Your GPU does not have native support for FP4 computation but FP4 quantization is being used

[christopher_owen]

I kind of did…. check the other thread.

vLLM on GB10: gpt-oss-120b MXFP4 slower than SGLang/llama.cpp... what’s missing?

I’m using MXFP4 model weights and I’m specifically looking to ensure vLLM uses GB10’s native FP4 tensor-core kernels rather than slower fallbacks. I would like to get vLLM to the same performance class as the SGLang feature branch or recent llama.cpp improvements. At the moment, vLLM runs, but it looks like we’re not hitting the native FP4 (NVFP4) / Blackwell-optimized MoE GEMM path. My working hypothesis is that vLLM is either: falling back to a slower Marlin/weight-only FP4 path, or no…