (_: { venvSkip = [ "lib/python${python.pythonVersion}/site-packages/mlx/share/cmake/*" ]; });
+      mkApp = cmd: name: pkgs.writeShellApplication {
         inherit name;
         runtimeEnv = {
           EXO_DASHBOARD_DIR = self'.packages.dashboard;
@@ -174,17 +173,17 @@ let
         };
         runtimeInputs = [
           # mlx and mlx-cuda ship clashing cmake files - we dont need them at runtime anyway
-          ((pythonSet.mkVirtualEnv "${name}-env" members).overrideAttrs (_: { venvSkip = [ "lib/python${python.pythonVersion}/site-packages/mlx/share/cmake/*" ]; }))
+          (venv name)
         ]
         ++ lib.optionals isDarwin [ pkgs.macmon ];
         text = "exec " + lib.optionalString cudaSupport "${lib.getExe pkgs.nix-gl-host} " + cmd;
       };
     in
     {
-      inherit pythonSet;
+      inherit venv;
       editablePythonSet = pythonSet.overrideScope editableOverlay;
-      mkPythonScript = members: name: path: mkApp ''python ${path} "$@"'' name members;
-      mkExo = name: members: mkApp ''exo "$@"'' name members;
+      mkPythonScript = path: mkApp ''python ${path} "$@"'';
+      mkExo = mkApp ''exo "$@"'';
     };
 in
 {
@@ -192,16 +191,21 @@ in
     { self', pkgs, unfreePkgs, lib, ... }:
     let
       inherit (pkgs.stdenv.hostPlatform) isLinux;
-      inherit (mkPythonSet { inherit self' pkgs lib; }) pythonSet editablePythonSet mkPythonScript mkExo;
-
-      exoVenv = pythonSet.mkVirtualEnv "exo-env" { exo = lib.optionals isLinux [ "cpu" ]; };
+      inherit (mkPythonSet { inherit self' pkgs lib; members = { exo = [ "cpu" ]; }; }) editablePythonSet mkExo;
 
       # Virtual environment with dev dependencies for testing
-      testVenv = pythonSet.mkVirtualEnv "exo-test-env" {
-        exo = [ "dev" ] ++ lib.optionals isLinux [ "cpu" ]; # Include pytest, pytest-asyncio, pytest-env
+      testVenv = (mkPythonSet {
+        inherit self' pkgs lib; members = {
+        exo = [ "dev" "cpu" ]; # Include pytest, pytest-asyncio, pytest-env
       };
+      }).venv "exo-test";
 
-      mkBenchScript = mkPythonScript { exo-bench = [ ]; };
+      mkBenchScript = (mkPythonSet {
+        inherit self' pkgs lib; members = {
+        exo = [ "cpu" ];
+        exo-bench = [ ]; # Include pytest, pytest-asyncio, pytest-env
+      };
+      }).mkPythonScript;
 
       mkSimplePythonScript = name: path: pkgs.writeShellApplication {
         inherit name;
@@ -212,9 +216,7 @@ in
     in
     {
       packages = {
-        exo = mkExo "exo" { exo = lib.optionals isLinux [ "cpu" ]; };
-        # for devShell
-        exo-venv = exoVenv;
+        exo = mkExo "exo";
         editableVenv = editablePythonSet.mkVirtualEnv "exo-dev-env" { exo = [ "dev" ]; };
         # for running tests in ci
         exo-test-env = testVenv;
@@ -224,8 +226,8 @@ in
         # used by ./tests/run_exo_on.sh
         exo-get-all-models-on-cluster = mkSimplePythonScript "exo-get-all-models-on-cluster" (inputs.self + /tests/get_all_models_on_cluster.py);
       } // lib.optionalAttrs isLinux {
-        exo-cuda-12 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_12) pkgs; }).mkExo "exo-cuda-12" { exo = [ "cuda12" ]; };
-        exo-cuda-13 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_13) pkgs; }).mkExo "exo-cuda-13" { exo = [ "cuda13" ]; };
+        exo-cuda-12 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_12) pkgs; members = { exo = [ "cuda12" ]; }; }).mkExo "exo-cuda-12";
+        exo-cuda-13 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_13) pkgs; members = { exo = [ "cuda13" ]; }; }).mkExo "exo-cuda-13";
       };
 
       checks = {
@@ -235,19 +237,11 @@ in
           touch $out
         '';
 
