Model benchmarks
qwen38-27b local LLM performance
As of September 2026, qwen38-27b runs at up to 78.6 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
78.6 tok/s
Average speed
72.1 tok/s
Avg prefill
531.0 tok/s
Min memory
13.2 GB
Max context
65,536 tokens
Avg output / run
42,509 tokens
Avg runtime / run
10m 12s
Avg quality
76.9
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 | 75.5 | 76.9 | 78.0 |
| Agent Workflow | 63.3 | 72.7 | 84.0 |
| Code Generation | 40.8 | 60.4 | 72.4 |
| Role Play & Narrative | 78.5 | 88.4 | 96.3 |
| Research & Analysis | 83.7 | 86.1 | 88.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination qwen38-27b 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900M | llama.cpp | — | 78.6 tok/s | 72.1 tok/s | 13.2 GB | 65,536 tokens | 76.9 | 3 |
Frequently asked questions
- Is qwen38-27b good for coding?
- In our benchmarks, qwen38-27b scores 60.4/100 for coding. It runs at about 72.1 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 qwen38-27b good for agentic (tool-using) tasks?
- In our benchmarks, qwen38-27b scores 72.7/100 for agentic workflows. It runs at about 72.1 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~165.0 tok/s) and still scores well for agentic workflows (89.3/100).
- How fast is qwen38-27b for local inference?
- Across 3 community benchmark runs, qwen38-27b reaches up to 78.6 tok/s and averages 72.1 tok/s, with the fastest results on AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900M.
- How much memory does qwen38-27b need?
- The leanest observed configuration used about 13.2 GB of memory.
- Which tools have been used to run qwen38-27b?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.