Claude Sonnet 4.6
Anthropic
At a glance
- Price per 1M tokens (input)
- $3.00
- Price per 1M tokens (output)
- $15.00
- Context
- 1,000,000 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The Claude Sonnet model is designed for businesses and organizations that require advanced image understanding and step-by-step reasoning capabilities. This model is well-suited for tasks that involve analyzing visual data, making decisions based on that analysis, and taking subsequent actions. The vendor's approach to developing this model focuses on enabling tool calling, which allows the model to invoke external functions and integrate with other systems, enhancing its overall functionality. By leveraging these capabilities, users can automate complex workflows and improve their overall decision-making processes. The model's ability to understand images and reason about the world makes it a valuable tool for a wide range of applications.
Specifications & pricing
| Input (per 1M tokens) | $3.00 |
|---|---|
| Output (per 1M tokens) | $15.00 |
| Cache read (per 1M tokens) | $0.30 |
| Cache write (per 1M tokens) | $3.75 |
| Context window | 1,000,000 tokens |
| Max output | 64,000 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified August 15, 2026. Official Anthropic pricing.
What Claude Sonnet 4.6 would cost on your workload — run it through the cost calculator →
Where to try Claude Sonnet 4.6 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, such as analyzing visual data, and making decisions based on that analysis, as well as taking subsequent actions through tool calling, which involves invoking external functions to integrate with other systems
How do I get started with this model+
To get started with this model, users should familiarize themselves with the concept of tool calling, and understand how to design workflows that leverage the model's image understanding and reasoning capabilities
How does this model differ from other models in the line+
This model differs from other models in the line due to its advanced image understanding capabilities, and its ability to perform step-by-step reasoning, which enables more complex decision-making and automation workflows
What are the limitations of this model+
The limitations of this model include its reliance on high-quality visual data, and its potential struggles with nuanced or ambiguous images, which can impact the accuracy of its analysis and decision-making
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