Model benchmarks
Swift-1.5-Qwen3.8-27b-oQ8e-mtp local LLM performance
As of September 2026, Swift-1.5-Qwen3.8-27b-oQ8e-mtp runs at up to 34.8 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
34.8 tok/s
Average speed
29.1 tok/s
Avg PP
405.3 tok/s
Min memory
28.6 GB
Max context
262,144 tokens
Avg output / run
48,188 tokens
Avg runtime / run
29m 3s
Avg quality
84.6
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 | 83.1 | 84.6 | 86.4 |
| Agent Workflow | 78.5 | 84.9 | 90.4 |
| Code Generation | 77.2 | 81.6 | 85.4 |
| Role Play & Narrative | 81.8 | 86.7 | 89.9 |
| Research & Analysis | 82.8 | 85.3 | 88.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination Swift-1.5-Qwen3.8-27b-oQ8e-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 | oQ8e | 34.8 tok/s | 29.1 tok/s | 28.6 GB | 262,144 tokens | 84.6 | 3 |
Benchmark runs
All 3 Swift-1.5-Qwen3.8-27b-oQ8e-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Swift-1.5-Qwen3.8-27b-oQ8e-mtp good for coding?
- In our benchmarks, Swift-1.5-Qwen3.8-27b-oQ8e-mtp scores 81.6/100 for coding. It runs at about 29.1 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
- Is Swift-1.5-Qwen3.8-27b-oQ8e-mtp good for agentic (tool-using) tasks?
- In our benchmarks, Swift-1.5-Qwen3.8-27b-oQ8e-mtp scores 84.9/100 for agentic workflows. It runs at about 29.1 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-1.5-Qwen3.8-27b-oQ8e-mtp for local inference?
- Across 3 community benchmark runs, Swift-1.5-Qwen3.8-27b-oQ8e-mtp reaches up to 34.8 tok/s and averages 29.1 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Swift-1.5-Qwen3.8-27b-oQ8e-mtp need?
- The leanest observed configuration used about 28.6 GB of memory (quantizations tested: oQ8e).
- Which tools have been used to run Swift-1.5-Qwen3.8-27b-oQ8e-mtp?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.