-        typecheck = pkgs.runCommand "typecheck"
-          {
-            nativeBuildInputs = [
-              testVenv
-              pkgs.basedpyright
-            ];
-          }
-          ''
-            cd ${inputs.self}
-            export HOME=$TMPDIR
-            basedpyright --pythonpath ${testVenv}/bin/python --project ${inputs.self}/pyproject.toml
-            touch $out
-          '';
+        typecheck = pkgs.runCommand "typecheck" { nativeBuildInputs = [ testVenv ]; } ''
+          cd ${inputs.self}
+          basedpyright
+          touch $out
+        '';
       };
     };
 }
diff --git a/resources/inference_model_cards/moonshotai--Kimi-K2.6.toml b/resources/inference_model_cards/moonshotai--Kimi-K2.6.toml
new file mode 100644
index 000000000..d18c73c11
--- /dev/null
+++ b/resources/inference_model_cards/moonshotai--Kimi-K2.6.toml
@@ -0,0 +1,32 @@
+model_id = "moonshotai/Kimi-K2.6"
+n_layers = 61
+hidden_size = 7168
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "kimi"
+quantization = ""
+base_model = "Kimi K2.6"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
+
+[storage_size]
+in_bytes = 595148192736
+
+[vision]
+image_token_id = 163605
+model_type = "kimi_vl"
+processor_repo = "moonshotai/Kimi-K2.6"
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+min_p = 0.01
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults.non_thinking]
+temperature = 0.6
+top_p = 0.95
+min_p = 0.01
diff --git a/src/exo/api/adapters/responses.py b/src/exo/api/adapters/responses.py
index ad11b0593..d65db32d5 100644
--- a/src/exo/api/adapters/responses.py
+++ b/src/exo/api/adapters/responses.py
@@ -113,6 +113,23 @@ def _extract_content(content: str | list[ResponseContentPart]) -> str:
     )
 
 
+def _append_tool_call(
+    chat_template_messages: list[dict[str, Any]], tool_call: dict[str, Any]
+) -> None:
+    if chat_template_messages:
+        prev = chat_template_messages[-1]
+        if prev.get("role") == "assistant" and isinstance(prev.get("content"), str):
+            existing: list[dict[str, Any]] | None = prev.get("tool_calls")
+            if existing is None:
+                prev["tool_calls"] = [tool_call]
+            else:
+                existing.append(tool_call)
+            return
+    chat_template_messages.append(
+        {"role": "assistant", "content": "", "tool_calls": [tool_call]}
+    )
+
+
 async def responses_request_to_text_generation(
     request: ResponsesRequest,
 ) -> TextGenerationTaskParams:
@@ -182,59 +199,44 @@ async def responses_request_to_text_generation(
                     | McpCallInputItem()
                     | CustomToolCallInputItem()
                 ):
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.name,
-                                        "arguments": item.arguments,
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.name,
+                                "arguments": item.arguments,
+                            },
+                        },
                     )
                 case (
                     LocalShellCallInputItem()
                     | ShellCallInputItem()
                     | ComputerCallInputItem()
                 ):
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.type,
-                                        "arguments": json.dumps(item.action),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.type,
+                                "arguments": json.dumps(item.action),
+                            },
+                        },
                     )
                 case ApplyPatchCallInputItem():
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": "apply_patch",
-                                        "arguments": json.dumps({"patch": item.patch}),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": "apply_patch",
+                                "arguments": json.dumps({"patch": item.patch}),
+                            },
+                        },
                     )
                 case (
                     WebSearchCallInputItem()
@@ -254,21 +256,16 @@ async def responses_request_to_text_generation(
                         args = {"prompt": item.prompt}
                     else:
                         args = {"query": item.query}
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.type,
-                                        "arguments": json.dumps(args),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.type,
+                                "arguments": json.dumps(args),
+                            },
+                        },
                     )
                 case (
                     FunctionCallOutputInputItem()
@@ -320,21 +317,16 @@ async def responses_request_to_text_generation(
                             }
                         )
                 case McpApprovalRequestInputItem():
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.name,
-                                        "arguments": item.arguments,
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.name,
+                                "arguments": item.arguments,
+                            },
+                        },
                     )
                 case McpApprovalResponseInputItem():
                     chat_template_messages.append(
diff --git a/src/exo/download/coordinator.py b/src/exo/download/coordinator.py
index df379b70c..2e9de3a8b 100644
--- a/src/exo/download/coordinator.py
+++ b/src/exo/download/coordinator.py
@@ -88,7 +88,9 @@ class DownloadCoordinator:
 
         try:
             if progress.status == "complete":
-                found = await to_thread.run_sync(resolve_existing_model, model_id)
+                found = await to_thread.run_sync(
+                    resolve_existing_model, model_id, callback_shard.model_card
+                )
                 if found is not None:
                     completed = self._completed_from_path(
                         callback_shard, found, progress.total
@@ -193,7 +195,9 @@ class DownloadCoordinator:
                 return
 
