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).
OllamaQ4_K_M
Model size
27.3B
Peak speed
35.8 tok/s
Average speed
34.5 tok/s
Min memory
19.3 GB
Max context
7,066 tokens
Best quality
90.4
Benchmark runs
2
GPUs tested
1
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 | 7,066 tokens | 84.3 | 2 |
Frequently asked questions
- 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.