[Doc] Documentation on supported hardware for quantization methods (#5745)

docs/source/quantization/supported_hardware.rst

@@ -0,0 +1,30 @@
+.. _supported_hardware_for_quantization:
+
+Supported Hardware for Quantization Kernels
+===========================================
+
+The table below shows the compatibility of various quantization implementations with different hardware platforms in vLLM:
+
+==============  ======  =======  =======  =====  ======  =======  =========  =======  ==============  ==========
+Implementation  Volta   Turing   Ampere   Ada    Hopper  AMD GPU  Intel GPU  x86 CPU  AWS Inferentia  Google TPU
+==============  ======  =======  =======  =====  ======  =======  =========  =======  ==============  ==========
+AQLM            ✅      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+AWQ             ❌      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+DeepSpeedFP     ✅      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+FP8             ❌      ❌       ❌       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+Marlin          ❌      ❌       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+GPTQ            ✅      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+SqueezeLLM      ✅      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+bitsandbytes    ✅      ✅       ✅       ✅     ✅      ❌        ❌         ❌       ❌              ❌
+==============  ======  =======  =======  =====  ======  =======  =========  =======  ==============  ==========
+
+Notes:
+^^^^^^
+
+- 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.
+- "✅" indicates that the quantization method is supported on the specified hardware.
+- "❌" indicates that the quantization method is not supported on the specified hardware.
+
+Please note that this compatibility chart may be subject to change as vLLM continues to evolve and expand its support for different hardware platforms and quantization methods.
+
+For the most up-to-date information on hardware support and quantization methods, please check the `quantization directory <https://github.com/vllm-project/vllm/tree/main/vllm/model_executor/layers/quantization>`_ or consult with the vLLM development team.