[AutoDeploy]: Support nvfp4 quantization fusion
Open
@tcherckez-nvidia is already working on this.
Since Mar 9, 2026.
feature request
Low Precision
- Dominant language
- Python
- Stars
- 14.7k
- Forks
- 2.8k
- Avg merge
- 2d 23h
- Merged PRs (30d)
- 489
Description
🚀 The feature, motivation and pitch
We currently invoke dynamic quantization in a separate quantize_with_block_size kernel before every nvfp4 gemm.
Add a transformation to fuse quantization with the following gemm (preferred) or with the previous kernel (as epilogue - if fusing with gemm is not feasible).
See also: https://github.com/NVIDIA/TensorRT-LLM/pull/11273
Alternatives
No response
Additional context
No response
Before submitting a new issue...
- Make sure you already searched for relevant issues, and checked the documentation and examples for answers to frequently asked questions.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.