Claude Sonnet 4.5 chat from Anthropic through an OpenAI-compatible endpoint. It takes up to 198,000 tokens of text and image context and returns up to 64,000, with temperature and top_p control, up to 128 tool definitions and SSE streaming.
Workbench
These examples were written for this endpoint. Replace the prompt and sample media URLs with your own accessible inputs, then check the current quote and model availability before submitting.
- Input types
- Text
- Output types
- Text
- Input
- $2.70 / 1 million tokens
- Cached input
- $0.27 / 1 million tokens
- Output
- $13.50 / 1 million tokens
- Context
- 198K
- Max output
- 64K
$2.70/13.50per 1 million tokens · input / output
bulk-classification The cheap end of the range: a fixed system message, and only the material changes. JSON is asked for in the prompt because there is no response_format, so validate what comes back.
- 2000
- Input types
- Text
- Output types
- Text
- Input
- $2.70 / 1 million tokens
- Cached input
- $0.27 / 1 million tokens
- Output
- $13.50 / 1 million tokens
- Context
- 198K
- Max output
- 64K
$2.70/13.50per 1 million tokens · input / output
tool-loop One agent turn with tools. Tool results stay in the thread and count against the window, so a long chain needs a trimming rule of your own.
- 4000
- Input types
- Text
- Output types
- Text
- Input
- $2.70 / 1 million tokens
- Cached input
- $0.27 / 1 million tokens
- Output
- $13.50 / 1 million tokens
- Context
- 198K
- Max output
- 64K
$2.70/13.50per 1 million tokens · input / output
mid-length-analysis One analysis with the material supplied in full, the shape a 198,000-token window handles without a retrieval layer in front of it.
- 6000
This example starts at Input $2.70 / Output $13.50 per 1 million tokens. The Playground updates the estimate when you change the settings.
