Сборка Ollama: зависимости, GPU-бэкенды, MLX

Title:

URL Source: https://raw.githubusercontent.com/ollama/ollama/main/docs/development.md

Markdown Content: # Development

Install prerequisites:

- [Go](https://go.dev/doc/install) - [CMake](https://cmake.org/download/) 3.24 or newer - C/C++ compiler: Clang on macOS, Visual Studio 2022 C++ tools on Windows, or GCC/Clang on Linux - [Ninja](https://github.com/ninja-build/ninja/releases) in `PATH` is recommended, especially on Windows

For pure Go iteration against an existing native payload, run Ollama from the repository root:

```shell 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.

## Native build model

For a fresh checkout, or after changing native code, build from the repository root. On macOS arm64, this builds Metal inference. On all other platforms this builds CPU-only inference. It builds the Go binary at the repository root and installs the native runtime payload under `build/lib/ollama`.

```shell cmake -B build . cmake --build build --parallel 8 ./ollama serve ```

To install into a standard prefix layout:

```shell cmake --install build --prefix /path/to/install ```

On all platforms except macOS arm64, to build GPU backends select the backends explicitly:

```shell cmake -B build . -DOLLAMA_LLAMA_BACKENDS="cuda_v13;vulkan" cmake --build build --parallel 8 ```

Supported backend values are `cuda_v12`, `cuda_v13`, `rocm_v7_1`, `rocm_v7_2`, `vulkan`, `cuda_jetpack5`, and `cuda_jetpack6`.

Use standard CMake architecture overrides to narrow GPU builds for local hardware:

```shell # CUDA cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v13 -DCMAKE_CUDA_ARCHITECTURES=native

# ROCm / HIP cmake -B build . -DOLLAMA_LLAMA_BACKENDS=rocm_v7_2 -DCMAKE_HIP_ARCHITECTURES=gfx1100 ```

You can tune GGML build options by setting `GGML_*` values during configure. For example, to disable CUDA flash attention kernels for local debugging:

```shell cmake -B build . -DOLLAMA_LLAMA_BACKENDS=cuda_v12 -DGGML_CUDA_FA=OFF ```

## macOS (Apple Silicon)

Additional prerequisites:

MLX Metal requires the Metal toolchain. Install [Xcode](https://developer.apple.com/xcode/) first, then:

```shell xcodebuild -downloadComponent MetalToolchain ```

## Windows

Additional prerequisites:

- [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) including the Native Desktop Workload - (Optional) AMD GPU support - [ROCm](https://rocm.docs.amd.com/en/latest/) - (Optional) NVIDIA GPU support - [CUDA SDK](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_type=exe_network) - (Optional) Vulkan GPU support - [Vulkan SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs - (Optional) MLX engine support - [CUDA 13+ SDK](https://developer.nvidia.com/cuda-downloads) - [cuDNN 9+](https://developer.nvidia.com/cudnn)

For Ninja builds, run CMake from a Developer PowerShell/Command Prompt or another shell where the Visual Studio compiler is available.

> Building for Vulkan requires VULKAN_SDK environment variable: > > PowerShell > ```powershell > $env:VULKAN_SDK="C:\VulkanSDK\<version>" > ``` > CMD > ```cmd > set VULKAN_SDK=C:\VulkanSDK\<version> > ```

## Windows (ARM)

Windows ARM does not support additional acceleration libraries at this time.

## Linux

Additional prerequisites:

- (Optional) AMD GPU support - [ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html) - (Optional) NVIDIA GPU support - [CUDA SDK](https://developer.nvidia.com/cuda-downloads) - (Optional) Vulkan GPU support - [Vulkan SDK](https://vulkan.lunarg.com/sdk/home) - useful for AMD/Intel GPUs - Or install via package manager: `sudo apt install vulkan-sdk` (Ubuntu/Debian) or `sudo dnf install vulkan-sdk` (Fedora/CentOS) - (Optional) MLX engine support - [CUDA 13+ SDK](https://developer.nvidia.com/cuda-downloads) - [cuDNN 9+](https://developer.nvidia.com/cudnn) - OpenBLAS/LAPACK: `sudo apt install libopenblas-dev liblapack-dev liblapacke-dev` (Ubuntu/Debian) > [!IMPORTANT] > Ensure prerequisites are in `PATH` before running CMake.

## MLX Engine (Optional)

The MLX engine enables running safetensor based models. On macOS arm64, MLX is enabled by default. On other platforms, MLX backends are selected with `OLLAMA_MLX_BACKENDS`.

### CUDA

Requires CUDA 13+ and [cuDNN](https://developer.nvidia.com/cudnn) 9+.

```shell cmake -B build . -DOLLAMA_MLX_BACKENDS=cuda_v13 cmake --build build --parallel 8 ```

### Local MLX source overrides

To build against a local checkout of MLX and/or MLX-C (useful for development), set environment variables before running CMake:

```shell export OLLAMA_MLX_SOURCE=/path/to/mlx export OLLAMA_MLX_C_SOURCE=/path/to/mlx-c ```

On macOS arm64:

```shell OLLAMA_MLX_SOURCE=../mlx OLLAMA_MLX_C_SOURCE=../mlx-c cmake -B build . cmake --build build --parallel 8 ```

For CUDA:

```powershell $env:OLLAMA_MLX_SOURCE="../mlx" $env:OLLAMA_MLX_C_SOURCE="../mlx-c" cmake -B build . -DOLLAMA_MLX_BACKENDS=cuda_v13 cmake --build build --parallel 8 ```

## Docker

```shell docker build . ```

### ROCm

```shell docker build --build-arg FLAVOR=rocm . ```

## Running tests

To run tests, use `go test`:

```shell go test ./... ```

## Library detection

Ollama looks for native helper binaries and acceleration libraries in installed and local development layouts:

* `../lib/ollama` for standard installs where `ollama` is under `bin/` * `./lib/ollama` for Windows release-style payloads and local dist output * `.` for macOS release artifacts that colocate helpers with `ollama` * `build/lib/ollama` and `dist/<platform>/lib/ollama` for local development builds

If the libraries are not found, Ollama will not run with any acceleration libraries.