Compare / Ministral 3 14B vs Mellum2.1 12B-A2.5B Thinking

Ministral 3 14B vs Mellum2.1 12B-A2.5B Thinking

Updated November 2026

Verdict

Ministral 3 14B and Mellum2.1 12B-A2.5B Thinking are roughly tied on the Small LM Index (61.6 vs 60.8). On the 3 benchmarks both labs report, Ministral 3 14B wins 2 and Mellum2.1 12B-A2.5B Thinking wins 1. Mellum2.1 12B-A2.5B Thinking is smaller: it needs about 8.3 GB of memory at 4-bit, against 10.6 GB for Ministral 3 14B. 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 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 Mellum2.1 12B-A2.5B Thinking if…

you mostly write code
you have limited memory (about 8.3 GB at 4-bit)

Specifications

	Ministral 3 14B	Mellum2.1 12B-A2.5B Thinking
Small LM Index	61.6 (likely 59–64)	60.8 (likely 58–63)
Lab	Mistral AI · Europe	JetBrains (Mellum) · Europe
Released	2025-12-02	2026-09-20
Parameters	14B (dense)	12.2B (2.5B active, MoE)
Memory at 4-bit	~10.6 GB	~8.3 GB
Context window	256K tokens	131K tokens
Input	text, image	text
Reasoning	Hybrid (thinking on/off)	Always thinks
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)	294.9K	10.5K

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	Mellum2.1 12B-A2.5B Thinking
GPQA Diamond Knowledge	71.2	64.6
AIME Math	85.0	83.3
LiveCodeBench Coding	64.6	82.0
SWE-bench Verified Coding	≈ 54	47.0
Terminal-Bench Agentic	—	17.4
MMLU Knowledge	—	87.8
IFEval Instruction following	—	90.6
BFCL Agentic	—	62.3

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 Mellum2.1 12B-A2.5B Thinking?

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. Mellum2.1 12B-A2.5B Thinking is smaller: it needs about 8.3 GB of memory at 4-bit, against 10.6 GB for Ministral 3 14B.

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 Mellum2.1 12B-A2.5B Thinking 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.