supported_hardware.md 1.97 KB
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(quantization-supported-hardware)=
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# Supported Hardware
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The table below shows the compatibility of various quantization implementations with different hardware platforms in vLLM:

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:::{list-table}
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:header-rows: 1
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- * Implementation
  * Volta
  * Turing
  * Ampere
  * Ada
  * Hopper
  * AMD GPU
  * Intel GPU
  * x86 CPU
  * AWS Inferentia
  * Google TPU
- * AWQ
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  *
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  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
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  * ✅︎
  * ✅︎
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  *
  *
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- * GPTQ
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
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  * ✅︎
  * ✅︎
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  *
  *
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- * Marlin (GPTQ/AWQ/FP8)
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  *
  *
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  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
  *
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- * INT8 (W8A8)
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  *
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  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
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  * ✅︎
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  *
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  * ✅︎
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- * FP8 (W8A8)
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  *
  *
  *
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  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
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- * AQLM
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
  *
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- * bitsandbytes
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
  *
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- * DeepSpeedFP
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
  *
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- * GGUF
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
  * ✅︎
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  *
  *
  *
  *
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:::
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- Volta refers to SM 7.0, Turing to SM 7.5, Ampere to SM 8.0/8.6, Ada to SM 8.9, and Hopper to SM 9.0.
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- ✅︎ indicates that the quantization method is supported on the specified hardware.
- ❌ indicates that the quantization method is not supported on the specified hardware.
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:::{note}
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This compatibility chart is subject to change as vLLM continues to evolve and expand its support for different hardware platforms and quantization methods.
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For the most up-to-date information on hardware support and quantization methods, please refer to <gh-dir:vllm/model_executor/layers/quantization> or consult with the vLLM development team.
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:::