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Revise supported formats to reflect new quantization types #2678

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dsikka merged 2 commits into from
May 1, 2026
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Revise supported formats to reflect new quantization types #2678

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Revise supported formats to reflect new quantization types
dsikka Apr 30, 2026
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Update README.md
dsikka May 1, 2026
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8 changes: 5 additions & 3 deletions README.md
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Expand Up @@ -58,16 +58,18 @@ Some of the exciting new features include:
* **Extended KV Cache and Attention Quantization Support**: LLM Compressor now supports attention quantization, as well as fine-grained KV Cache quantization. Previously only per-tensor KV cache quantization was supported. Now, you can quantize KV cache with `per-head` scales and run with vLLM. Examples of more generalized attention and kv cache quantization can be found in the [experimental folder](experimental/attention).


### Supported Formats
* Activation Quantization: W8A8 (int8 and fp8), MXFP8 (experimental)
* Mixed Precision: W4A16, W8A16, MXFP8A16 (experimental), NVFP4 (W4A4 and W4A16 support)
### Supported Precisions and Types
* Activation Quantization: W8A8 (int8 and fp8), W4AFP8, Microscale (NVFP4, MXFP4, MXFP8)
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* Mixed Precision: W4A16, W8A16, MXFP8A16, MXFP4A16, NVFP4A16
* Attention and KV Cache Quantization: FP8, NVFP4

### Supported Algorithms
* Simple PTQ
* GPTQ
* AWQ
* SmoothQuant
* AutoRound
* Rotation-based (SpinQuant, QuIP)

### Quantizing your model, step-by-step

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