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 2 community benchmark runs across 1 GPU).
llama.cppQ8_K
Model size
27B
Peak speed
26.2 tok/s
Average speed
25.0 tok/s
Min memory
26.4 GB
Max context
13,809 tokens
Best quality
93.2
Benchmark runs
2
GPUs tested
1
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 | 25.0 tok/s | 26.4 GB | 13,809 tokens | 76.6 | 2 |
Frequently asked questions
- How fast is unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL for local inference?
- Across 2 community benchmark runs, unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL reaches up to 26.2 tok/s and averages 25.0 tok/s, with the fastest results on Apple M5 Max.
- How much memory does unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL need?
- The leanest observed configuration used about 26.4 GB of memory (quantizations tested: Q8_K).
- 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.