Model benchmarks
qwen3.5:9b local LLM performance
As of May 2026, qwen3.5:9b runs at up to 36.6 tok/s for local inference (best of 10 community benchmark runs across 2 GPUs).
OllamaQ4_K_M
Model size
9.7B
Peak speed
36.6 tok/s
Average speed
22.8 tok/s
Min memory
8.2 GB
Max context
9,539 tokens
Best quality
90.3
Benchmark runs
10
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.5:9b 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_K_M | 36.6 tok/s | 22.9 tok/s | 8.3 GB | 9,539 tokens | 66.2 | 8 |
| NVIDIA GeForce RTX 5080 | Ollama | Q4_K_M | 24.1 tok/s | 22.3 tok/s | 8.2 GB | 8,286 tokens | 63.0 | 2 |
Frequently asked questions
- How fast is qwen3.5:9b for local inference?
- Across 10 community benchmark runs, qwen3.5:9b reaches up to 36.6 tok/s and averages 22.8 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does qwen3.5:9b need?
- The leanest observed configuration used about 8.2 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run qwen3.5:9b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.