GPT 4.1 Batch
Neural Network
GPT-4.1 for code and long context: OpenAI model with a 1M token window and precise instruction following.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 047 576 tokens
- Max answer length
- 32 768 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 4.1 Batch?
GPT-4.1 is OpenAI's flagship language model designed for precise adherence to complex instructions, real-world development tasks, and long-context reasoning. The 1M token window allows you to work with an entire repository, voluminous documentation, or long correspondence, and it outperforms GPT-4o in quality. The batch version is designed for batch request processing. Through BotHub, the model is available without a VPN or foreign card: you pay in rubles only for the tokens used, and they do not expire. Alongside, in one window, there are over 250 neural networks, and a unified OpenAI-compatible API allows you to connect GPT-4.1 to your services and change the model later without rewriting the integration; traffic is encrypted, chats are not saved, and for teams, there is a contract, invoice, electronic document management, and an admin panel with limits. Developers will find the model useful for refactoring, reviewing, and debugging code; analysts for parsing long reports and contracts; product teams for mass automation scenarios via API; and editorial teams for working with large text arrays.Frequently asked questions about GPT 4.1 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.
The model works with text, images, and documents: it analyzes long materials, writes and edits code, prepares drafts, and extracts data from scans and PDFs. A context of up to 1,047,576 tokens allows you to keep a large repository or report in one session, and batch mode is convenient for repetitive requests.
In a single response, the model outputs up to 32,768 tokens — enough for a detailed analysis, a large code fragment, or a long document. If you need a larger result, break the task into parts: the large context window allows you to keep the entire source in the chat and continue from the same place.
A separate reasoning mode is not noted in our data, so do not count on a hidden chain of thought. However, you can directly ask in the prompt to break down the task step-by-step, explain the logic, and check itself — this works for math, code analysis, and complex formulations.
Yes, function calling and structured JSON output are confirmed. The model returns an answer according to a specified schema and accesses your tools, which is convenient for agents and automation. In BotHub, this is available via a unified OpenAI-compatible API — you can change the model without rewriting the integration.
Images and documents — yes: send a screenshot, diagram, table, or PDF and ask to analyze the content. Audio and video are not listed in the input formats, but there are over 250 models in BotHub, and you can find a suitable one for audio or video in the same window.
There is no specific information in our data about prompt and response languages, so we will not promise specific accuracy in Russian — test it on your tasks. The BotHub interface is in Russian, payment is in rubles, and access is without VPN or a foreign card, so the test will take a couple of minutes.