 | CUDA prompt processing speedup on MoE check this https://github.com/ggml-org/llama.cpp/pull/22298#issuecomment-4307164207 [link] [comments] |
CUDA: reduce MMQ stream-k overhead by JohannesGaessler · Pull Request #22298 · ggml-org/llama.cpp
Reddit r/LocalLLaMA / 4/25/2026
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Key Points
- A pull request to the ggml-org/llama.cpp repository proposes CUDA changes to reduce MMQ (matrix-multiply/quantization) stream-k overhead during prompt processing.
- The update is aimed at improving prompt-processing speed specifically in Mixture-of-Experts (MoE) scenarios.
- The post points readers to an associated GitHub issue comment for additional details on the proposed performance improvement.
- The work is part of ongoing optimization efforts for running LLMs efficiently on NVIDIA GPUs using CUDA.
- Expected outcome is lower runtime overhead and faster prompt throughput for CUDA-based deployments of llama.cpp, particularly with MoE models.
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