Compare / Ministral 3 14B vs Gemma 4 12B
Ministral 3 14B vs Gemma 4 12B
Updated November 2026
Verdict
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 56.9, although their likely ranges overlap, so the lead is not certain. On the 3 benchmarks both labs report, Ministral 3 14B wins 1 and Gemma 4 12B wins 2. Both need about 10.6 GB of memory at 4-bit quantization. Only Ministral 3 14B has a hosted API on OpenRouter ($0.20 per million tokens); the other has to be self-hosted.
Pick Ministral 3 14B if…
- you want the strongest model overall
- you need math and reasoning
- you want a hosted API rather than running it yourself
Pick Gemma 4 12B if…
- you mostly write code
- you want the more widely used model (more quantized builds and community support)
Specifications
| Ministral 3 14B | Gemma 4 12B | |
|---|---|---|
| Small LM Index | 60.0 (likely 56–64) | 56.9 (likely 53–61) |
| Lab | Mistral AI · Europe | Google · United States |
| Released | 2025-12-02 | 2026-06-03 |
| Parameters | 14B (dense) | 11.9B (dense) |
| Memory at 4-bit | ~10.6 GB | ~8.9 GB |
| Context window | 256K tokens | 256K tokens |
| Input | text, image | text, image, audio |
| Reasoning | Hybrid (thinking on/off) | Hybrid (thinking on/off) |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | $0.20 ($0.20 in, $0.20 out) | Self-host only |
| Hugging Face downloads (30 days) | 294.8K | 1.8M |
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 | Gemma 4 12B |
|---|---|---|
| MMLU-Pro Knowledge | ≈ 79 | 77.2 |
| GPQA Diamond Knowledge | 71.2 | 78.8 |
| Humanity's Last Exam Reasoning | ≈ 11 | 5.2 |
| AIME Math | 85.0 | 77.5 |
| LiveCodeBench Coding | 64.6 | 72.0 |
| τ²-Bench Agentic | — | 69.0 |
| MMMU-Pro Vision | — | 69.1 |
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 Gemma 4 12B?
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 56.9, although their likely ranges overlap, so the lead is not certain. On the 3 benchmarks both labs report, Ministral 3 14B wins 1 and Gemma 4 12B wins 2.
Which is cheaper to run?
Only Ministral 3 14B has a hosted API on OpenRouter ($0.20 per million tokens); the other has to be self-hosted. Both need about 10.6 GB of memory at 4-bit quantization.
Which has the longer context window?
Both have a 256K-token context window.
Can I use Ministral 3 14B and Gemma 4 12B commercially?
Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.