Compare / Ministral 3 14B vs Phi-4
Ministral 3 14B vs Phi-4
Updated November 2026
Verdict
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 44.7. On the 1 benchmark both labs report, Ministral 3 14B wins 1 and Phi-4 wins 0. Both need about 11.4 GB of memory at 4-bit quantization. Phi-4 is cheaper through an API: $0.070 per million tokens against $0.20.
Pick Ministral 3 14B if…
- you want the strongest model overall
- you work with long documents
- you need image input
Pick Phi-4 if…
- API cost matters most
Specifications
| Ministral 3 14B | Phi-4 | |
|---|---|---|
| Small LM Index | 60.0 (likely 56–64) | 44.7 (likely 35–55) |
| Lab | Mistral AI · Europe | Microsoft (Phi) · United States |
| Released | 2025-12-02 | 2024-12-12 |
| Parameters | 14B (dense) | 14.7B (dense) |
| Memory at 4-bit | ~10.6 GB | ~11.4 GB |
| Context window | 256K tokens | 16K tokens |
| Input | text, image | text |
| Reasoning | Hybrid (thinking on/off) | No thinking |
| License | Apache-2.0 | MIT |
| API price / 1M tokens | $0.20 ($0.20 in, $0.20 out) | $0.070 ($0.056 in, $0.11 out) |
| Hugging Face downloads (30 days) | 294.8K | 327K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Ministral 3 14B | Phi-4 |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 79 | 70.4 |
| GPQA Diamond Knowledge | 71.2 | 56.1 |
| AIME Math | 85.0 | ≈ 61 |
| LiveCodeBench Coding | 64.6 | ≈ 50 |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Ministral 3 14B or Phi-4?
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 44.7. On the 1 benchmark both labs report, Ministral 3 14B wins 1 and Phi-4 wins 0.
Which is cheaper to run?
Phi-4 is cheaper through an API: $0.070 per million tokens against $0.20. Both need about 11.4 GB of memory at 4-bit quantization.
Which has the longer context window?
Ministral 3 14B has the longer context window: 256K tokens against 16K.
Can I use Ministral 3 14B and Phi-4 commercially?
Ministral 3 14B is released under Apache-2.0 and Phi-4 under MIT. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.