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Model details

o4 Mini

o4-mini sits inside OpenAI's o-series of reasoning models, launched alongside o3 as a paired release on April 16, 2025. Like its siblings, it is trained to deliberate longer before answering, positioning it for tasks where step-by-step thinking, careful tool selection, and structured responses matter more than raw speed. Its place in the o-series lineage means it inherits the same training philosophy aimed at producing more considered, agentic behavior across complex queries.

Practically, the model fits workflows that blend reasoning with tool use, such as breaking down multi-step problems, orchestrating external tools, and generating well-formatted outputs for downstream systems. A subsequent release on June 10, 2025 extended the broader o-series lineup with o3-pro for Pro users and the API, signaling continued investment in the reasoning family and a roadmap that benefits the smaller o4-mini variant as the ecosystem matures.

Merge Gatewayopenai/o4-minio-mini

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Model key
openai/o4-mini
Release date
Apr 16, 2025
Last updated
Apr 16, 2025
Knowledge cutoff
2024-05
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.10
Output token cost
$4.40

Limits

Output tokens
100,000 tokens
Context window
200,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about o4 Mini

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Coverage

A Hacker News thread dated April 16, 2025 contains a comment from an OpenAI employee (tedsanders) clarifying the deployment of o4-mini: "In ChatGPT, o4-mini is replacing o3-mini. It's a straight 1-to-1 upgrade." The same comment explains that in the API, o4-mini is a new model option and that OpenAI continues to suppor This first-party statement on the HN thread provides explicit creator attribution to OpenAI and concrete developer-impact detail on the API coexistence policy between o4-mini and o3-mini. The commenter also references OpenAI's prior naming conventions (e.g., text-davinci-002, text-earhart-001) to explain versioning rat

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