         # Check all model directories for pre-existing complete models
-        found_path = await to_thread.run_sync(resolve_existing_model, model_id)
+        found_path = await to_thread.run_sync(
+            resolve_existing_model, model_id, shard.model_card
+        )
         if found_path is not None:
             logger.info(f"DownloadCoordinator: Model {model_id} found at {found_path}")
             completed = self._completed_from_path(
@@ -220,7 +224,9 @@ class DownloadCoordinator:
         )
 
         if initial_progress.status == "complete":
-            found = await to_thread.run_sync(resolve_existing_model, model_id)
+            found = await to_thread.run_sync(
+                resolve_existing_model, model_id, shard.model_card
+            )
             if found is not None:
                 completed = self._completed_from_path(
                     shard, found, initial_progress.total
@@ -351,7 +357,9 @@ class DownloadCoordinator:
 
                     if progress.status == "complete":
                         found = await to_thread.run_sync(
-                            resolve_existing_model, model_id
+                            resolve_existing_model,
+                            model_id,
+                            progress.shard.model_card,
                         )
                         if found is not None:
                             status: DownloadProgress = self._completed_from_path(
@@ -380,7 +388,9 @@ class DownloadCoordinator:
                         # (is_model_directory_complete) which validates that all
                         # safetensors weight files are present.
                         found = await to_thread.run_sync(
-                            resolve_existing_model, model_id
+                            resolve_existing_model,
+                            model_id,
+                            progress.shard.model_card,
                         )
                         if found is not None:
                             status = self._completed_from_path(
@@ -421,7 +431,9 @@ class DownloadCoordinator:
                             (DownloadCompleted, DownloadOngoing, DownloadFailed),
                         ):
                             continue
-                        found = await to_thread.run_sync(resolve_existing_model, mid)
+                        found = await to_thread.run_sync(
+                            resolve_existing_model, mid, card
+                        )
                         if found is not None and is_read_only_model_dir(found):
                             path_shard = PipelineShardMetadata(
                                 model_card=card,
diff --git a/src/exo/download/download_utils.py b/src/exo/download/download_utils.py
index de4b92e0b..5aedfb20a 100644
--- a/src/exo/download/download_utils.py
+++ b/src/exo/download/download_utils.py
@@ -35,7 +35,7 @@ from exo.shared.constants import (
     EXO_MODELS_DIRS,
     EXO_MODELS_READ_ONLY_DIRS,
 )
-from exo.shared.models.model_cards import ModelTask
+from exo.shared.models.model_cards import ModelCard, ModelTask
 from exo.shared.types.common import ModelId
 from exo.shared.types.memory import Memory
 from exo.shared.types.worker.downloads import (
@@ -118,7 +118,9 @@ class InsufficientDiskSpaceError(Exception):
     """Raised when no writable model directory has enough free space."""
 
 
-def resolve_existing_model(model_id: ModelId) -> Path | None:
+def resolve_existing_model(
+    model_id: ModelId, card: ModelCard | None = None
+) -> Path | None:
     """Search all model directories for a complete, pre-existing model.
 
     Checks read-only directories first, then writable directories.
@@ -128,7 +130,7 @@ def resolve_existing_model(model_id: ModelId) -> Path | None:
     normalized = model_id.normalize()
     for search_dir in (*EXO_MODELS_READ_ONLY_DIRS, *EXO_MODELS_DIRS):
         candidate = search_dir / normalized
-        if candidate.is_dir() and is_model_directory_complete(candidate):
+        if candidate.is_dir() and is_model_directory_complete(candidate, card):
             return candidate
     return None
 
@@ -279,10 +281,26 @@ def _scan_model_directory(
     return list(entries_by_path.values())
 
 
-def is_model_directory_complete(model_dir: Path) -> bool:
-    """Check if a model directory contains all required weight files."""
+def is_model_directory_complete(model_dir: Path, card: ModelCard | None = None) -> bool:
+    """Check if a model directory contains all required weight files.
+    Also checks for sibling weights repo.
+    """
     file_list = _scan_model_directory(model_dir, recursive=True)
-    return file_list is not None and all(f.size is not None for f in file_list)
+    if file_list is None or not all(f.size is not None for f in file_list):
+        return False
+    if (
+        card is not None
+        and card.vision is not None
+        and card.vision.weights_repo != str(card.model_id)
+    ):
+        vision_id = ModelId(card.vision.weights_repo)
+        normalized = vision_id.normalize()
+        for search_dir in (*EXO_MODELS_READ_ONLY_DIRS, *EXO_MODELS_DIRS):
+            candidate = search_dir / normalized
+            if candidate.is_dir() and is_model_directory_complete(candidate):
+                return True
+        return False
+    return True
 
 
 async def _build_file_list_from_local_directory(
diff --git a/src/exo/download/impl_shard_downloader.py b/src/exo/download/impl_shard_downloader.py
index 0820380f1..14ec83b68 100644
--- a/src/exo/download/impl_shard_downloader.py
+++ b/src/exo/download/impl_shard_downloader.py
@@ -117,40 +117,39 @@ class ResumableShardDownloader(ShardDownloader):
     ) -> Path:
         allow_patterns = ["config.json"] if config_only else None
 
