Model benchmarks
qwen3.6:27b-mlx local LLM performance
As of July 2026, qwen3.6:27b-mlx runs at up to 24.1 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Ollamanvfp4
Model size
27.4B
Peak speed
24.1 tok/s
Average speed
15.9 tok/s
Min memory
19.9 GB
Max context
6,626 tokens
Best quality
94.3
Benchmark runs
2
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.6:27b-mlx has been benchmarked on, ranked by peak token generation speed. Last updated July 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M4 Max | Ollama | nvfp4 | 24.1 tok/s | 24.1 tok/s | 20.8 GB | 6,626 tokens | 78.8 | 1 |
| Apple M5 Max | Ollama | nvfp4 | 7.6 tok/s | 7.6 tok/s | 19.9 GB | 6,458 tokens | 83.9 | 1 |
Frequently asked questions
- How fast is qwen3.6:27b-mlx for local inference?
- Across 2 community benchmark runs, qwen3.6:27b-mlx reaches up to 24.1 tok/s and averages 15.9 tok/s, with the fastest results on Apple M4 Max.
- How much memory does qwen3.6:27b-mlx need?
- The leanest observed configuration used about 19.9 GB of memory (quantizations tested: nvfp4).
- Which tools have been used to run qwen3.6:27b-mlx?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.