A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 10, 21:30 UTC
Migrate doc to website: Hardware Plugins (1/N) (#31496)
Signed-off-by: esmeetu <jasonailu87@gmail.com>
Roy Wang committed
Dec 29, 2025 at 23:55 UTC
b5d2d71d26b28ad4f9cee8698fa20030835170ad
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docs/getting_started/installation/README.md
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@@ -14,18 +14,6 @@ vLLM supports the following hardware platforms:
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## Hardware Plugins
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-The backends below live **outside** the main `vllm` repository and follow the
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-[Hardware-Pluggable RFC](../../design/plugin_system.md).
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+vLLM supports third-party hardware plugins that live **outside** the main `vllm` repository. These follow the [Hardware-Pluggable RFC](../../design/plugin_system.md).
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-| Accelerator | PyPI / package | Repository |
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-|-------------|----------------|------------|
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-| Google TPU | `tpu-inference` | <https://github.com/vllm-project/tpu-inference> |
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-| Ascend NPU | `vllm-ascend` | <https://github.com/vllm-project/vllm-ascend> |
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-| Intel Gaudi (HPU) | N/A, install from source | <https://github.com/vllm-project/vllm-gaudi> |
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-| MetaX MACA GPU | N/A, install from source | <https://github.com/MetaX-MACA/vLLM-metax> |
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-| Rebellions ATOM / REBEL NPU | `vllm-rbln` | <https://github.com/rebellions-sw/vllm-rbln> |
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-| IBM Spyre AIU | `vllm-spyre` | <https://github.com/vllm-project/vllm-spyre> |
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-| Cambricon MLU | `vllm-mlu` | <https://github.com/Cambricon/vllm-mlu> |
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-| Baidu Kunlun XPU | N/A, install from source | <https://github.com/baidu/vLLM-Kunlun> |
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-| Sophgo TPU | N/A, install from source | <https://github.com/sophgo/vllm-tpu> |
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-| Apple Silicon (Metal) | N/A, install from source | <https://github.com/vllm-project/vllm-metal> |
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+A list of all supported hardware can be found on the [vllm.ai website](https://vllm.ai/#hardware). If you want to add new hardware, please contact us on [Slack](https://slack.vllm.ai/) or [Email](mailto:collaboration@vllm.ai).