Model benchmarks
ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp local LLM performance
As of October 2026, ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp runs at up to 51.2 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
51.2 tok/s
Average speed
51.0 tok/s
Avg PP
329.2 tok/s
Min memory
16.1 GB
Max context
32,768 tokens
Avg output / run
29,377 tokens
Avg runtime / run
9m 29s
Avg quality
81.4
Benchmark runs
2
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 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 | 78.0 | 81.4 | 84.7 |
| Agent Workflow | 81.5 | 81.7 | 81.9 |
| Code Generation | 67.3 | 73.1 | 78.8 |
| Role Play & Narrative | 78.5 | 84.2 | 89.9 |
| Research & Analysis | 84.8 | 86.5 | 88.2 |
Performance by hardware and tool
Every hardware/tool/quantization combination ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 9070/9070 XT/9070 GRE | llama.cpp | — | 51.2 tok/s | 51.0 tok/s | 16.1 GB | 32,768 tokens | 81.4 | 2 |
Benchmark runs
All 2 ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp good for coding?
- In our benchmarks, ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp scores 73.1/100 for coding. It runs at about 51.0 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~91.2 tok/s) and still scores well for coding (81.9/100).
- Is ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp good for agentic (tool-using) tasks?
- In our benchmarks, ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp scores 81.7/100 for agentic workflows. It runs at about 51.0 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp for local inference?
- Across 2 community benchmark runs, ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp reaches up to 51.2 tok/s and averages 51.0 tok/s, with the fastest results on AMD Radeon RX 9070/9070 XT/9070 GRE.
- How much memory does ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp need?
- The leanest observed configuration used about 16.1 GB of memory.
- Which tools have been used to run ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S-mtp?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.