diff --git a/docs/source/installation.mdx b/docs/source/installation.mdx index 768a740be..ba1b5544b 100644 --- a/docs/source/installation.mdx +++ b/docs/source/installation.mdx @@ -10,6 +10,9 @@ We provide official support for NVIDIA GPUs, CPUs, Intel XPUs, and Intel Gaudi. - [NVIDIA CUDA](#cuda) - [Installation via PyPI](#cuda-pip) - [Compile from Source](#cuda-compile) +- [AMD ROCm](#rocm) + - [Installation via PyPI](#rocm-pip) + - [Compile from Source](#rocm-compile) - [Intel XPU](#xpu) - [Installation via PyPI](#xpu-pip) - [Intel Gaudi](#gaudi) @@ -17,9 +20,6 @@ We provide official support for NVIDIA GPUs, CPUs, Intel XPUs, and Intel Gaudi. - [CPU](#cpu) - [Installation via PyPI](#cpu-pip) - [Compile from Source](#cpu-compile) -- [AMD ROCm (Preview)](#rocm) - - [Installation via PyPI](#rocm-pip) - - [Compile from Source](#rocm-compile) - [Preview Wheels](#preview-wheels) ## System Requirements[[requirements]] @@ -126,107 +126,8 @@ Big thanks to [wkpark](https://github.com/wkpark), [Jamezo97](https://github.com -## Intel XPU[[xpu]] - -* A compatible PyTorch version with Intel XPU support is required. The current minimum is **PyTorch 2.6.0**. It is recommended to use the latest stable release. See [Getting Started on Intel GPU](https://docs.pytorch.org/docs/stable/notes/get_start_xpu.html) for guidance. - -### Installation via PyPI[[xpu-pip]] - -This is the most straightforward and recommended installation option. - -The currently distributed `bitsandbytes` packages are built with the following configurations: - -| **OS** | **oneAPI Toolkit** | **Kernel Implementation** | -|--------------------|------------------|----------------------| -| **Linux x86-64** | 2025.1.3 | SYCL + Triton | -| **Windows x86-64** | 2025.1.3 | SYCL + Triton | - -The Linux build has a minimum glibc version of 2.34. - -Use `pip` or `uv` to install the latest release: - -```bash -pip install bitsandbytes -``` - -## Intel Gaudi[[gaudi]] - -* A compatible PyTorch version with Intel Gaudi support is required. The current minimum is **Gaudi v1.21** with **PyTorch 2.6.0**. It is recommended to use the latest stable release. See the Gaudi software [installation guide](https://docs.habana.ai/en/latest/Installation_Guide/index.html) for guidance. - - -### Installation from PyPI[[gaudi-pip]] - -Use `pip` or `uv` to install the latest release: - -```bash -pip install bitsandbytes -``` - -## CPU[[cpu]] - -### Installation from PyPI[[cpu-pip]] - -This is the most straightforward and recommended installation option. - -The currently distributed `bitsandbytes` packages are built with the following configurations: - -| **OS** | **Host Compiler** | Hardware Minimum -|--------------------|----------------------|----------------------| -| **Linux x86-64** | GCC 11.4 | AVX2 | -| **Linux aarch64** | GCC 11.4 | | -| **Windows x86-64** | MSVC 19.51+ (VS2026) | AVX2 | -| **Windows arm64** | MSVC 19.43+ (VS2022) | ARM NEON | -| **macOS arm64** | Apple Clang 17 | | - -The Linux build has a minimum glibc version of 2.24. - -Use `pip` or `uv` to install the latest release: - -```bash -pip install bitsandbytes -``` - -### Compile from Source[[cpu-compile]] - -To compile from source, simply install the package from source using `pip`. The package will be built for CPU only at this time. - - - - -```bash -git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ -pip install -e . -``` - - - - -Requires Visual Studio 2022 or 2026. - -```bash -git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ -pip install -e . -``` - - - - -Requires Visual Studio 2022 or 2026 with the **ARM64 C++ build tools** component, Python >= **3.12**, and PyTorch >= **2.12**. - -```bash -git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ -pip install -e . -``` - -> [!NOTE] -> The build system will detect the ARM64 architecture automatically via CMake. Only the CPU backend is supported on Windows ARM64 at this time (no CUDA). - - - +## AMD ROCm [[rocm]] -## AMD ROCm (Preview)[[rocm]] - -* Support for AMD GPUs is currently in a preview state. * All features are supported for both consumer RDNA devices and Data Center CDNA products. * A compatible PyTorch version with AMD ROCm support is required. It is recommended to