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Gemma 4 MTP speeds llama.cpp 40%

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Gemma 4 MTP speeds llama.cpp 40%
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// 23h agoBENCHMARK RESULT

Gemma 4 MTP speeds llama.cpp 40%

A community llama.cpp fork and GGUF drafter pack bring Gemma 4’s multi-token prediction into local inference. On a MacBook Pro M5 Max, the benchmark jumps from 97 tokens/s to 138 tokens/s on a Fibonacci prompt.

// ANALYSIS

This is a real local-inference win, not just a flashy benchmark. The important part is that Gemma 4’s MTP path is now being pushed through a runnable llama.cpp fork with quantized drafter weights.

  • The measured gain is substantial: about 40% faster token generation on the cited setup and prompt
  • The repo links suggest this is not stock llama.cpp; it depends on custom MTP support and a patched runtime
  • Quantized assistant GGUFs lower the barrier for local testing, which matters more than raw headline speed
  • The result is still narrow: one prompt, one machine, one model family, so broader gains will depend on workload and draft acceptance
  • If upstream support matures, this could become a practical default for local Gemma 4 serving rather than a niche optimization
// TAGS
llminferencequantizationbenchmarkopen-sourceatomic-llama-cpp-turboquantgemma-4

DISCOVERED

23h ago

2026-05-08

PUBLISHED

1d ago

2026-05-08

RELEVANCE

8/ 10

AUTHOR

gladkos