Model benchmarks
unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S local LLM performance
As of September 2026, unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S runs at up to 44.8 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
44.8 tok/s
Average speed
40.6 tok/s
Avg prefill
210.2 tok/s
Min memory
16.5 GB
Max context
65,536 tokens
Avg output / run
15,739 tokens
Avg runtime / run
6m 23s
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 | 80.5 | 81.4 | 82.3 |
| Agent Workflow | 80.1 | 80.6 | 81.1 |
| Code Generation | 79.4 | 79.7 | 80.0 |
| Role Play & Narrative | 78.7 | 82.2 | 85.7 |
| Research & Analysis | 82.1 | 83.1 | 84.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/Qwen3.8-27B-GGUF:UD-Q5_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 |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce GTX 1070 with Max-Q Design | llama.cpp | Q5_K_S | 44.8 tok/s | 40.6 tok/s | 16.5 GB | 65,536 tokens | 81.4 | 2 |
Frequently asked questions
- Is unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S good for coding?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S scores 79.7/100 for coding. It runs at about 40.6 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).
- Is unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S scores 80.6/100 for agentic workflows. It runs at about 40.6 tok/s, so if you want more speed, unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL is faster (~169.2 tok/s) and still scores well for agentic workflows (83.0/100).
- How fast is unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S for local inference?
- Across 2 community benchmark runs, unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S reaches up to 44.8 tok/s and averages 40.6 tok/s, with the fastest results on NVIDIA GeForce GTX 1070 with Max-Q Design.
- How much memory does unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S need?
- The leanest observed configuration used about 16.5 GB of memory (quantizations tested: Q5_K_S).
- Which tools have been used to run unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_S?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.