use the latest stable release. On Linux, see [PyTorch on ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html) for guidance. On Windows, ROCm-enabled PyTorch wheels are available from: - [repo.radeon.com/rocm/windows/](https://repo.radeon.com/rocm/windows/) — official AMD releases @@ -257,14 +158,14 @@ pip install bitsandbytes ### Compile from Source[[rocm-compile]] -bitsandbytes can be compiled from ROCm 6.4 - ROCm 7.14.0. See the `CMakeLists.txt` for additional options. +bitsandbytes can be compiled from ROCm 6.3 - ROCm 7.14.0. See the `CMakeLists.txt` for additional options. To compile from source, you need CMake >= **3.31.6** and Python >= **3.10** installed. Make sure you have a compiler installed to compile C++ (`gcc`, `make`, headers, etc.). -You should also have a ROCm installation (system-wide or via Docker). The current minimum supported version is **6.4**. +You should also have a ROCm installation (system-wide or via Docker). The current minimum supported version is **6.3**. ```bash # Install bitsandbytes from source @@ -332,6 +233,105 @@ pip install . + +## Intel XPU[[xpu]] + +* A compatible PyTorch version with Intel XPU support is required. The current minimum is **PyTorch 2.6.0**. It is recommended to use the latest stable release. See [Getting Started on Intel GPU](https://docs.pytorch.org/docs/stable/notes/get_start_xpu.html) for guidance. + +### Installation via PyPI[[xpu-pip]] + +This is the most straightforward and recommended installation option. + +The currently distributed `bitsandbytes` packages are built with the following configurations: + +| **OS** | **oneAPI Toolkit** | **Kernel Implementation** | +|--------------------|------------------|----------------------| +| **Linux x86-64** | 2025.1.3 | SYCL + Triton | +| **Windows x86-64** | 2025.1.3 | SYCL + Triton | + +The Linux build has a minimum glibc version of 2.34. + +Use `pip` or `uv` to install the latest release: + +```bash +pip install bitsandbytes +``` + +## Intel Gaudi[[gaudi]] + +* A compatible PyTorch version with Intel Gaudi support is required. The current minimum is **Gaudi v1.21** with **PyTorch 2.6.0**. It is recommended to use the latest stable release. See the Gaudi software [installation guide](https://docs.habana.ai/en/latest/Installation_Guide/index.html) for guidance. + + +### Installation from PyPI[[gaudi-pip]] + +Use `pip` or `uv` to install the latest release: + +```bash +pip install bitsandbytes +``` + +## CPU[[cpu]] + +### Installation from PyPI[[cpu-pip]] + +This is the most straightforward and recommended installation option. + +The currently distributed `bitsandbytes` packages are built with the following configurations: + +| **OS** | **Host Compiler** | Hardware Minimum +|--------------------|----------------------|----------------------| +| **Linux x86-64** | GCC 11.4 | AVX2 | +| **Linux aarch64** | GCC 11.4 | | +| **Windows x86-64** | MSVC 19.51+ (VS2026) | AVX2 | +| **Windows arm64** | MSVC 19.43+ (VS2022) | ARM NEON | +| **macOS arm64** | Apple Clang 17 | | + +The Linux build has a minimum glibc version of 2.24. + +Use `pip` or `uv` to install the latest release: + +```bash +pip install bitsandbytes +``` + +### Compile from Source[[cpu-compile]] + +To compile from source, simply install the package from source using `pip`. The package will be built for CPU only at this time. + + + + +```bash +git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ +pip install -e . +``` + + + + +Requires Visual Studio 2022 or 2026. + +```bash +git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ +pip install -e . +``` + + + + +Requires Visual Studio 2022 or 2026 with the **ARM64 C++ build tools** component, Python >= **3.12**, and PyTorch >= **2.12**. + +```bash +git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/ +pip install -e . +``` + +> [!NOTE] +> The build system will detect the ARM64 architecture automatically via CMake. Only the CPU backend is supported on Windows ARM64 at this time (no CUDA). + + + + ## Preview Wheels[[preview-wheels]] If you would like to use new features even before they are officially released and help us test them, feel free to install the wheel directly from our CI (*the wheel links will remain stable!*):