Claude Fable 5.1
Neural Network
Claude Fable 5.1 is an Anthropic model for code, large-scale refactoring, and long agentic workflows.
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 Fable 5.1?
Claude Fable 5.1 is an Anthropic language model that advances the Claude Fable 5 line. It has notably improved in agentic programming, long agentic scenarios, and knowledge work, including large-scale refactoring, frontend development, and visual interface components. This is a batch-processing version of the model, convenient for tasks submitted in bulk where instant results are not required. In BotHub, access is available from Russia without a VPN or foreign card; payment is made with Russian cards in rubles based on actual usage, not by subscription. Alongside it in the same window are over 250 models that you can switch between to compare responses to the same prompt. The product features a unified OpenAI-compatible API, so switching models does not require rewriting your integration. Use cases include: navigating large codebases and performing multi-step refactoring, building and fixing frontend code, creating agents that manage tasks over long periods without manual control, analyzing documentation and internal materials, and running batch tasks like reviews, annotations, and labeling.Frequently asked questions about Claude Fable 5.1
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 one-million token context window. It analyzes documents and images, writes and refactors code, finds bugs, solves math and logic problems, and prepares analytics. It is suitable for projects where you need to keep a large project or extensive archive of materials in context.
Up to 128,000 tokens per response, which is dozens of pages of text. Enough for a large technical document, a long code module, or a detailed analysis. If you need more volume, split the work into parts and continue generation with subsequent requests.
Yes, reasoning mode is confirmed: the model thinks through the solution process before providing an answer. This is noticeable in multi-step tasks like debugging, math, and analyzing long documents. For simple queries, this mode is usually not needed, and the answer comes immediately.
Yes, both function calling and structured JSON output are supported. You describe the tools, the model decides when to call them, and returns arguments in the specified schema. Convenient for agents and integrations: the response goes directly into the code without parsing free text.
In addition to text, images and documents are accepted as input, including natively—you can provide the file as a whole without pre-recognition. We have no data on audio and video, so we cannot promise support: please check with your own file in the BotHub interface.
We do not publish specific data on languages for this model, so it is better to evaluate it yourself: submit your typical query and compare the result with another model in the same window. The BotHub interface is in Russian, payment is in rubles, and access is available without a VPN or foreign card.