Model benchmarks
qwen3.8:27b-mtp-q4_K_M local LLM performance
As of September 2026, qwen3.8:27b-mtp-q4_K_M runs at up to 42.9 tok/s for local inference (best of 4 community benchmark runs across 2 GPUs).
Model size
27.3B
Peak speed
42.9 tok/s
Average speed
36.6 tok/s
Avg PP
417.9 tok/s
Min memory
16.2 GB
Max context
65,536 tokens
Avg output / run
16,343 tokens
Avg runtime / run
7m 24s
Avg quality
84.7
Benchmark runs
4
GPUs tested
2
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 4 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 | 80.6 | 84.7 | 88.0 |
| Agent Workflow | 86.1 | 87.9 | 89.9 |
| Code Generation | 61.7 | 74.1 | 82.4 |
| Role Play & Narrative | 83.3 | 89.4 | 93.3 |
| Research & Analysis | 84.1 | 87.2 | 88.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.8:27b-mtp-q4_K_M 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 XTX | Ollama | Q4_K_M | 42.9 tok/s | 40.8 tok/s | 16.2 GB | 65,536 tokens | 83.5 | 3 |
| AMD Radeon RX 9050 / 9060 XT | Ollama | Q4_K_M | 24.2 tok/s | 24.2 tok/s | 19.1 GB | 65,536 tokens | 88.1 | 1 |
Benchmark runs
All 4 qwen3.8:27b-mtp-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-mtp-q4_K_M good for coding?
- In our benchmarks, qwen3.8:27b-mtp-q4_K_M scores 74.1/100 for coding. It runs at about 36.6 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-mtp-q4_K_M good for agentic (tool-using) tasks?
- In our benchmarks, qwen3.8:27b-mtp-q4_K_M scores 88.0/100 for agentic workflows. It runs at about 36.6 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-mtp-q4_K_M for local inference?
- Across 4 community benchmark runs, qwen3.8:27b-mtp-q4_K_M reaches up to 42.9 tok/s and averages 36.6 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does qwen3.8:27b-mtp-q4_K_M need?
- The leanest observed configuration used about 16.2 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run qwen3.8:27b-mtp-q4_K_M?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.