O3 Batch
Neural Network
O3 Batch is an OpenAI reasoning model for math, science, and code: o3 API for batch request processing.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 200 000 tokens
- Max answer length
- 100 000 tokens
- Reasoning effort
- low, medium, high
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works O3 Batch?
O3 is a versatile OpenAI reasoning model for math, science, programming, visual analysis, precise instruction following, and technical texts. The Batch variant is designed for batch processing, where a queue of requests is sent as an array rather than one by one. In BotHub, the model is available without a VPN or foreign card: pay with a Russian card in rubles for tokens used, and they do not expire. With over 250 neural networks in one window, you can compare answers or switch models without rewriting integrations—the unified OpenAI-compatible API remains the same. Chats are encrypted via AES-GCM, data is not stored, and teams have access to contracts, invoices, electronic document management, and an admin panel with limits. Use cases are simple: break down complex scientific or engineering problems step-by-step, refactor and debug large codebases, prepare technical documentation and specifications, analyze diagrams and images, or queue a batch of analytical requests overnight and retrieve the results in the morning.Frequently asked questions about O3 Batch
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.
This is an OpenAI model for complex text tasks: code analysis and refactoring, debugging, math and STEM calculations, and long document analytics. The 200,000-token context allows you to upload technical documentation, reports, or large repositories and get a coherent analysis.
Up to 100,000 tokens in a single response—enough for extensive technical analysis, detailed documentation, large code modules, or detailed analytical reports. The total dialogue budget is limited to a 200,000-token context, which includes your request.
The model belongs to OpenAI's o-series and supports adjusting the effort for thinking through tasks, making it effective for multi-step problems like proofs, code logic analysis, and calculation chains. If you need detailed intermediate steps, just ask it to break down the solution by stages.
Yes, both function calling and structured JSON output are supported. This is convenient for agents, parsers, and integrations with your services. Through the unified OpenAI-compatible BotHub API, you connect the model once and switch to another without rewriting code.
It accepts text, images, and documents as input, including native file processing. You can send screenshots of errors, diagrams, charts, or PDFs and ask for an analysis of the content. This model does not process audio or video—BotHub has separate models for those.
OpenAI o-series models work confidently with Russian-language queries: you can describe tasks in your own words, send Russian documents, and discuss code. In BotHub, access to the model is provided without a VPN or foreign card, and payment is made in rubles based on actual usage.