+        has_vision_sibling = (
+            not config_only
+            and not self.offline
+            and shard.model_card.vision is not None
+            and shard.model_card.vision.weights_repo != str(shard.model_card.model_id)
+        )
+
+        async def main_progress(
+            cb_shard: ShardMetadata, progress: RepoDownloadProgress
+        ) -> None:
+            if has_vision_sibling and progress.status == "complete":
+                return
+            await self.on_progress_wrapper(cb_shard, progress)
+
         target_dir, _ = await download_shard(
             shard,
-            self.on_progress_wrapper,
+            main_progress,
             max_parallel_downloads=self.max_parallel_downloads,
             allow_patterns=allow_patterns,
             skip_internet=self.offline,
         )
 
-        if (
-            not config_only
-            and not self.offline
-            and shard.model_card.vision
-            and shard.model_card.vision.weights_repo != str(shard.model_card.model_id)
-        ):
-            vision_repo = shard.model_card.vision.weights_repo
-            vision_card = ModelCard(
-                model_id=ModelId(vision_repo),
-                storage_size=Memory.from_bytes(0),
-                n_layers=1,
-                hidden_size=1,
-                supports_tensor=False,
-                tasks=[ModelTask.TextGeneration],
-            )
-            vision_shard = PipelineShardMetadata(
-                model_card=vision_card,
-                device_rank=0,
-                world_size=1,
-                start_layer=0,
-                end_layer=1,
-                n_layers=1,
-            )
+        if has_vision_sibling:
+            vision_shard = self._build_vision_shard(shard)
+
+            async def vision_progress(
+                _cb_shard: ShardMetadata, progress: RepoDownloadProgress
+            ) -> None:
+                await self.on_progress_wrapper(shard, progress)
+
             await download_shard(
                 vision_shard,
-                self.on_progress_wrapper,
+                vision_progress,
                 max_parallel_downloads=self.max_parallel_downloads,
                 allow_patterns=["*.safetensors", "config.json"],
                 skip_internet=self.offline,
@@ -158,6 +157,87 @@ class ResumableShardDownloader(ShardDownloader):
 
         return target_dir
 
+    async def _status_for_shard(
+        self, shard: ShardMetadata
+    ) -> tuple[Path, RepoDownloadProgress]:
+        async def _noop(
+            _cb_shard: ShardMetadata, _progress: RepoDownloadProgress
+        ) -> None:
+            return
+
+        path, main_progress = await download_shard(
+            shard,
+            _noop,
+            skip_download=True,
+            skip_internet=self.offline,
+        )
+
+        has_vision_sibling = (
+            shard.model_card.vision is not None
+            and shard.model_card.vision.weights_repo != str(shard.model_card.model_id)
+        )
+        if not has_vision_sibling:
+            return path, main_progress
+
+        vision_shard = self._build_vision_shard(shard)
+        _, vision_progress = await download_shard(
+            vision_shard,
+            _noop,
+            skip_download=True,
+            skip_internet=self.offline,
+        )
+        combined = self._combine_progress(shard, main_progress, vision_progress)
+        return path, combined
+
+    @staticmethod
+    def _build_vision_shard(shard: ShardMetadata) -> PipelineShardMetadata:
+        assert shard.model_card.vision is not None
+        vision_card = ModelCard(
+            model_id=ModelId(shard.model_card.vision.weights_repo),
+            storage_size=Memory.from_bytes(0),
+            n_layers=1,
+            hidden_size=1,
+            supports_tensor=False,
+            tasks=[ModelTask.TextGeneration],
+        )
+        return PipelineShardMetadata(
+            model_card=vision_card,
+            device_rank=0,
+            world_size=1,
+            start_layer=0,
+            end_layer=1,
+            n_layers=1,
+        )
+
+    @staticmethod
+    def _combine_progress(
+        shard: ShardMetadata,
+        main: RepoDownloadProgress,
+        vision: RepoDownloadProgress,
+    ) -> RepoDownloadProgress:
+        status_rank = {"not_started": 0, "in_progress": 1, "complete": 2}
+        combined_status = min(
+            (main.status, vision.status), key=lambda s: status_rank[s]
+        )
+        file_progress = dict(main.file_progress)
+        for file_path, fp in vision.file_progress.items():
+            file_progress[f"{vision.repo_id}/{file_path}"] = fp
+        return RepoDownloadProgress(
+            repo_id=main.repo_id,
+            repo_revision=main.repo_revision,
+            shard=shard,
+            completed_files=main.completed_files + vision.completed_files,
+            total_files=main.total_files + vision.total_files,
+            downloaded=main.downloaded + vision.downloaded,
+            downloaded_this_session=main.downloaded_this_session
+            + vision.downloaded_this_session,
+            total=main.total + vision.total,
+            overall_speed=main.overall_speed + vision.overall_speed,
+            overall_eta=max(main.overall_eta, vision.overall_eta),
+            status=combined_status,
+            file_progress=file_progress,
+        )
+
     async def get_shard_download_status(
         self,
     ) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
@@ -166,12 +246,7 @@ class ResumableShardDownloader(ShardDownloader):
         ) -> tuple[Path, RepoDownloadProgress]:
             """Helper coroutine that builds the shard for a model and gets its download status."""
             shard = await build_full_shard(model_id)
-            return await download_shard(
-                shard,
-                self.on_progress_wrapper,
-                skip_download=True,
-                skip_internet=self.offline,
-            )
+            return await self._status_for_shard(shard)
 
