Model benchmarks
gemma-4-31B-it-MLX-8bit local LLM performance
As of August 2026, gemma-4-31B-it-MLX-8bit runs at up to 14.9 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
oMLX
Model size
31B
Peak speed
14.9 tok/s
Average speed
14.9 tok/s
Min memory
35.7 GB
Max context
3,625 tokens
Best quality
81.3
Benchmark runs
2
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination gemma-4-31B-it-MLX-8bit has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | oMLX | — | 14.9 tok/s | 14.9 tok/s | 35.7 GB | 3,625 tokens | 68.2 | 2 |
Frequently asked questions
- How fast is gemma-4-31B-it-MLX-8bit for local inference?
- Across 2 community benchmark runs, gemma-4-31B-it-MLX-8bit reaches up to 14.9 tok/s and averages 14.9 tok/s, with the fastest results on Apple M5 Max.
- How much memory does gemma-4-31B-it-MLX-8bit need?
- The leanest observed configuration used about 35.7 GB of memory.
- Which tools have been used to run gemma-4-31B-it-MLX-8bit?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.