Model benchmarks
ministral-3:14b local LLM performance
As of April 2026, ministral-3:14b runs at up to 43.0 tok/s for local inference (best of 6 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
13.9B
Peak speed
43.0 tok/s
Average speed
42.3 tok/s
Min memory
14.4 GB
Max context
65,536 tokens
Avg quality
66.8
Benchmark runs
6
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 6 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 59.7 | 66.8 | 72.1 |
| Agent Workflow | 63.9 | 72.3 | 79.8 |
| Code Generation | 48.8 | 54.6 | 60.2 |
| Role Play & Narrative | 67.6 | 74.2 | 81.6 |
| Research & Analysis | 53.9 | 65.9 | 76.1 |
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 | 43.0 tok/s | 42.3 tok/s | 14.4 GB | 65,536 tokens | 66.7 | 6 |
Frequently asked questions
- Is ministral-3:14b good for coding?
- In our benchmarks, ministral-3:14b scores 54.6/100 for coding. It runs at about 42.3 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for coding (66.9/100).
- Is ministral-3:14b good for agentic (tool-using) tasks?
- In our benchmarks, ministral-3:14b scores 72.3/100 for agentic workflows. It runs at about 42.3 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for agentic workflows (71.7/100).
- How fast is ministral-3:14b for local inference?
- Across 6 community benchmark runs, ministral-3:14b reaches up to 43.0 tok/s and averages 42.3 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 14.4 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.