Claude Opus 5.5
Neural Network
Claude Opus 5.5 is Anthropic's flagship model for reasoning, development, and agentic tasks; Claude for code in large projects.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 000 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- low, medium, high, extra high, max
- Capabilities
- reasoning, function calling, Batch API
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Claude Opus 5.5?
Claude Opus 5.5 is Anthropic's flagship model for complex reasoning, programming, and long-running agentic tasks. It inherits from the Claude Opus 5 line and is particularly adept at handling multi-step changes in large codebases. In BotHub, the model is available without a VPN or foreign card; payment is in rubles based on actual token usage. You have access to over 250 other neural networks in the same window, making it easy to switch between them and compare responses. A unified OpenAI-compatible API connects Claude Opus 5.5 to your services, allowing you to switch models without rewriting integrations. Chats are encrypted via AES-GCM, and companies have access to contracts, invoices, electronic document management (EDO), and an admin panel with limits. It is useful when refactoring a large project, analyzing unfamiliar code, debugging, building an agent with a long chain of steps, designing service architecture, or untangling technical tasks requiring sequential reasoning.Frequently asked questions about Claude Opus 5.5
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.
claude-opus-5.5 works with text, images, and documents, reasons before answering, and calls external functions. A million-token context allows you to work with a large codebase, a set of contracts, or an entire research project: it is suitable for code analysis and refactoring, analytics, and complex multi-step tasks.
In a single response, the model generates up to 128,000 tokens — that's dozens of pages of coherent text. It's enough to assemble a large code module, a detailed report, or a comprehensive document analysis without breaking the task into pieces. If you need more, just continue the dialogue with the next request.
Yes, the reasoning mode is confirmed: the model first builds a solution path and only then formulates an answer. The difference is noticeable in math, logic, code debugging, and tasks where many conditions need to be reconciled at once. You will barely notice this on short, everyday queries.
Yes, both function calling and structured JSON output are supported. The model decides when to call your tool and returns arguments according to a specified schema — this is convenient for agents, document parsing, and integrations. In BotHub, everything works via a unified OpenAI-compatible API.
Images and documents are accepted as input: upload a screenshot, diagram, table, or PDF and ask to analyze the content. Audio and video are not marked in our data for this model. For working with audio and video, BotHub has specialized models in the same window.
We do not have specific data on query and response languages, so we will not provide ratings — it is faster to test the model with your own text right in the chat. The BotHub interface is in Russian, payment is accepted via Russian bank cards, and no VPN or foreign card is required.