GPT 5 Batch
Neural Network
GPT-5 Batch is an OpenAI model for complex reasoning and code, with batch processing of large request volumes via the GPT-5 API.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 400 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- minimal, low, medium, high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 5 Batch?
GPT-5 is OpenAI's flagship line, significantly improving step-by-step reasoning, code quality, and instruction following compared to previous versions. The Batch variant is designed for asynchronous batch mode: you send a large array of tasks in one queue and retrieve the result when processing is complete—convenient for regular, high-volume computations where an instant response isn't required. In BotHub, the model is available from Russia without a VPN or foreign card; payment is made with Russian cards in rubles based on token consumption, and tokens do not expire. Requests are encrypted with AES-GCM, and chat history is not saved. A unified OpenAI-compatible API allows you to connect GPT-5 Batch to your service and switch to any of the 250+ available models without rewriting the integration. For teams, we offer contracts, invoices, EDI, an admin panel, and limits. Batch mode is most often used for mass data classification and labeling, generating and reviewing code in batches, parsing technical documentation, analytical reports with complex multi-step calculations, and preparing descriptions for catalogs and knowledge bases.Frequently asked questions about GPT 5 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 a 400,000 token context: it parses long documents, writes and refactors code, helps with debugging, solves math and STEM problems, and extracts data from images and files. Suitable for analytics, support, content generation, and integration into services.
In a single response, the model outputs up to 128,000 tokens—that's dozens of pages of text. Enough for a large technical document, a detailed analysis, or an entire large code module. If the result is larger, break the task into parts and continue generation in segments.
Yes, reasoning mode is confirmed: before answering, the model builds a chain of steps, checks intermediate conclusions, and only then responds. This is noticeable in math, logic, code analysis, and multi-step tasks where it is important not to guess the answer, but to arrive at it sequentially.
Yes. The model can call functions and output structured JSON according to a specified schema, making it easy to connect to external services, databases, and custom tools. In BotHub, this works via a unified OpenAI-compatible API: write the integration once, then change the model in the settings.
Images and documents—yes: you can send a screenshot, diagram, photo, or file and ask to analyze the content, extract numbers, or summarize. There is no mention of audio or video in our data, so count on text, images, and documents.
There is no formal evaluation by language in our data, so we won't promise exact figures. The GPT-5 line generally works with various languages, including Russian, but it's more reliable to test it on your own task: in BotHub, the model is available without a VPN or foreign card, and payment is in rubles.