Model benchmarks
Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered local LLM performance
As of October 2026, Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered runs at up to 40.7 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
40.7 tok/s
Average speed
37.4 tok/s
Avg PP
309.4 tok/s
Min memory
16.3 GB
Max context
65,536 tokens
Avg output / run
74,914 tokens
Avg runtime / run
33m 20s
Avg quality
86.4
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 | 86.2 | 86.4 | 86.7 |
| Agent Workflow | 82.4 | 83.3 | 84.1 |
| Code Generation | 81.1 | 81.6 | 82.1 |
| Role Play & Narrative | 90.4 | 91.8 | 93.1 |
| Research & Analysis | 88.5 | 89.2 | 89.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered 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 | — | 40.7 tok/s | 37.4 tok/s | 16.3 GB | 65,536 tokens | 86.4 | 2 |
Benchmark runs
All 2 Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered good for coding?
- In our benchmarks, Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered scores 81.6/100 for coding. It runs at about 37.4 tok/s, so if you want more speed, K2-Horizon-MoVA-36B-A4B-MLX-4bit is faster (~48.5 tok/s) and still scores well for coding (82.5/100).
- Is Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered scores 83.3/100 for agentic workflows. It runs at about 37.4 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 Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered reaches up to 40.7 tok/s and averages 37.4 tok/s, with the fastest results on AMD Radeon RX 7800 XT.
- How much memory does Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered need?
- The leanest observed configuration used about 16.3 GB of memory.
- Which tools have been used to run Qwen3.8-27B-GSQ-RCO-IQ3_S-recovered?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.