Gemma 3 4B IT (QAT) › Apple M2 Ultra
Gemma 3 4B IT (QAT) on the Apple M2 Ultra
Best measured: 134 tokens/s generation and 2,924 tokens/s prompt processing (Q4_0, Metal, FA on).
For comparison, our size-scaling estimate for this combination is 255 tok/s.
Every run
| Quant | Backend | Generate tok/s | Prompt tok/s | Test | Build / by / notes | Source |
|---|---|---|---|---|---|---|
| Q4_0 | Metal FA on | 134 | 2,924 | tg32 | ggml-org maintainers Benchmarked repo: https://huggingface.co/ggml-org/gemma-3-4b-it-qat-GGUF; chip named only by the file's directory (M2 Ultra), GPU core count not stated | llama.cpp benches/ (maintainer runs) |
tg128 = generating 128 tokens; pp512 = reading a 512-token prompt (llama-bench). LocalScore averages several prompt and output lengths, so its numbers run lower than tg128.
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All results for the Apple M2 Ultra · Gemma 3 4B IT (QAT) on other hardware