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
65,536 tokens
Avg quality
83.3
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 | 82.0 | 83.3 | 84.5 |
| Agent Workflow | 77.5 | 83.2 | 88.9 |
| Code Generation | 73.0 | 74.5 | 76.0 |
| Role Play & Narrative | 94.8 | 95.1 | 95.4 |
| Research & Analysis | 79.8 | 80.3 | 80.7 |
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 | 8,192 tokens | 81.9 | 1 |
| Apple M5 Max | Ollama | nvfp4 | 7.6 tok/s | 7.6 tok/s | 19.9 GB | 65,536 tokens | 84.6 | 1 |
Frequently asked questions
- Is qwen3.6:27b-mlx good for coding?
- In our benchmarks, qwen3.6:27b-mlx scores 74.5/100 for coding. It runs at about 15.9 tok/s, so if you want more speed, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf is faster (~35.6 tok/s) and still scores well for coding (84.9/100).
- Is qwen3.6:27b-mlx good for agentic (tool-using) tasks?
- In our benchmarks, qwen3.6:27b-mlx scores 83.2/100 for agentic workflows. It runs at about 15.9 tok/s, so if you want more speed, muse-glimmer:latest is faster (~34.5 tok/s) and still scores well for agentic workflows (93.0/100).
- 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.