GPT 6 Astra Pro Batch
Neural Network
GPT 6 Astra Pro is an OpenAI model with pro reasoning mode: GPT 6 Astra Pro API for complex tasks and batch request processing.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 050 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 6 Astra Pro Batch?
GPT 6 Astra Pro is the same base model as OpenAI's GPT 6 Astra, but run with the reasoning.mode parameter set to 'pro': it spends more reasoning on complex tasks and returns higher-quality answers. The batch variant is designed for batch processing, where requests are sent as an array and the result is needed in bulk, not instantly. In BotHub, the model is available without a VPN or foreign card: pay with a Russian card in rubles for tokens used, which do not expire. Over 250 neural networks are gathered in one window, making it easy to switch between them and compare answers, while a unified OpenAI-compatible API allows you to change models in a multi-model system without rewriting integrations. Data is encrypted via AES-GCM, and for companies, we offer contracts, invoices, EDI, and an admin panel with limits. It is useful for analyzing complex bugs and suggesting refactoring, completing multi-step math or analytics tasks, processing large batches of documents, or building a service where heavy requests go to the reasoning model and simple ones to a fast one.Frequently asked questions about GPT 6 Astra Pro 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 a text model with reasoning: it answers questions, writes and refactors code, debugs errors, analyzes uploaded documents and images, and calls external functions. The context window is 1,050,000 tokens, so large codebases, long reports, and entire archives of correspondence fit into a single dialogue.
Up to 128,000 tokens in a single response — that's dozens of pages of text or a large code module in its entirety. Enough for a detailed analysis, voluminous documentation, a large translation, or a book draft that won't need to be assembled from several pieces manually.
Yes, the reasoning mode is confirmed: before answering, the model builds a chain of steps rather than giving the first solution that comes to mind. This is especially noticeable in math, logic, code debugging, and tasks where you need to sequentially check several conditions and not miss anything.
Yes, the model can call functions and provide structured output in JSON, making it convenient to integrate into agents, bots, and automation. Connection is via the unified OpenAI-compatible BotHub API — you can change models later without rewriting the integration.
Images and documents — yes: send a screenshot, diagram, table, or the entire file and ask to analyze the content. We have no data on audio and video, so it's easier to check the required format directly in the interface — uploading is available on the website and in the Telegram bot.
We have no data on languages, so we won't promise anything specific — it's easier to test the model on your real task. The BotHub interface, payment in rubles, and access from Russia without a VPN or foreign card will certainly not hinder you in this.