Model benchmarks
Qwen3.8-27B-oQ8e-fp16-mtp local LLM performance
As of August 2026, Qwen3.8-27B-oQ8e-fp16-mtp runs at up to 35.4 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
oMLXFP16
Model size
27B
Peak speed
35.4 tok/s
Average speed
35.4 tok/s
Min memory
33.4 GB
Max context
13,158 tokens
Best quality
95.4
Benchmark runs
2
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-oQ8e-fp16-mtp 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 | FP16 | 35.4 tok/s | 35.4 tok/s | 33.4 GB | 13,158 tokens | 87.6 | 2 |
Frequently asked questions
- How fast is Qwen3.8-27B-oQ8e-fp16-mtp for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-oQ8e-fp16-mtp reaches up to 35.4 tok/s and averages 35.4 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Qwen3.8-27B-oQ8e-fp16-mtp need?
- The leanest observed configuration used about 33.4 GB of memory (quantizations tested: FP16).
- Which tools have been used to run Qwen3.8-27B-oQ8e-fp16-mtp?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.