O3 Mini
Neural Network
O3 Mini is an OpenAI reasoning model for STEM, math, and coding tasks with adjustable reasoning depth.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works O3 Mini?
O3 Mini is a cost-effective OpenAI reasoning model tailored for STEM: science, math, and programming. Its key feature is the 'reasoning_effort' parameter, which lets you control how much the model thinks before answering: less effort for simple questions and quick answers, more for multi-step derivations and complex code analysis. Via BotHub, the model works from Russia without a VPN or foreign card; payment is in rubles based on actual usage, and unused tokens do not expire. Other neural networks are available in the same window, allowing you to compare answers on a single task. A unified OpenAI-compatible API lets you switch between them without rewriting integrations. Data is encrypted, and for companies, we offer contracts, invoices, and an admin panel with limits. It is useful when you need to break down an engineering task step-by-step, find a bug in a function and explain its cause, rewrite a module more cleanly, summarize statistical calculations, or compile the technical part of a training course.Frequently asked questions about O3 Mini
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
o3-mini works with text and documents: code analysis and refactoring, debugging, math and other STEM tasks, analytics on uploaded files, and function calling. A 200,000-token context allows you to keep a large project or a long document entirely within one conversation.
Up to 100,000 tokens in a single response — this is a very long text: a large code module, a detailed technical analysis, or a translation of a voluminous document. If the response hits the limit, ask it to continue, and the model will write the rest in the next message.
o3-mini is a model from OpenAI's o3 line, designed for step-by-step task analysis rather than instant answers. An effort level parameter is available in the interface and API: increase it for complex code and math tasks, decrease it when speed is more important.
Yes, o3-mini supports function calling and structured JSON output, making it easy to integrate into agents and services: the model decides when to call your tool and returns the answer in the specified schema. In BotHub, this is available via a unified OpenAI-compatible API.
According to our data, text and documents are accepted as input — files can be uploaded directly into the chat and you can ask to analyze their content. For images, audio, and video, switch to a model with the required modality in the same BotHub window; you won't need to rewrite the integration.
The language of prompts and responses is not specified in our data, so test it with your own task — a couple of queries will show the result more accurately than any promises. In BotHub, you pay per token, without a subscription, and can compare the answer with another model in the same window.