         semaphore = asyncio.Semaphore(self.max_parallel_downloads)
 
@@ -195,10 +270,5 @@ class ResumableShardDownloader(ShardDownloader):
     async def get_shard_download_status_for_shard(
         self, shard: ShardMetadata
     ) -> RepoDownloadProgress:
-        _, progress = await download_shard(
-            shard,
-            self.on_progress_wrapper,
-            skip_download=True,
-            skip_internet=self.offline,
-        )
+        _, progress = await self._status_for_shard(shard)
         return progress
diff --git a/src/exo/worker/engines/mlx/cache.py b/src/exo/worker/engines/mlx/cache.py
index f2f197cdc..c66693fc4 100644
--- a/src/exo/worker/engines/mlx/cache.py
+++ b/src/exo/worker/engines/mlx/cache.py
@@ -249,7 +249,12 @@ class KVPrefixCache:
         # For partial match: trim to best_length, remaining has suffix to prefill
         # This ensures stream_generate always has at least one token to start with
         has_ssm = has_non_kv_caches(self.caches[best_index])
-        target = (max_length - 1) if is_exact and not has_ssm else best_length
+        cached_length = cache_length(self.caches[best_index])
+        if has_ssm:
+            target = best_length
+        else:
+            desired = (max_length - 1) if is_exact else best_length
+            target = min(cached_length, desired)
         restore_pos, restore_snap = self._get_snapshot(best_index, target)
 
         # No usable snapshot — need fresh cache
@@ -257,7 +262,6 @@ class KVPrefixCache:
             return make_kv_cache(model), prompt_tokens, None, False
 
         prompt_cache = deepcopy(self.caches[best_index])
-        cached_length = cache_length(self.caches[best_index])
         tokens_to_trim = cached_length - restore_pos
         if tokens_to_trim > 0:
             trim_cache(prompt_cache, tokens_to_trim, restore_snap)
diff --git a/src/exo/worker/engines/mlx/utils_mlx.py b/src/exo/worker/engines/mlx/utils_mlx.py
index 2b28c7ff3..1a16e26d0 100644
--- a/src/exo/worker/engines/mlx/utils_mlx.py
+++ b/src/exo/worker/engines/mlx/utils_mlx.py
@@ -208,9 +208,20 @@ def load_mlx_items(
     if vision_config is not None:
         from exo.worker.engines.mlx.vision import VisionProcessor
 
-        vision_processor: VisionProcessor | None = VisionProcessor(
-            vision_config, bound_instance.bound_shard.model_card.model_id
-        )
+        vision_start_time = time.perf_counter()
+        try:
+            vision_processor: VisionProcessor | None = VisionProcessor(
+                vision_config, bound_instance.bound_shard.model_card.model_id
+            )
+            vision_processor.load()
+            logger.info(
+                f"Time taken to load vision weights: {(time.perf_counter() - vision_start_time):.2f}s"
+            )
+        except Exception as e:
+            logger.opt(exception=e).error(
+                "Failed to load vision weights — disabling vision for this runner"
+            )
+            vision_processor = None
     else:
         vision_processor = None
 
diff --git a/src/exo/worker/engines/mlx/vision.py b/src/exo/worker/engines/mlx/vision.py
index 10d5312f0..f8af3e97e 100644
--- a/src/exo/worker/engines/mlx/vision.py
+++ b/src/exo/worker/engines/mlx/vision.py
@@ -36,6 +36,19 @@ from exo.worker.runner.bootstrap import logger
 
