GPT-4o-mini
OpenAI's efficiency model. Context window: 128K tokens.
Scores by test
Methodology →What you need to know
GPT-4o-mini is positioned as a low-cost utility model, prioritizing operational efficiency over cognitive depth. With a blended cost of $0.487 per million tokens, it provides an economical entry point for high-volume tasks that do not require complex reasoning.
The model excels at structured, deterministic tasks. It scores consistently high (4/5) in classification, tool calling, and structured output, making it reliable for API-driven workflows and data labeling. Its 128K context window is well-supported, maintaining a 4/5 internal score for long-context processing.
Performance drops significantly in high-reasoning domains. It struggles with strategic analysis and creative problem solving, both scoring 2/5. This cognitive ceiling is further evidenced by a low 6.9% score on the AIME 2025 benchmark, indicating it is unsuitable for advanced mathematics or complex logical synthesis.
Use this model for high-throughput classification, multilingual translation, and basic tool-integrated agents where cost is the primary constraint. Skip this model for applications requiring strategic planning, complex mathematical reasoning, or nuanced creative problem solving.
Strengths — Top 3
Relative weaknesses — Bottom 3
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