Model benchmarks
Qwen3.8-27B-Ridge-3.7bpw local LLM performance
As of October 2026, Qwen3.8-27B-Ridge-3.7bpw runs at up to 42.6 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
42.6 tok/s
Average speed
38.6 tok/s
Avg PP
513.6 tok/s
Min memory
23.2 GB
Max context
98,304 tokens
Avg output / run
22,521 tokens
Avg runtime / run
9m 36s
Avg quality
77.0
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 | 73.2 | 77.0 | 80.8 |
| Agent Workflow | 90.4 | 90.8 | 91.2 |
| Code Generation | 44.5 | 54.6 | 64.7 |
| Role Play & Narrative | 77.2 | 80.6 | 84.0 |
| Research & Analysis | 80.0 | 82.0 | 83.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-Ridge-3.7bpw has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5060 | llama.cpp | — | 42.6 tok/s | 38.6 tok/s | 23.2 GB | 98,304 tokens | 77.0 | 2 |
Benchmark runs
All 2 Qwen3.8-27B-Ridge-3.7bpw runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-Ridge-3.7bpw good for coding?
- In our benchmarks, Qwen3.8-27B-Ridge-3.7bpw scores 54.6/100 for coding. It runs at about 38.6 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~80.3 tok/s) and still scores well for coding (84.5/100).
- Is Qwen3.8-27B-Ridge-3.7bpw good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-Ridge-3.7bpw scores 90.8/100 for agentic workflows. It runs at about 38.6 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is Qwen3.8-27B-Ridge-3.7bpw for local inference?
- Across 2 community benchmark runs, Qwen3.8-27B-Ridge-3.7bpw reaches up to 42.6 tok/s and averages 38.6 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.
- How much memory does Qwen3.8-27B-Ridge-3.7bpw need?
- The leanest observed configuration used about 23.2 GB of memory.
- Which tools have been used to run Qwen3.8-27B-Ridge-3.7bpw?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.