Claude Opus 4.8
Neural Network
Claude Opus 4.8 is an Anthropic model with 1M token context and reasoning support for code and complex tasks in BotHub.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 000 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- none, low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Claude Opus 4.8?
Claude Opus 4.8 is an Anthropic Opus family model that accepts text, images, and files as input and responds with text. The 1M token context window allows you to hold a large codebase, long documents, and the entire discussion history in a single request, while the reasoning mode helps solve tasks where a sequence of steps is more important than a quick answer. The batch option is suitable when it is more convenient to send requests in batches. In BotHub, Claude is available without a VPN or foreign card: you pay with a Russian card in rubles based on actual token usage, and unused tokens do not expire. Other models—over 250—work in the same window, so you can compare answers or switch without rewriting the integration. A unified OpenAI-compatible API and AES-GCM encryption cover integration and privacy needs; for companies, we offer contracts, invoices, electronic document management (EDO), and an admin panel with limits. Useful for refactoring and debugging code, analyzing voluminous reports and contracts, gathering analytics from a set of files, preparing materials for STEM tasks, and supporting multi-step agent scenarios.Frequently asked questions about Claude Opus 4.8
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 context window of up to 1 million tokens. It accepts text, images, and documents, reasons before answering, and calls functions. Suitable for working with code, analyzing large repositories, analytics on voluminous documents, and complex STEM tasks.
In a single response, the model outputs up to 128,000 tokens—that's dozens of pages. Enough to assemble a large code module, a detailed report, or a comprehensive analysis of an entire document without breaking the task into parts. In BotHub, you pay for actual usage, and tokens do not expire.
Yes, reasoning before answering is confirmed: before providing a result, the model builds a chain of thought. This is noticeable where logic is important—code debugging, mathematics, analyzing conflicting requirements in documentation. For simple queries, deep reasoning can be disabled.
Yes. The model supports function calling and structured JSON output, making it easy to integrate into agents and workflows. In BotHub, all this works via a unified OpenAI-compatible API—you can switch models without rewriting the integration.
Images and documents—yes: send a screenshot, diagram, PDF, or contract and get a text analysis. Audio and video input are not supported in our data; for such tasks, BotHub has separate models available in the same window and via the same API.
The language of prompts and output is not specified in our data, so we will not make promises—test the model on your task. The BotHub interface is in Russian, access from the Russian Federation is available without a VPN or foreign card, payment is in rubles, and you can switch to another model with one click.