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 Anthropic text model with a 200,000-token context window. It is suitable for parsing large documents, writing and debugging code, data analysis, and reasoning tasks. The batch suffix indicates batch mode: convenient when you need to run many similar requests at once.

Up to 64,000 tokens in a single response — that's dozens of pages of text. Enough for a detailed document analysis or a long code module in its entirety, without manual stitching. If the response hits the limit, ask it to continue from where it stopped.

Yes, reasoning before answering is supported: the model thinks through the steps first and then provides the result. This significantly helps with math, logic, analyzing third-party code, and all tasks where the sequence of steps is important rather than an instant reaction.

Yes. The model calls functions and returns structured JSON according to your schema — this is the foundation for agents, parsers, and integrations with your services. BotHub uses a unified OpenAI-compatible API, so you can switch to another model without rewriting code.

Text, images, and documents are accepted as input: screenshots, diagrams, tables, PDFs — the model will read and parse the content. Audio and video input is not noted in our data, so for such files, you should choose a model with confirmed format support.

The Claude line is multilingual, and the model works confidently with Russian queries: it captures phrasing, terminology, and context without additional settings. Quality still depends on the specific task, so test it with your own materials — access in BotHub is available without a VPN or foreign card.