o4 Mini
OpenAI's mid-tier model. Context window: 200K tokens.
Scores by test
Methodology →What you need to know
o4 Mini differentiates itself through exceptional reasoning and technical precision, particularly in mathematics and structured data. With a 97.8% score on MATH Level 5 and 81.7% on AIME 2025, it operates at a high cognitive tier for a mini-model. Its perfect internal scores in strategic analysis, structured output, and tool calling make it a reliable engine for complex logic and API integrations.
The model handles large-scale data efficiently, combining a 200K context window with top-tier performance in long-context processing and tabular data. At a blended cost of $3.58/MTok, it provides a high ratio of intelligence to price, offering capabilities that typically require larger, more expensive frontier models.
A critical weakness is safety calibration, where it scored 1/5, indicating a lack of alignment or restrictive filtering. It also struggles with constrained rewriting compared to its other capabilities. Developers should implement their own robust guardrails if the application is user-facing or requires strict content moderation.
Use this model if you need a cost-effective solution for complex mathematical reasoning, agentic planning, or processing large datasets into structured formats. Skip this model if your project requires strict built-in safety filters or high precision in constrained rewriting tasks.
Strengths — Top 3
Relative weaknesses — Bottom 3
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