Model benchmarks
Swift-Qwen3.8-27b-oQ4e-fp16-mtp local LLM performance
As of September 2026, Swift-Qwen3.8-27b-oQ4e-fp16-mtp runs at up to 48.6 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
48.6 tok/s
Average speed
41.5 tok/s
Avg PP
517.5 tok/s
Min memory
19.6 GB
Max context
262.144 tokens
Avg output / run
31.281 tokens
Avg runtime / run
11m 59s
Avg quality
84.7
Benchmark runs
3
GPUs tested
1
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 3 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 | 82.1 | 84.7 | 86.6 |
| Agent Workflow | 82.4 | 85.9 | 91.4 |
| Code Generation | 72.1 | 77.0 | 83.1 |
| Role Play & Narrative | 85.4 | 90.4 | 94.5 |
| Research & Analysis | 83.1 | 85.4 | 87.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination Swift-Qwen3.8-27b-oQ4e-fp16-mtp has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | oMLX | FP16 | 48.6 tok/s | 41.5 tok/s | 19.6 GB | 262.144 tokens | 84.7 | 3 |
Benchmark runs
All 3 Swift-Qwen3.8-27b-oQ4e-fp16-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Swift-Qwen3.8-27b-oQ4e-fp16-mtp good for coding?
- In our benchmarks, Swift-Qwen3.8-27b-oQ4e-fp16-mtp scores 77.0/100 for coding. It runs at about 41.5 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
- Is Swift-Qwen3.8-27b-oQ4e-fp16-mtp good for agentic (tool-using) tasks?
- In our benchmarks, Swift-Qwen3.8-27b-oQ4e-fp16-mtp scores 85.9/100 for agentic workflows. It runs at about 41.5 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is Swift-Qwen3.8-27b-oQ4e-fp16-mtp for local inference?
- Across 3 community benchmark runs, Swift-Qwen3.8-27b-oQ4e-fp16-mtp reaches up to 48.6 tok/s and averages 41.5 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Swift-Qwen3.8-27b-oQ4e-fp16-mtp need?
- The leanest observed configuration used about 19.6 GB of memory (quantizations tested: FP16).
- Which tools have been used to run Swift-Qwen3.8-27b-oQ4e-fp16-mtp?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.