NVIDIA / NVIDIA/TensorRT-LLM

[Bug]: CuTe DSL NVFP4 SwiGLU / FP4Out dense GEMM has no SM107 kernel

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#19,362 0 comments 0 reactions 1 assignee View on GitHub

@peaceh-nv is already working on this.

Since Sep 17, 2026.

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Description

Summary

The CuTe DSL NVFP4 dense GEMM with fused SwiGLU (and the FP4-output variant) is Blackwell-only. On SM107 the ops raise at init:

CuteDSL NVFP4 SwiGLU backend requires SM 100 (B200) or SM 103 (B300), but got SM 107
CuteDSL NVFP4 SwiGLU FP4Out requires SM 100 or SM 103

Gates: tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py around L1716 and L2248.

Impact

TestDeepSeekV3Lite::test_cute_dsl_nvfp4[...] cannot run on SM107 (found while sweeping llm_function_core.txt on 4x SM107 against main). The dense BF16/FP8/MXFP8/NVFP4 SM107 GEMMs landed in #18761/#18765, but the SwiGLU act-fusion variants did not.

Ask

  • Port the NVFP4 SwiGLU / FP4Out act-fusion dense GEMM to SM107 (same family as #18765), or
  • keep the SM100/103 gate and make the skip reason in test_llm_api_pytorch.py (~L1116, currently "blockscaling mm supports SM 100 and 103 only") say that the SwiGLU fusion is the missing piece.

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