Ministral 3 14B 2512
Mistral's efficiency model. Context window: 262K tokens.
Scores by test
Methodology →What you need to know
Ministral 3 14B 2512 is most effective for applications requiring strict persona adherence and reliable structured data. It achieves a perfect 5/5 in persona consistency and strong 4/5 scores across tool calling and structured output, making it a viable option for building specialized assistants or API-driven workflows.
The model provides a massive 262K context window at a low price point of $0.200 per million tokens for both input and output. While its overall rank is low (#111 of 130), the cost-to-capability ratio is favorable for high-volume tasks that do not require complex reasoning.
There is a significant deficiency in safety calibration, which scores a 1/5, indicating a lack of built-in guardrails. Additionally, its agentic planning capabilities are mediocre (3/5), suggesting it will struggle with multi-step autonomous task execution compared to higher-ranked models.
Use this model if you need a cheap, long-context engine for roleplay, data extraction, or tool-integrated tasks where you can manage safety filtering externally. Skip this model if your application requires autonomous agentic planning or strict native safety alignments.
Strengths — Top 3
Relative weaknesses — Bottom 3
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