Model benchmarks
qwen3.8-27b-gsq-rco local LLM performance
As of September 2026, qwen3.8-27b-gsq-rco runs at up to 49.5 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
27B
Peak speed
49.5 tok/s
Average speed
39.7 tok/s
Avg prefill
724.8 tok/s
Min memory
10.3 GB
Max context
8,192 tokens
Avg output / run
19,063 tokens
Avg runtime / run
9m 17s
Avg quality
71.5
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 | 62.3 | 71.5 | 80.6 |
| Agent Workflow | 79.9 | 82.4 | 84.9 |
| Code Generation | 3.2 | 32.3 | 61.4 |
| Role Play & Narrative | 88.4 | 88.9 | 89.3 |
| Research & Analysis | 76.9 | 82.3 | 87.8 |
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.8-27b-gsq-rco 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 9060 XT | LM Studio | — | 49.5 tok/s | 49.5 tok/s | 11.3 GB | 8,192 tokens | 81.6 | 1 |
| Apple M5 Max | LM Studio | — | 29.9 tok/s | 29.9 tok/s | 10.3 GB | 8,192 tokens | 61.3 | 1 |
Frequently asked questions
- Is qwen3.8-27b-gsq-rco good for coding?
- In our benchmarks, qwen3.8-27b-gsq-rco scores 32.3/100 for coding. It runs at about 39.7 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
- Is qwen3.8-27b-gsq-rco good for agentic (tool-using) tasks?
- In our benchmarks, qwen3.8-27b-gsq-rco scores 82.4/100 for agentic workflows. It runs at about 39.7 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 qwen3.8-27b-gsq-rco for local inference?
- Across 2 community benchmark runs, qwen3.8-27b-gsq-rco reaches up to 49.5 tok/s and averages 39.7 tok/s, with the fastest results on AMD Radeon RX 9060 XT.
- How much memory does qwen3.8-27b-gsq-rco need?
- The leanest observed configuration used about 10.3 GB of memory.
- Which tools have been used to run qwen3.8-27b-gsq-rco?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.