Recent upstream Pascal kernel fixes let us compile native SM60/SM61 kernels again instead of relying on PTX JIT, so allow Flash Attention auto at runtime for CC 6.x devices. Fixes #16591 Fixes #16754
5.7 KiB
Development
Install prerequisites:
- Go
- CMake 3.24 or newer
- C/C++ compiler: Clang on macOS, Visual Studio 2022 C++ tools on Windows, or GCC/Clang on Linux
- Ninja in
PATHis recommended, especially on Windows
For pure Go iteration against an existing native payload, run Ollama from the repository root:
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 -cachefirst.
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.
cmake -B build .
cmake --build build --parallel 8
./ollama serve
To install into a standard prefix layout:
cmake --install build --prefix /path/to/install
On all platforms except macOS arm64, to build GPU backends select the backends explicitly:
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:
# 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:
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 first, then:
xcodebuild -downloadComponent MetalToolchain
Windows
Additional prerequisites:
- Visual Studio 2022 including the Native Desktop Workload
- (Optional) AMD GPU support
- (Optional) NVIDIA GPU support
- (Optional) Vulkan GPU support
- Vulkan SDK - useful for AMD/Intel GPUs
- (Optional) MLX engine support
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
$env:VULKAN_SDK="C:\VulkanSDK\<version>"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
- (Optional) NVIDIA GPU support
- (Optional) Vulkan GPU support
- Vulkan SDK - useful for AMD/Intel GPUs
- Or install via package manager:
sudo apt install vulkan-sdk(Ubuntu/Debian) orsudo dnf install vulkan-sdk(Fedora/CentOS)
- (Optional) MLX engine support
- CUDA 13+ SDK
- cuDNN 9+
- OpenBLAS/LAPACK:
sudo apt install libopenblas-dev liblapack-dev liblapacke-dev(Ubuntu/Debian)
Important
Ensure prerequisites are in
PATHbefore 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 9+.
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:
export OLLAMA_MLX_SOURCE=/path/to/mlx
export OLLAMA_MLX_C_SOURCE=/path/to/mlx-c
On macOS arm64:
OLLAMA_MLX_SOURCE=../mlx OLLAMA_MLX_C_SOURCE=../mlx-c cmake -B build .
cmake --build build --parallel 8
For CUDA:
$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
docker build .
ROCm
docker build --build-arg FLAVOR=rocm .
Running tests
To run tests, use go test:
go test ./...
Library detection
Ollama looks for native helper binaries and acceleration libraries in installed and local development layouts:
../lib/ollamafor standard installs whereollamais underbin/./lib/ollamafor Windows release-style payloads and local dist output.for macOS release artifacts that colocate helpers withollamabuild/lib/ollamaanddist/<platform>/lib/ollamafor local development builds
If the libraries are not found, Ollama will not run with any acceleration libraries.