Model benchmarks
gemma4:12b-mlx local LLM performance
As of August 2026, gemma4:12b-mlx runs at up to 68.5 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
12.4B
Peak speed
68.5 tok/s
Average speed
57.8 tok/s
Min memory
9.3 GB
Max context
131,072 tokens
Avg runtime / run
3m 24s
Avg quality
65.8
Benchmark runs
2
GPUs tested
2
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 2 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 59.3 | 65.8 | 72.3 |
| Agent Workflow | 68.7 | 74.4 | 80.0 |
| Code Generation | 42.1 | 52.0 | 61.9 |
| Role Play & Narrative | 65.9 | 70.6 | 75.4 |
| Research & Analysis | 60.4 | 66.1 | 71.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination gemma4:12b-mlx 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 | Ollama | nvfp4 | 68.5 tok/s | 68.5 tok/s | 9.3 GB | 131,072 tokens | 58.6 | 1 |
| Apple M4 Pro | Ollama | nvfp4 | 47.1 tok/s | 47.1 tok/s | 9.3 GB | 131,072 tokens | 73.0 | 1 |
Benchmark runs
All 2 gemma4:12b-mlx runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is gemma4:12b-mlx good for coding?
- In our benchmarks, gemma4:12b-mlx scores 52.0/100 for coding. It runs at about 57.8 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~91.4 tok/s) and still scores well for coding (81.6/100).
- Is gemma4:12b-mlx good for agentic (tool-using) tasks?
- In our benchmarks, gemma4:12b-mlx scores 74.4/100 for agentic workflows. It runs at about 57.8 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is gemma4:12b-mlx for local inference?
- Across 2 community benchmark runs, gemma4:12b-mlx reaches up to 68.5 tok/s and averages 57.8 tok/s, with the fastest results on Apple M5 Max.
- How much memory does gemma4:12b-mlx need?
- The leanest observed configuration used about 9.3 GB of memory (quantizations tested: nvfp4).
- Which tools have been used to run gemma4:12b-mlx?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.