Model benchmarks
qwen3-coder-next:latest local LLM performance
As of May 2026, qwen3-coder-next:latest runs at up to 34.1 tok/s for local inference (best of 4 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
79.7B
Peak speed
34.1 tok/s
Average speed
31.4 tok/s
Min memory
50.3 GB
Max context
4,839 tokens
Best quality
94.5
Benchmark runs
4
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3-coder-next:latest has been benchmarked on, ranked by peak token generation speed. Last updated May 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | Ollama | Q4_K_M | 34.1 tok/s | 31.4 tok/s | 50.3 GB | 4,839 tokens | 74.9 | 4 |
Frequently asked questions
- How fast is qwen3-coder-next:latest for local inference?
- Across 4 community benchmark runs, qwen3-coder-next:latest reaches up to 34.1 tok/s and averages 31.4 tok/s, with the fastest results on Apple M5 Max.
- How much memory does qwen3-coder-next:latest need?
- The leanest observed configuration used about 50.3 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run qwen3-coder-next:latest?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.