Domestic GPU Trains AI to Write Its Own Kernels—Moore Threads Tops KernelBench

MusaCoder‑27B‑RL, the first open‑source large model fully trained on a domestic GPU stack, achieved an 88.6% pass rate on the Stanford‑Princeton KernelBench benchmark and outperformed leading foreign models by delivering at least 1.1× speedup over baseline kernels.

AI code generationChinese GPUGPU kernel generation

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Domestic GPU Trains AI to Write Its Own Kernels—Moore Threads Tops KernelBench