Claude Fable 5
Neural Network
Claude Fable 5 is an Anthropic model for autonomous knowledge and code work with reasoning support.
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 Fable 5?
Claude Fable 5 is an Anthropic Mythos-family model designed for autonomous knowledge work and programming. It accepts text, images, and files, responds with text, and supports reasoning, making it suitable for tasks requiring a chain of steps rather than an immediate answer. In BotHub, the model is accessible from Russia without a VPN or foreign card, with pay-as-you-go billing in rubles for consumed tokens, no subscription required. Over 250 neural networks are available in the same window, allowing easy switching and comparison. A unified OpenAI-compatible API lets you connect Claude Fable 5 to your services and swap it for another model without rewriting integrations. Chats are encrypted, and companies get access to contracts, invoices, and an admin panel with limits. Developers can use it for refactoring, review, and debugging code; analysts for parsing documents and file uploads; product teams for multi-step research and specification drafting; and it can analyze interface screenshots or diagrams to generate text.Frequently asked questions about Claude Fable 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.
This is a Claude text model: it accepts text, documents, and images, and responds with text. A million-token context allows uploading large repositories, contracts, or long chat archives. It is suitable for coding, refactoring, debugging, analyzing large materials, STEM tasks, and function-calling scenarios.
The output limit is 128,000 tokens per response. This is enough for a voluminous technical document, a large code module, or a detailed analysis in its entirety, without splitting into parts. If the task is even larger, split it into sequential requests: the million-token context allows keeping the entire history nearby.
Yes, reasoning before answering is supported. The model first breaks down the condition step-by-step and only then formulates the result — this helps in mathematics, logic, code debugging, and where multiple conditions need to be maintained simultaneously. For simple queries, such analysis is usually not required.
Yes, the model supports function calling and structured JSON output — this is convenient for agents, automation, and integrations where the response goes directly into code. In BotHub, everything works via a unified OpenAI-compatible API, so you can switch models without rewriting integrations.
You can upload images and documents: the model analyzes screenshots, diagrams, charts, and files, and responds with text. There is no note about audio and video in our data, so please check with your own file or select a model in the BotHub catalog specifically designed for that format.
There is no specific note about languages in our data, so we cannot make any promises in advance. The most honest way is to run your real query in BotHub and see the result: access is open from Russia, without a VPN or foreign card, and payment is in rubles based on actual token usage.