Model benchmarks
unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL local LLM performance
As of August 2026, unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL runs at up to 26.2 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
26.2 tok/s
Average speed
24.4 tok/s
Min memory
n/a
Max context
65,536 tokens
Avg runtime / run
16m 10s
Avg quality
80.9
Benchmark runs
3
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 3 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 | 77.2 | 80.9 | 85.4 |
| Agent Workflow | 71.9 | 80.7 | 88.4 |
| Code Generation | 43.9 | 68.1 | 83.7 |
| Role Play & Narrative | 87.8 | 89.3 | 90.6 |
| Research & Analysis | 80.7 | 85.4 | 88.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/Qwen3.8-27B-GGUF:UD-Q8_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 |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | llama.cpp | Q8_K | 26.2 tok/s | 24.4 tok/s | n/a | 65,536 tokens | 80.9 | 3 |
Benchmark runs
All 3 unsloth/Qwen3.8-27B-GGUF:UD-Q8_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-Q8_K_XL good for coding?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL scores 68.1/100 for coding. It runs at about 24.4 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-Q8_K_XL good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL scores 80.7/100 for agentic workflows. It runs at about 24.4 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-Q8_K_XL for local inference?
- Across 3 community benchmark runs, unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL reaches up to 26.2 tok/s and averages 24.4 tok/s, with the fastest results on Apple M5 Max.
- Which tools have been used to run unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.