Model benchmarks
Qwen3.8-27B-4bit local LLM performance
As of August 2026, Qwen3.8-27B-4bit runs at up to 31.9 tok/s for local inference (best of 5 community benchmark runs across 1 GPU).
oMLX
Model size
27B
Peak speed
31.9 tok/s
Average speed
31.0 tok/s
Min memory
17.8 GB
Max context
15,137 tokens
Best quality
94.3
Benchmark runs
5
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-4bit 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 | — | 31.9 tok/s | 31.0 tok/s | 17.8 GB | 15,137 tokens | 77.7 | 5 |
Frequently asked questions
- How fast is Qwen3.8-27B-4bit for local inference?
- Across 5 community benchmark runs, Qwen3.8-27B-4bit reaches up to 31.9 tok/s and averages 31.0 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Qwen3.8-27B-4bit need?
- The leanest observed configuration used about 17.8 GB of memory.
- Which tools have been used to run Qwen3.8-27B-4bit?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.