Claude Fable 5
Anthropic
At a glance
- Price per 1M tokens (input)
- $10.00
- Price per 1M tokens (output)
- $50.00
- Context
- 1,000,000 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 9, 2026.
The Claude Fable model is designed for businesses and organizations that require advanced language understanding and generation capabilities. It is particularly suited for tasks that involve image understanding, step-by-step reasoning, and tool calling, which refers to the ability to call external functions or tools to perform specific tasks. This model's approach is distinguished by its ability to understand and generate human-like language, while also being able to reason and solve problems in a logical and methodical way. The vendor's approach focuses on creating models that can be used in a variety of applications, from customer service to content generation. By leveraging the strengths of this model, businesses can automate tasks, improve customer engagement, and gain valuable insights from their data.
Specifications & pricing
| Input (per 1M tokens) | $10.00 |
|---|---|
| Output (per 1M tokens) | $50.00 |
| Cache read (per 1M tokens) | $1.00 |
| Cache write (per 1M tokens) | $12.50 |
| Context window | 1,000,000 tokens |
| Max output | 128,000 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified August 15, 2026. Official Anthropic pricing.
What Claude Fable 5 would cost on your workload — run it through the cost calculator →
Where to try Claude Fable 5 for free
- Anthropic offers a free chat — Claude (free plan). A vendor's free chat may run a different model from the same family — the exact model is not guaranteed.
- 🎁 On our promo-codes page: Claude Code Guest Pass — a community invite.
Frequently asked questions
What is this model good for+
This model is good for tasks that require image understanding, step-by-step reasoning, and tool calling, making it suitable for applications such as visual question answering, automated reasoning, and workflow automation
How do I get started with this model+
To get started with this model, you will need to integrate it into your application or workflow, which can be done through an API or other interface, and then provide it with the necessary input and guidance to perform the desired tasks
How does this model differ from other models in the line+
This model differs from other models in the line in its ability to understand and generate human-like language, while also being able to reason and solve problems in a logical and methodical way, making it a good choice for applications that require a combination of language understanding and problem-solving abilities
What are the limitations of this model+
The limitations of this model include its reliance on high-quality input data, its potential for bias if trained on biased data, and its need for careful tuning and evaluation to ensure it is performing as expected in a given application or workflow
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