Model benchmarks
Qwen3.8-27B-Q4_K_S local LLM performance
As of September 2026, Qwen3.8-27B-Q4_K_S runs at up to 39.8 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
39.8 tok/s
Average speed
35.5 tok/s
Avg PP
327.3 tok/s
Min memory
13.2 GB
Max context
65.536 tokens
Avg output / run
12.431 tokens
Avg runtime / run
5m 51s
Avg quality
77.7
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 | 73.5 | 77.7 | 81.9 |
| Agent Workflow | 75.4 | 76.1 | 76.8 |
| Code Generation | 56.7 | 66.9 | 77.0 |
| Role Play & Narrative | 76.5 | 83.7 | 90.9 |
| Research & Analysis | 82.9 | 84.1 | 85.2 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-Q4_K_S 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 6700/6700 XT/6750 XT / 6800M/6850M XT | llama.cpp | Q4_K_S | 39.8 tok/s | 35.5 tok/s | 13.2 GB | 65.536 tokens | 77.7 | 2 |
Benchmark runs
All 2 Qwen3.8-27B-Q4_K_S runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-Q4_K_S good for coding?
- In our benchmarks, Qwen3.8-27B-Q4_K_S scores 66.9/100 for coding. It runs at about 35.5 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-Q4_K_S good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-Q4_K_S scores 76.1/100 for agentic workflows. It runs at about 35.5 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-Q4_K_S for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-Q4_K_S reaches up to 39.8 tok/s and averages 35.5 tok/s, with the fastest results on AMD Radeon RX 6700/6700 XT/6750 XT / 6800M/6850M XT.
- How much memory does Qwen3.8-27B-Q4_K_S need?
- The leanest observed configuration used about 13.2 GB of memory (quantizations tested: Q4_K_S).
- Which tools have been used to run Qwen3.8-27B-Q4_K_S?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.