 _video_processor_patched = False
 
+_MLX_VLM_MODEL_TYPE_ALIASES: dict[str, str] = {
+    "kimi_k25": "kimi_vl",
+    "kimi_k26": "kimi_vl",
+}
+
+
+def _torch_tensor_to_mx(
+    tensor: Any,  # pyright: ignore[reportAny]
+) -> mx.array:
+    if str(tensor.dtype) == "torch.bfloat16":  # type: ignore
+        return mx.array(tensor.float().numpy(), dtype=mx.bfloat16)  # type: ignore
+    return mx.array(tensor.numpy())  # type: ignore
+
 
 def _filter_config(cls: type, d: dict[str, Any]) -> dict[str, Any]:
     valid = set(inspect.signature(cls.__init__).parameters.keys()) - {"self"}
@@ -85,6 +98,8 @@ def _instantiate_projector(
     params = {n: p for n, p in init_sig.parameters.items() if n != "self"}
     kwargs: dict[str, Any] = {}
 
+    if "config" in params:
+        kwargs["config"] = model_config
     if "embedding_dim" in params:
         kwargs["embedding_dim"] = vision_config.hidden_size  # pyright: ignore[reportAny]
     if "text_hidden_size" in params:
@@ -205,7 +220,9 @@ class VisionEncoder:
         return {}
 
     def _import_mlx_vlm(self, *submodules: str) -> Any:  # type: ignore
-        mt = self._config.model_type
+        mt = _MLX_VLM_MODEL_TYPE_ALIASES.get(
+            self._config.model_type, self._config.model_type
+        )
         results: list[Any] = []
         for sub in submodules:
             name = f"mlx_vlm.models.{mt}.{sub}"
@@ -238,7 +255,7 @@ class VisionEncoder:
     def _load_image_processor_from_module(self, repo: str) -> "ImageProcessor | None":
         # mlx_vlm.utils.load_image_processor only works for models that set
         # `Model.ImageProcessor = <cls>`, but Gemma4 just uses
-        # `Gemma4ImageProcessor` from the package `__init__.py`
+        # `Gemma4ImageProcessor` from the package `__init__.py`.
         try:
             pkg: Any = importlib.import_module(
                 f"mlx_vlm.models.{self._config.model_type}"
@@ -319,10 +336,16 @@ class VisionEncoder:
         else:
             self._load_weights_from_model_repo()
 
-        repo = processor_repo or str(self._model_path)
-        image_proc = load_image_processor(
-            repo
-        ) or self._load_image_processor_from_module(repo)
+        if processor_repo:
+            repo = str(build_model_path(ModelId(processor_repo)))
+        else:
+            repo = str(self._model_path)
+        try:
+            image_proc = load_image_processor(repo)
+        except ValueError:
+            image_proc = None
+        if image_proc is None:
+            image_proc = self._load_image_processor_from_module(repo)
         if image_proc is not None:
             self._processor = image_proc
         else:
@@ -339,39 +362,42 @@ class VisionEncoder:
         if not safetensors_files:
             raise FileNotFoundError(f"No safetensors files found in {self._model_path}")
 
-        weights: dict[str, mx.array] = {}
-        for sf_path in safetensors_files:
-            with safe_open(str(sf_path), framework="pt") as f:
-                keys = f.keys()
-                for key in keys:
-                    tensor = f.get_tensor(key)  # type: ignore
-                    np_tensor = tensor.float().numpy()  # type: ignore
-                    weights[key] = mx.array(np_tensor, dtype=mx.bfloat16)  # type: ignore
-
         vision_weights: dict[str, mx.array] = {}
         projector_weights: dict[str, mx.array] = {}
-        for key, val in weights.items():
-            if key.startswith("vision_tower."):
-                short_key = key[len("vision_tower.") :]
-                if short_key.startswith("encoder."):
-                    short_key = short_key[len("encoder.") :]
-                m = re.match(r"^(blocks\.\d+)\.(wqkv|wo)\.(weight|bias)$", short_key)
-                if m:
-                    short_key = f"{m.group(1)}.attn.{m.group(2)}.{m.group(3)}"
-                if short_key == "patch_embed.proj.weight" and val.ndim == 4:
-                    val = val.transpose(0, 2, 3, 1)
-                vision_weights[short_key] = val
-            elif key.startswith(("mm_projector.", "multi_modal_projector.")):
-                if key.startswith("multi_modal_projector."):
-                    short_key = key[len("multi_modal_projector.") :]
-                    if short_key.startswith("mm_projector."):
-                        short_key = short_key[len("mm_projector.") :]
-                else:
-                    short_key = key[len("mm_projector.") :]
-                short_key = short_key.replace("proj.0.", "linear_1.").replace(
-                    "proj.2.", "linear_2."
-                )
-                projector_weights[short_key] = val
+
+        for sf_path in safetensors_files:
+            with safe_open(str(sf_path), framework="pt") as f:
+                keys = cast(list[str], list(f.keys()))  # type: ignore
+                for key in keys:
+                    if key.startswith("vision_tower."):
+                        short_key = key[len("vision_tower.") :]
+                        if short_key.startswith("encoder."):
+                            short_key = short_key[len("encoder.") :]
+                        m = re.match(
+                            r"^(blocks\.\d+)\.(wqkv|wo)\.(weight|bias)$", short_key
+                        )
+                        if m:
+                            short_key = f"{m.group(1)}.attn.{m.group(2)}.{m.group(3)}"
+                        tensor = f.get_tensor(key)  # type: ignore
+                        val = mx.array(tensor.float().numpy(), dtype=mx.bfloat16)  # type: ignore
+                        if short_key == "patch_embed.proj.weight" and val.ndim == 4:
+                            val = val.transpose(0, 2, 3, 1)
+                        vision_weights[short_key] = val
+                    elif key.startswith(("mm_projector.", "multi_modal_projector.")):
+                        if key.startswith("multi_modal_projector."):
+                            short_key = key[len("multi_modal_projector.") :]
+                            if short_key.startswith("mm_projector."):
+                                short_key = short_key[len("mm_projector.") :]
+                        else:
+                            short_key = key[len("mm_projector.") :]
+                        short_key = short_key.replace("proj.0.", "linear_1.").replace(
+                            "proj.2.", "linear_2."
+                        )
+                        tensor = f.get_tensor(key)  # type: ignore
+                        projector_weights[short_key] = mx.array(
+                            tensor.float().numpy(),  # type: ignore
+                            dtype=mx.bfloat16,
+                        )
 
