Claude Sonnet 5.5
Neural Network
Claude Sonnet 5.5 is an Anthropic Sonnet-class model; Claude for coding, developing new features, and fixing bugs.
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
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Claude Sonnet 5.5?
Claude Sonnet 5.5 is an Anthropic Sonnet-class model designed for daily tasks with clear boundaries. It is a direct successor to Claude Sonnet 5: it holds the same role in the lineup but is stronger where you need to build a new feature, find and fix a bug, understand someone else's code, and bring a fix to a working result. Through BotHub, you can connect to it from Russia without a VPN or foreign card, paying in rubles only for the tokens you use, which do not expire. With over 250 models available in the same window, you can compare answers or switch models in a few clicks. A unified OpenAI-compatible API allows you to change models in your product without rewriting the integration. Requests are transmitted with AES-GCM encryption, and chats are not saved. For teams, we offer contracts, invoices, electronic document management (EDO), an admin panel, and limits. Developers use the model for writing modules and code reviews, team leads for analyzing legacy code and preparing technical descriptions, analysts for regular work with texts and documents, and product teams for rapid prototyping and hypothesis testing.Frequently asked questions about Claude Sonnet 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.
The model works with text, images, and documents, can reason before answering, and call external functions. The context window is one million tokens, making it suitable for analyzing codebases, long reports and contracts, analytics, and tasks you run in batches via API.
The single response limit is 128,000 tokens, which is the size of a small book. You can request an entire technical document, a large code module, or a detailed analysis at once without breaking the task into pieces. If the response hits the limit, continue generation with the next message.
Yes, reasoning before answering is confirmed: the model breaks down the task into steps, checks intermediate conclusions, and only then formulates the result. This significantly helps with math, logic, code debugging, and areas where reasoning accuracy is more important than response speed.
Yes, the model supports function calling and structured JSON output, making it easy to integrate into agents, pipelines, and internal services. A unified OpenAI-compatible API is available in BotHub: you can switch tasks to another model without rewriting the integration.
Images and documents — yes, and documents are read natively without prior recognition: upload screenshots, diagrams, and PDFs with tables. Audio and video are not marked in our data, so it is more reliable to transcribe the recording into text first and then provide it to the model.
There are no separate language benchmarks in our data, so we won't promise figures — test the model with your own texts, it takes a couple of minutes. The BotHub interface, payment in rubles, and access without VPN or foreign cards work from Russia; formulate your prompt however you like.