GPT-5.4 Nano
OpenAI's efficiency model. Context window: 400K tokens.
Scores by test
Methodology →What you need to know
GPT-5.4 Nano is defined by its high-reasoning capabilities and massive 400K context window, making it a strong candidate for complex, long-form analysis. It achieves perfect internal scores in strategic analysis, multilingual processing, and structured output, while its 87.8% AIME 2025 score indicates strong mathematical and logical proficiency for a model of this size.
At a blended cost of $0.988/MTok, the model provides high-tier reasoning and long-context handling at a low price point. It effectively bridges the gap between lightweight efficiency and the performance typically reserved for larger, more expensive models.
Performance is inconsistent in utility tasks. It struggles with basic classification and safety calibration, scoring 3/5 in both areas. Developers should expect lower reliability when using the model for strict content filtering or simple categorical labeling.
Use this model for multilingual strategic planning, processing large datasets within a single prompt, or generating structured data. Skip this model if your primary use case is high-precision classification or requires strict safety guardrails.
Strengths — Top 3
Relative weaknesses — Bottom 3
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