         assert self._vision_tower is not None
         self._vision_tower.load_weights(list(vision_weights.items()))
@@ -407,18 +433,26 @@ class VisionEncoder:
         needs_sanitize = False
 
         for sf_path in safetensors_files:
-            file_weights: dict[str, mx.array] = mx.load(str(sf_path))  # type: ignore
-            for key, val in file_weights.items():
-                for prefix in vision_prefixes:
-                    if key.startswith(prefix):
-                        vision_weights[key[len(prefix) :]] = val
-                        if prefix == "model.visual.":
-                            needs_sanitize = True
-                        break
-                else:
+            with safe_open(str(sf_path), framework="pt") as f:
+                keys = cast(list[str], list(f.keys()))  # type: ignore
+                for key in keys:
+                    matched = False
+                    for prefix in vision_prefixes:
+                        if key.startswith(prefix):
+                            vision_weights[key[len(prefix) :]] = _torch_tensor_to_mx(
+                                f.get_tensor(key)
+                            )
+                            if prefix == "model.visual.":
+                                needs_sanitize = True
+                            matched = True
+                            break
+                    if matched:
+                        continue
                     for prefix in projector_prefixes:
                         if key.startswith(prefix):
-                            projector_weights[key[len(prefix) :]] = val
+                            projector_weights[key[len(prefix) :]] = _torch_tensor_to_mx(
+                                f.get_tensor(key)
+                            )
                             break
 
         if not vision_weights:
@@ -463,7 +497,12 @@ class VisionEncoder:
         grid_thw: mx.array | None
         n_tokens_per_image: list[int]
 
-        if self._config.processor_repo:
+        is_kimi_vl_processor = any(
+            "mlx_vlm.models.kimi_vl" in cls.__module__
+            for cls in type(self._processor).__mro__
+        )
+
+        if self._config.processor_repo and not is_kimi_vl_processor:
             processed = self._processor.preprocess(
                 [{"type": "image", "image": img} for img in pil_images],
                 return_tensors="np",
@@ -481,6 +520,24 @@ class VisionEncoder:
                 int(mx.prod(grid_thw[i]).item()) // merge_length
                 for i in range(grid_thw.shape[0])
             ]
+        elif is_kimi_vl_processor:
+            proc: Any = self._processor
+            raw_processed = proc.preprocess(pil_images, return_tensors="np")  # type: ignore
+            stacked_pixels = mx.array(raw_processed["pixel_values"])  # type: ignore
+            if stacked_pixels.ndim == 3:
+                stacked_pixels = stacked_pixels[None]
+            per_image_pixels = [
+                stacked_pixels[i : i + 1] for i in range(stacked_pixels.shape[0])
+            ]
+            grid_raw = raw_processed.get("image_grid_hws")  # type: ignore
+            if grid_raw is None:
+                grid_raw = raw_processed["grid_thws"]  # type: ignore
+            grid_thw = mx.array(grid_raw)  # type: ignore
+            merge_length = int(np.prod(self._merge_kernel_size or [2, 2]))
+            n_tokens_per_image = [
+                int(mx.prod(grid_thw[i]).item()) // merge_length
+                for i in range(grid_thw.shape[0])
+            ]
         else:
             batch, tokens_override = _run_processor(self._processor, pil_images)
             # `Gemma4ImageProcessor` returns pixel_values as a plain ndarray
diff --git a/src/exo/worker/main.py b/src/exo/worker/main.py
index 81c8c26c8..f983b9ca7 100644
--- a/src/exo/worker/main.py
+++ b/src/exo/worker/main.py
@@ -209,7 +209,7 @@ class Worker:
                     self._download_backoff.record_attempt(model_id)
 
