Model benchmarks
qwen3.8:27b-q4_K_M local LLM performance
As of August 2026, qwen3.8:27b-q4_K_M runs at up to 35.8 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27.3B
Peak speed
35.8 tok/s
Average speed
34.5 tok/s
Min memory
19.3 GB
Max context
65,536 tokens
Avg runtime / run
7m 34s
Avg quality
85.8
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 | 85.1 | 85.8 | 86.5 |
| Agent Workflow | 85.3 | 85.8 | 86.3 |
| Code Generation | 79.7 | 80.7 | 81.7 |
| Role Play & Narrative | 85.1 | 88.3 | 91.4 |
| Research & Analysis | 88.4 | 88.4 | 88.4 |
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.8:27b-q4_K_M 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_K_M | 35.8 tok/s | 34.5 tok/s | 19.3 GB | 65,536 tokens | 85.8 | 2 |
Benchmark runs
All 2 qwen3.8:27b-q4_K_M runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is qwen3.8:27b-q4_K_M good for coding?
- In our benchmarks, qwen3.8:27b-q4_K_M scores 80.7/100 for coding. It runs at about 34.5 tok/s, so if you want more speed, K2-Horizon-MoVA-36B-A4B-MLX-4bit is faster (~48.5 tok/s) and still scores well for coding (82.5/100).
- Is qwen3.8:27b-q4_K_M good for agentic (tool-using) tasks?
- In our benchmarks, qwen3.8:27b-q4_K_M scores 85.8/100 for agentic workflows. It runs at about 34.5 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-q4_K_M for local inference?
- Across 2 community benchmark runs, qwen3.8:27b-q4_K_M reaches up to 35.8 tok/s and averages 34.5 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does qwen3.8:27b-q4_K_M need?
- The leanest observed configuration used about 19.3 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run qwen3.8:27b-q4_K_M?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.