Model benchmarks
ministral-3:14b local LLM performance
As of April 2026, ministral-3:14b runs at up to 47.0 tok/s for local inference (best of 12 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
13.9B
Peak speed
47.0 tok/s
Average speed
43.3 tok/s
Min memory
10.6 GB
Max context
5,481 tokens
Best quality
91.4
Benchmark runs
12
GPUs tested
1
Performance by hardware and tool
Every hardware/tool/quantization combination ministral-3:14b 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 | 47.0 tok/s | 43.3 tok/s | 10.6 GB | 5,481 tokens | 67.4 | 12 |
Frequently asked questions
- How fast is ministral-3:14b for local inference?
- Across 12 community benchmark runs, ministral-3:14b reaches up to 47.0 tok/s and averages 43.3 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does ministral-3:14b need?
- The leanest observed configuration used about 10.6 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run ministral-3:14b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.