PDF support
Process PDFs with Claude 3.5 Sonnet. Extract text, analyze charts, and understand visual content from your documents.
You can now ask Claude bout any text, pictures, charts, and tables in PDFs you provide. Some sample use cases:
- Analyzing financial reports and understanding charts/tables
- Extracting key information from legal documents
- Translation assistance for documents
- Converting document information into structured formats
Before you begin
Check PDF requirements
Claude works with any standard PDF. However, you should ensure your request size meet these requirements when using PDF support:
| Requirement | Limit |
|---|---|
| Maximum request size | 32MB |
| Maximum pages per request | 100 |
| Format | Standard PDF (no passwords/encryption) |
Please note that both limits are on the entire request payload, including any other content sent alongside PDFs.
Since PDF support relies on Claude’s vision capabilities, it is subject to the same limitations and considerations as other vision tasks.
Supported platforms and models
PDF support is currently available on both Claude 3.5 Sonnet models (claude-3-5-sonnet-20241022, claude-3-5-sonnet-20240620) via direct API access. This functionality will be supported on Amazon Bedrock and Google Vertex AI soon
Process PDFs with Claude
Send your first PDF request
Let’s start with a simple example using the Messages API:
How PDF support works
When you send a PDF to Claude, the following steps occur:
The system extracts the contents of the document.
- The system converts each page of the document into an image.
- The text from each page is extracted and provided alongside each page’s image.
Claude analyzes both the text and images to better understand the document.
- Documents are provided as a combination of text and images for analysis.
- This allows users to ask for insights on visual elements of a PDF, such as charts, diagrams, and other non-textual content.
Claude responds, referencing the PDF's contents if relevant.
Claude can reference both textual and visual content when it responds. You can further improve performance by integrating PDF support with:
- Prompt caching: To improve performance for repeated analysis.
- Batch processing: For high-volume document processing.
- Tool use: To extract specific information from documents for use as tool inputs.
Estimate your costs
The token count of a PDF file depends on the total text extracted from the document as well as the number of pages:
- Text token costs: Each page typically uses 1,500-3,000 tokens per page depending on content density. Standard API pricing applies with no additional PDF fees.
- Image token costs: Since each page is converted into an image, the same image-based cost calculations are applied.
You can use token counting to estimate costs for your specific PDFs.
Optimize PDF processing
Improve performance
Follow these best practices for optimal results:
- Place PDFs before text in your requests
- Use standard fonts
- Ensure text is clear and legible
- Rotate pages to proper upright orientation
- Use logical page numbers (from PDF viewer) in prompts
- Split large PDFs into chunks when needed
- Enable prompt caching for repeated analysis
Scale your implementation
For high-volume processing, consider these approaches:
Use prompt caching
Cache PDFs to improve performance on repeated queries:
Process document batches
Use the Message Batches API for high-volume workflows:
Next steps
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