GPT-5 Mini
OpenAI's mid-tier model. Context window: 400K tokens.
Scores by test
Methodology →What you need to know
GPT-5 Mini distinguishes itself through exceptional reasoning and precision, particularly in strategic analysis and structured output. With a 5/5 internal score across faithfulness, tabular data, and multilingual capabilities, the model is highly reliable for tasks requiring strict adherence to formats and factual accuracy. This is further supported by strong external performance in high-complexity mathematics, scoring 97.8% on MATH Level 5 and 86.7% on AIME 2025.
The model provides a massive 400K context window, which it utilizes effectively as evidenced by a 5/5 long-context internal score. At a blended cost of $1.56/MTok, it offers a high-performance ratio for developers who need deep reasoning and large-scale data processing without the cost of a full-scale frontier model.
Performance is inconsistent in execution-heavy tasks. Tool calling and safety calibration are the model's primary weaknesses, both scoring 3/5. While it excels at planning and analysis, it is less reliable when tasked with interacting with external APIs or maintaining strict safety guardrails.
Use this model for complex data extraction, strategic planning, and high-accuracy mathematical tasks involving large datasets. Skip this model if your primary requirement is autonomous tool use or if your application requires the highest level of safety calibration.
Strengths — Top 3
Relative weaknesses — Bottom 3
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