Model benchmarks
qwen2.5-coder:7b-instruct local LLM performance
As of July 2026, qwen2.5-coder:7b-instruct runs at up to 17.2 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
7.6B
Peak speed
17.2 tok/s
Average speed
15.2 tok/s
Min memory
4.6 GB
Max context
2,431 tokens
Best quality
78.9
Benchmark runs
2
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination qwen2.5-coder:7b-instruct has been benchmarked on, ranked by peak token generation speed. Last updated July 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M4 | Ollama | Q4_K_M | 17.2 tok/s | 15.2 tok/s | 4.6 GB | 2,431 tokens | 45.3 | 2 |
Frequently asked questions
- How fast is qwen2.5-coder:7b-instruct for local inference?
- Across 2 community benchmark runs, qwen2.5-coder:7b-instruct reaches up to 17.2 tok/s and averages 15.2 tok/s, with the fastest results on Apple M4.
- How much memory does qwen2.5-coder:7b-instruct need?
- The leanest observed configuration used about 4.6 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run qwen2.5-coder:7b-instruct?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.