Model benchmarks
unsloth/Qwen3.8-27B-GGUF local LLM performance
As of September 2026, unsloth/Qwen3.8-27B-GGUF runs at up to 42.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
42.1 tok/s
Average speed
41.2 tok/s
Avg PP
575.1 tok/s
Min memory
13.2 GB
Max context
16.384 tokens
Avg output / run
25.845 tokens
Avg runtime / run
10m 29s
Avg quality
53.3
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 | 32.8 | 53.3 | 73.7 |
| Agent Workflow | 16.0 | 41.7 | 67.4 |
| Code Generation | 7.6 | 28.3 | 49.1 |
| Role Play & Narrative | 91.3 | 91.3 | 91.4 |
| Research & Analysis | 16.5 | 51.7 | 86.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/Qwen3.8-27B-GGUF 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 RTX 4070 | llama.cpp | — | 42.1 tok/s | 41.2 tok/s | 13.2 GB | 16.384 tokens | 53.3 | 2 |
Benchmark runs
All 2 unsloth/Qwen3.8-27B-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is unsloth/Qwen3.8-27B-GGUF good for coding?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF scores 28.3/100 for coding. It runs at about 41.2 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 unsloth/Qwen3.8-27B-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/Qwen3.8-27B-GGUF scores 41.7/100 for agentic workflows. It runs at about 41.2 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 for local inference?
- Across 2 community benchmark runs, unsloth/Qwen3.8-27B-GGUF reaches up to 42.1 tok/s and averages 41.2 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does unsloth/Qwen3.8-27B-GGUF need?
- The leanest observed configuration used about 13.2 GB of memory.
- Which tools have been used to run unsloth/Qwen3.8-27B-GGUF?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.