Model benchmarks
ukisai/Swift-Qwen3.8-27B-GGUF local LLM performance
As of September 2026, ukisai/Swift-Qwen3.8-27B-GGUF runs at up to 34.8 tok/s for local inference (best of 6 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
34.8 tok/s
Average speed
33.4 tok/s
Avg PP
379.5 tok/s
Min memory
24.6 GB
Max context
80.000 tokens
Avg output / run
43.194 tokens
Avg runtime / run
21m 56s
Avg quality
85.1
Benchmark runs
6
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 6 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 | 81.2 | 85.1 | 87.4 |
| Agent Workflow | 80.9 | 86.5 | 91.5 |
| Code Generation | 66.4 | 77.2 | 87.7 |
| Role Play & Narrative | 80.5 | 88.8 | 96.4 |
| Research & Analysis | 84.0 | 87.7 | 90.5 |
Performance by hardware and tool
Every hardware/tool/quantization combination ukisai/Swift-Qwen3.8-27B-GGUF 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 7900 XTX | Unsloth Studio | Q4_K_M | 34.8 tok/s | 33.4 tok/s | 24.6 GB | 80.000 tokens | 85.1 | 6 |
Benchmark runs
All 6 ukisai/Swift-Qwen3.8-27B-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is ukisai/Swift-Qwen3.8-27B-GGUF good for coding?
- In our benchmarks, ukisai/Swift-Qwen3.8-27B-GGUF scores 77.2/100 for coding. It runs at about 33.4 tok/s, so if you want more speed, ornith-ai/Ornith-1.5-35B-A3B-GGUF is faster (~96.3 tok/s) and still scores well for coding (83.4/100).
- Is ukisai/Swift-Qwen3.8-27B-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, ukisai/Swift-Qwen3.8-27B-GGUF scores 86.5/100 for agentic workflows. It runs at about 33.4 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 ukisai/Swift-Qwen3.8-27B-GGUF for local inference?
- Across 6 community benchmark runs, ukisai/Swift-Qwen3.8-27B-GGUF reaches up to 34.8 tok/s and averages 33.4 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does ukisai/Swift-Qwen3.8-27B-GGUF need?
- The leanest observed configuration used about 24.6 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run ukisai/Swift-Qwen3.8-27B-GGUF?
- Benchmarks were submitted using Unsloth Studio. Results are community-contributed and updated as new runs arrive.