Model benchmarks
swift-qwen3.8-27b local LLM performance
As of September 2026, swift-qwen3.8-27b runs at up to 49.6 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
27B
Peak speed
49.6 tok/s
Average speed
29.3 tok/s
Avg PP
630.7 tok/s
Min memory
12.9 GB
Max context
8.192 tokens
Avg output / run
22.109 tokens
Avg runtime / run
25m 48s
Avg quality
61.5
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 | 54.9 | 61.5 | 68.1 |
| Agent Workflow | 70.2 | 80.9 | 91.5 |
| Code Generation | 0.0 | 0.0 | 0.0 |
| Role Play & Narrative | 91.8 | 92.4 | 93.0 |
| Research & Analysis | 56.3 | 72.7 | 89.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination swift-qwen3.8-27b 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 9050 / 9060 XT | LM Studio | — | 49.6 tok/s | 49.6 tok/s | 15.4 GB | 8.192 tokens | 54.1 | 1 |
| NVIDIA GeForce RTX 5060 Ti | LM Studio | — | 9.1 tok/s | 9.1 tok/s | 12.9 GB | 8.192 tokens | 68.8 | 1 |
Benchmark runs
All 2 swift-qwen3.8-27b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is swift-qwen3.8-27b good for coding?
- In our benchmarks, swift-qwen3.8-27b scores 0.0/100 for coding. It runs at about 29.3 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 swift-qwen3.8-27b good for agentic (tool-using) tasks?
- In our benchmarks, swift-qwen3.8-27b scores 80.9/100 for agentic workflows. It runs at about 29.3 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 for local inference?
- Across 2 community benchmark runs, swift-qwen3.8-27b reaches up to 49.6 tok/s and averages 29.3 tok/s, with the fastest results on AMD Radeon RX 9050 / 9060 XT.
- How much memory does swift-qwen3.8-27b need?
- The leanest observed configuration used about 12.9 GB of memory.
- Which tools have been used to run swift-qwen3.8-27b?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.