O3
Neural Network
o3 is an OpenAI model focused on step-by-step reasoning: o3 for code, math, science, and visual tasks.
Max answer length
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Context size
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Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works O3?
o3 is an OpenAI model built around step-by-step reasoning: it handles math, science, programming, and visual analysis with equal confidence, follows instructions accurately, and manages technical texts where structure and precision are key. You can use it in BotHub without a VPN or foreign card: pay with Russian cards in rubles, only for tokens used, which do not expire. With over 250 models in one window, it's easy to compare o3 with others on the same task, and the unified OpenAI-compatible API allows switching between them without rewriting integrations. Dialogues are encrypted, and teams have access to contracts, invoices, EDI, and an admin panel with limits. Engineers can use the model to analyze unfamiliar code, refactor, and debug; analysts to extract logic from charts, diagrams, or screenshots; researchers to derive formulas and verify solutions; and product teams for technical documentation and specifications.Frequently asked questions about O3
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 is an OpenAI model for complex tasks: analyzing long documents, analytics, math and STEM, writing and refactoring code, and debugging. It accepts text, images, and files as input, making it suitable for working with reports, diagrams, and interface screenshots.
Up to 100,000 tokens in a single response, with a 200,000 token context window. This is enough for a voluminous technical document, a detailed code base analysis, or a long analytical report without breaking the task into parts.
Yes, o3 belongs to OpenAI's line of reasoning models: it processes the task step-by-step before providing a result. In BotHub, an effort parameter is available, allowing you to adjust the depth of reasoning — from quick answers to thorough analysis.
Yes. The model supports function calling and structured JSON output, making it easy to integrate into agents and pipelines. Connection is via BotHub's unified OpenAI-compatible API — you can swap in another model without rewriting the integration.
According to our data, text, images, and documents are accepted as input, including native file processing. Audio and video are not in the list of input formats — for such tasks, BotHub has separate transcription and video processing models.
o3 is one of OpenAI's multilingual models and works confidently with Russian-language queries and documents. We do not have specific language benchmarks, so please test the model on your task: in BotHub, you pay per token used, without a subscription.