Model benchmarks
qwen3.8:27b-mlx local LLM performance
As of August 2026, qwen3.8:27b-mlx runs at up to 36.7 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Ollamanvfp4
Model size
27.8B
Peak speed
36.7 tok/s
Average speed
33.3 tok/s
Min memory
21.3 GB
Max context
7,286 tokens
Best quality
93.9
Benchmark runs
2
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.8:27b-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 Pro | Ollama | nvfp4 | 36.7 tok/s | 36.7 tok/s | 21.3 GB | 7,286 tokens | 81.0 | 1 |
| Apple M5 Max | Ollama | nvfp4 | 29.9 tok/s | 29.9 tok/s | 21.5 GB | 6,397 tokens | 82.9 | 1 |
Frequently asked questions
- How fast is qwen3.8:27b-mlx for local inference?
- Across 2 community benchmark runs, qwen3.8:27b-mlx reaches up to 36.7 tok/s and averages 33.3 tok/s, with the fastest results on Apple M5 Pro.
- How much memory does qwen3.8:27b-mlx need?
- The leanest observed configuration used about 21.3 GB of memory (quantizations tested: nvfp4).
- Which tools have been used to run qwen3.8:27b-mlx?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.