Compare / Ministral 3 14B vs LLaDA2.2 mini
Ministral 3 14B vs LLaDA2.2 mini
Updated November 2026
Verdict
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 29.7. On the 3 benchmarks both labs report, Ministral 3 14B wins 3 and LLaDA2.2 mini wins 0. Both need about 11 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 mostly write code
- you need math and reasoning
- you want a hosted API rather than running it yourself
- you work with long documents
- you need image input
- you want the more widely used model (more quantized builds and community support)
Pick LLaDA2.2 mini if…
No clear advantage in the data we have.
Specifications
| Ministral 3 14B | LLaDA2.2 mini | |
|---|---|---|
| Small LM Index | 60.0 (likely 56–64) | 29.7 (likely 26–34) |
| Lab | Mistral AI · Europe | InclusionAI (Ling) · China |
| Released | 2025-12-02 | 2026-09-05 |
| Parameters | 14B (dense) | 16.3B (1.4B active, MoE) |
| Memory at 4-bit | ~10.6 GB | ~11 GB |
| Context window | 256K tokens | 131K tokens |
| Input | text, image | text |
| Reasoning | Hybrid (thinking on/off) | No thinking |
| 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 | 4K |
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 | LLaDA2.2 mini |
|---|---|---|
| GPQA Diamond Knowledge | 71.2 | 44.4 |
| AIME Math | 85.0 | 35.1 |
| LiveCodeBench Coding | 64.6 | 28.1 |
| τ²-Bench Agentic | — | 57.5 |
| IFBench Instruction following | — | 24.9 |
| BFCL Agentic | — | 47.7 |
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 LLaDA2.2 mini?
Ministral 3 14B scores higher on the Small LM Index: 60.0 vs 29.7. On the 3 benchmarks both labs report, Ministral 3 14B wins 3 and LLaDA2.2 mini wins 0.
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 11 GB of memory at 4-bit quantization.
Which has the longer context window?
Ministral 3 14B has the longer context window: 256K tokens against 131K.
Can I use Ministral 3 14B and LLaDA2.2 mini 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.