Model benchmarks
unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL local LLM performance
As of August 2026, unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL runs at up to 47.1 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
27B
Peak speed
47.1 tok/s
Average speed
36.1 tok/s
Min memory
n/a
Max context
65,536 tokens
Avg runtime / run
24m 51s
Avg quality
88.3
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 | 87.1 | 88.3 | 89.5 |
| Agent Workflow | 78.5 | 84.9 | 91.3 |
| Code Generation | 81.2 | 83.2 | 85.2 |
| Role Play & Narrative | 95.4 | 96.1 | 96.7 |
| Research & Analysis | 88.1 | 89.0 | 89.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3080 Ti | llama.cpp | Q6_K | 47.1 tok/s | 47.1 tok/s | n/a | 65,536 tokens | 89.6 | 1 |
| Apple M5 Max | llama.cpp | Q6_K | 25.2 tok/s | 25.2 tok/s | n/a | 65,536 tokens | 87.0 | 1 |
Benchmark runs
All 2 unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL good for coding?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL scores 83.2/100 for coding. It runs at about 36.1 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
- Is unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL scores 84.9/100 for agentic workflows. It runs at about 36.1 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 unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL for local inference?
- Across 2 community benchmark runs, unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL reaches up to 47.1 tok/s and averages 36.1 tok/s, with the fastest results on NVIDIA GeForce RTX 3080 Ti.
- Which tools have been used to run unsloth/Qwen3.8-27B-GGUF:UD-Q6_K_XL?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.