                     found_path = await to_thread.run_sync(
-                        resolve_existing_model, model_id
+                        resolve_existing_model, model_id, shard.model_card
                     )
                     if found_path is not None:
                         logger.info(f"Model {model_id} found at {found_path}")
diff --git a/uv.lock b/uv.lock
index eac6dd112..ab9c65db0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,11 +1,9 @@
 version = 1
 revision = 3
-requires-python = ">=3.13"
+requires-python = "==3.13.*"
 resolution-markers = [
-    "python_full_version >= '3.14' and sys_platform == 'darwin'",
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@@ -485,8 +393,9 @@ dependencies = [
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     { name = "mflux", marker = "sys_platform == 'darwin' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
-    { name = "mlx", version = "0.31.2.dev20260420+553a7adb", source = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks#553a7adbb20ed1b71fe643f4075982a639aaef1b" }, marker = "sys_platform == 'darwin' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
-    { name = "mlx-lm", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
+    { name = "mlx", version = "0.31.1", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform == 'linux' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
+    { name = "mlx", version = "0.31.2.dev20260422+ec49d18e", source = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks#ec49d18ec4cfba0e0c7a37f20d1cf4d75fe56731" }, marker = "sys_platform == 'darwin' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
+    { name = "mlx-lm", version = "0.31.3", source = { git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak#62bbd5b2ef8d29d02dd08af303c22518341a46b0" }, marker = "sys_platform == 'darwin' or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
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@@ -506,13 +415,22 @@ build = [
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 ]
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+    { name = "mlx", version = "0.31.2.dev20260422+ec49d18e", source = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks#ec49d18ec4cfba0e0c7a37f20d1cf4d75fe56731" }, marker = "(sys_platform == 'darwin' and extra == 'extra-3-exo-cpu') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13')" },
     { name = "mlx-cpu", marker = "sys_platform == 'linux'" },
+    { name = "mlx-lm", version = "0.31.3", source = { git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak#62bbd5b2ef8d29d02dd08af303c22518341a46b0" }, marker = "sys_platform == 'linux'" },
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 cuda12 = [
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+    { name = "mlx", version = "0.31.2.dev20260422+ec49d18e", source = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks#ec49d18ec4cfba0e0c7a37f20d1cf4d75fe56731" }, marker = "(sys_platform == 'darwin' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13')" },
     { name = "mlx-cuda-12", marker = "sys_platform == 'linux'" },
+    { name = "mlx-lm", version = "0.31.3", source = { git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak#62bbd5b2ef8d29d02dd08af303c22518341a46b0" }, marker = "sys_platform == 'linux'" },
 ]
 cuda13 = [
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+    { name = "mlx", version = "0.31.2.dev20260422+ec49d18e", source = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks#ec49d18ec4cfba0e0c7a37f20d1cf4d75fe56731" }, marker = "(sys_platform == 'darwin' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cuda12' and extra == 'extra-3-exo-cuda13') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda12') or (extra == 'extra-3-exo-cpu' and extra == 'extra-3-exo-cuda13')" },
     { name = "mlx-cuda-13", marker = "sys_platform == 'linux'" },
+    { name = "mlx-lm", version = "0.31.3", source = { git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak#62bbd5b2ef8d29d02dd08af303c22518341a46b0" }, marker = "sys_platform == 'linux'" },
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     { name = "mlx", marker = "sys_platform == 'darwin'", git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git?branch=address-rdma-gpu-locks" },
+    { name = "mlx", marker = "sys_platform == 'linux' and extra == 'cpu'", specifier = "==0.31.1" },
+    { name = "mlx", marker = "sys_platform == 'linux' and extra == 'cuda12'", specifier = "==0.31.1" },
+    { name = "mlx", marker = "sys_platform == 'linux' and extra == 'cuda13'", specifier = "==0.31.1" },
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-    { name = "mlx-lm", git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak" },
+    { name = "mlx-lm", marker = "sys_platform == 'darwin'", git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak" },
+    { name = "mlx-lm", marker = "sys_platform == 'linux' and extra == 'cpu'", git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak" },
+    { name = "mlx-lm", marker = "sys_platform == 'linux' and extra == 'cuda12'", git = "https://github.com/rltakashige/mlx-lm?branch=leo%2Ffix-arrayscache-leak" },
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     { name = "msgspec", specifier = ">=0.19.0" },
     { name = "nanobind", marker = "extra == 'build'" },
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