Model benchmarks
Qwen3.8-27B-Opus-Distill-IQ3_XXS local LLM performance
As of October 2026, Qwen3.8-27B-Opus-Distill-IQ3_XXS runs at up to 37.4 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
37.4 tok/s
Average speed
28.9 tok/s
Avg PP
337.6 tok/s
Min memory
14.8 GB
Max context
65,536 tokens
Avg output / run
9,898 tokens
Avg runtime / run
6m 24s
Avg quality
76.3
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 | 75.8 | 76.3 | 76.7 |
| Agent Workflow | 66.6 | 72.5 | 78.4 |
| Code Generation | 64.4 | 65.7 | 66.9 |
| Role Play & Narrative | 84.8 | 86.2 | 87.6 |
| Research & Analysis | 79.3 | 80.8 | 82.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-Opus-Distill-IQ3_XXS 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 7800 XT | llama.cpp | — | 37.4 tok/s | 28.9 tok/s | 14.8 GB | 65,536 tokens | 76.3 | 2 |
Benchmark runs
All 2 Qwen3.8-27B-Opus-Distill-IQ3_XXS runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-Opus-Distill-IQ3_XXS good for coding?
- In our benchmarks, Qwen3.8-27B-Opus-Distill-IQ3_XXS scores 65.7/100 for coding. It runs at about 28.9 tok/s, so if you want more speed, Qwen3.8-27B-oQ4e-fp16-mtp is faster (~38.6 tok/s) and still scores well for coding (82.6/100).
- Is Qwen3.8-27B-Opus-Distill-IQ3_XXS good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-Opus-Distill-IQ3_XXS scores 72.5/100 for agentic workflows. It runs at about 28.9 tok/s, so if you want more speed, muse-glimmer:latest is faster (~33.3 tok/s) and still scores well for agentic workflows (91.6/100).
- How fast is Qwen3.8-27B-Opus-Distill-IQ3_XXS for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-Opus-Distill-IQ3_XXS reaches up to 37.4 tok/s and averages 28.9 tok/s, with the fastest results on AMD Radeon RX 7800 XT.
- How much memory does Qwen3.8-27B-Opus-Distill-IQ3_XXS need?
- The leanest observed configuration used about 14.8 GB of memory.
- Which tools have been used to run Qwen3.8-27B-Opus-Distill-IQ3_XXS?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.