Model benchmarks
mistral-small3.2:latest local LLM performance
As of April 2026, mistral-small3.2:latest runs at up to 32.5 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
24.0B
Peak speed
32.5 tok/s
Average speed
22.0 tok/s
Min memory
20.0 GB
Max context
5,068 tokens
Best quality
85.1
Benchmark runs
2
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination mistral-small3.2:latest has been benchmarked on, ranked by peak token generation speed. Last updated April 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_K_M | 32.5 tok/s | 22.0 tok/s | 20.0 GB | 5,068 tokens | 69.4 | 2 |
Frequently asked questions
- How fast is mistral-small3.2:latest for local inference?
- Across 2 community benchmark runs, mistral-small3.2:latest reaches up to 32.5 tok/s and averages 22.0 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does mistral-small3.2:latest need?
- The leanest observed configuration used about 20.0 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run mistral-small3.2:latest?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.