Model Comparison
Gemma 3 12B vs Ministral 3 (14B Reasoning 2512)Which is better in 2026?
Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks. Gemma 3 12B is 3.2x cheaper per token.
Verdict: Gemma 3 12B vs Ministral 3 (14B Reasoning 2512) — which is better?
Gemma 3 12B (by Google) and Ministral 3 (14B Reasoning 2512) (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Gemma 3 12B outperforms in 0 benchmarks, while Ministral 3 (14B Reasoning 2512) is better at 2 benchmarks (GPQA, LiveCodeBench). Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.
On price, Gemma 3 12B is roughly 3.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Ministral 3 (14B Reasoning 2512) also accepts a larger context window (262,100 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemma 3 12B if…
- cost matters — it's about 3.2x cheaper per token
Choose Ministral 3 (14B Reasoning 2512) if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 262,100 token context window
- you want the most recent training data — it shipped Dec 2025
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 3 12B outperforms in 0 benchmarks, while Ministral 3 (14B Reasoning 2512) is better at 2 benchmarks (GPQA, LiveCodeBench).
Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3 12B ($0.05/1M tokens) is 4.0x cheaper than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).
For output processing, Gemma 3 12B ($0.10/1M tokens) is 2.0x cheaper than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).
In conclusion, Ministral 3 (14B Reasoning 2512) is more expensive than Gemma 3 12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ministral 3 (14B Reasoning 2512) has 2.0B more parameters than Gemma 3 12B, making it 16.7% larger.
Context Window
Maximum input and output token capacity
Ministral 3 (14B Reasoning 2512) accepts 262,100 input tokens compared to Gemma 3 12B's 131,072 tokens. Ministral 3 (14B Reasoning 2512) can generate longer responses up to 262,100 tokens, while Gemma 3 12B is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Both Gemma 3 12B and Ministral 3 (14B Reasoning 2512) support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 12B
Ministral 3 (14B Reasoning 2512)
License
Usage and distribution terms
Gemma 3 12B is licensed under Gemma, while Ministral 3 (14B Reasoning 2512) uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemma 3 12B was released on 2025-03-12, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.
Ministral 3 (14B Reasoning 2512) is 9 months newer than Gemma 3 12B.
Mar 12, 2025
1.2 years ago
Dec 4, 2025
6 months ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Gemma 3 12B is available from DeepInfra. Ministral 3 (14B Reasoning 2512) is available from Mistral AI.
Gemma 3 12B
Ministral 3 (14B Reasoning 2512)
Outputs Comparison
Key Takeaways
Gemma 3 12B
View detailsDetailed Comparison
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FAQ
Common questions about Gemma 3 12B vs Ministral 3 (14B Reasoning 2512).