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docs: update AMD section #2015

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210 changes: 105 additions & 105 deletions docs/source/installation.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -10,16 +10,16 @@ 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)
- [Installation via PyPI](#gaudi-pip)
- [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]]
Expand Down Expand Up @@ -126,107 +126,8 @@ Big thanks to [wkpark](https://github.com/wkpark), [Jamezo97](https://github.com
</hfoption>
</hfoptions>

## 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.

<hfoptions id="cpu-source">
<hfoption id="Linux / macOS">

```bash
git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/
pip install -e .
```

</hfoption>
<hfoption id="Windows (x86-64)">

Requires Visual Studio 2022 or 2026.

```bash
git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/
pip install -e .
```

</hfoption>
<hfoption id="Windows (ARM64)">

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).

</hfoption>
</hfoptions>
## 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
Expand Down Expand Up @@ -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.

<hfoptions id="rocm-source">
<hfoption id="Linux">

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
Expand Down Expand Up @@ -332,6 +233,105 @@ pip install .
</hfoption>
</hfoptions>


## 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.

<hfoptions id="cpu-source">
<hfoption id="Linux / macOS">

```bash
git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/
pip install -e .
```

</hfoption>
<hfoption id="Windows (x86-64)">

Requires Visual Studio 2022 or 2026.

```bash
git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git && cd bitsandbytes/
pip install -e .
```

</hfoption>
<hfoption id="Windows (ARM64)">

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).

</hfoption>
</hfoptions>

## 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!*):
Expand Down
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