Claude AI File Upload and Reading: formats, limits, and operational behavior

Graziano Stefanelli
Oct 7
5 min read

Claude AI has evolved into a multi-surface system capable of reading, summarizing, and analyzing complex documents, images, and datasets. Across the Claude web app, Projects environment, and API integrations, file handling follows a consistent logic: data is parsed, text is extracted, and visual elements are interpreted through multimodal vision. However, file size, type, and context limitations vary depending on how the user interacts with the model. Understanding these parameters is essential to plan effective document workflows for research, analysis, or automation.

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File uploads in the Claude app.

The Claude web interface allows users to attach up to 20 files per chat, each with a maximum size of 30 MB. Supported file formats include PDF, DOCX, TXT, CSV, HTML, RTF, EPUB, and other text-based or structured data types. Image formats such as JPEG, PNG, GIF, and WebP are also accepted, up to 8,000 × 8,000 pixels.

When users upload files, Claude automatically extracts the textual content for reasoning. Embedded graphics are identified only if the file is in a vision-enabled format such as PDF or image. Within this 30 MB limit, users can combine multiple documents in one conversation, and the model merges their content dynamically. However, the total usable material is still constrained by Claude’s context window, which governs how much text the model can retain and process at once.

In addition to chat uploads, Claude Projects allow for a larger corpus of files to be stored and reused. Projects maintain the same 30 MB per-file limit but permit virtually unlimited total file counts. The actual reading limit depends on the model’s context capacity, which determines how much data can be referenced in a single query.

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How Claude reads and interprets documents.

Claude processes uploaded material in two main ways:

Text extraction: For standard documents (TXT, DOCX, CSV, RTF, HTML), the model extracts raw text and treats it as a reading source for summaries, answers, or transformations. Embedded charts or figures are ignored unless the file is image-based.
Multimodal interpretation: For PDFs and image formats, Claude uses its vision layer to analyze both text and visual content. This allows it to read scanned pages, charts, or embedded images, not just textual elements.

This dual approach makes Claude suitable for research, financial analysis, contract review, or data explanation. However, users should note that long PDFs with heavy image content consume more context space than plain-text equivalents. For best performance, large documents should be divided by chapter or section before upload.

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File size limits across environments.

Claude’s capacity differs between the Claude app, Projects, and API access points. Anthropic defines precise limits for each, balancing performance and reliability.

Table — File upload limits by environment.

Environment	Per-file size	File count	Notes
Claude app (chat)	30 MB	20 per chat	All users; text and images allowed
Claude Projects (KB)	30 MB	Unlimited	Limited only by model context window
Anthropic API – Messages	32 MB per request	—	Total request payload limit
Anthropic API – Files API	500 MB per file	—	Files can be uploaded once and reused via file_id
Amazon Bedrock (Claude)	4.5 MB per doc, 3.75 MB per image	5 docs / 20 images	Applies to Bedrock integration only

This structure enables small document handling in the web app and large-scale processing through the Files API, which supports files up to 500 MB each for reuse in multiple requests.

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Supported file formats and use cases.

Claude recognizes a wide range of document and data types.

Documents: PDF, DOCX, TXT, RTF, HTML, EPUB.
Data files: CSV, TSV, and other text-delimited structures for analysis.
Images: JPEG, PNG, GIF, WebP, up to 8,000 × 8,000 pixels.

For analytical tasks such as processing financial statements, datasets, or logs, CSV and TSV files are recommended, as they enable clean numerical reading without format artifacts. When handling image-heavy PDFs or presentation decks, users should isolate key sections or export text-based pages to improve speed and context efficiency.

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File handling through the Anthropic API.

Developers can upload files directly through the Anthropic API, using two distinct pathways:

Messages API: sends data inline with each request, limited to 32 MB per call.
Files API: uploads files (up to 500 MB) once and references them by file_id in future queries.

This separation improves performance by avoiding redundant transfers. Developers managing large repositories—such as academic papers or support tickets—can store them through the Files API and query only specific sections as needed.

When operating at scale, it is best practice to compress text where possible and ensure that long documents are segmented logically to remain within the 32 MB message boundary.

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File handling on Amazon Bedrock.

When Claude is deployed via Amazon Bedrock, stricter upload constraints apply. Bedrock permits only five documents (≤ 4.5 MB each) and twenty images (≤ 3.75 MB each) per request. These limitations apply exclusively to user messages, meaning files cannot be attached to system or assistant roles.

This configuration makes Bedrock suitable for production environments with fixed input sizes, but users must preprocess larger documents externally or reference them through retrieval systems.

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Common issues and best practices.

Several predictable challenges occur during document upload and analysis, most of which are linked to size or structure.

Truncated or partial responses: Often a sign of exceeding the model’s context window. Splitting large PDFs or text files by section prevents data loss.
Inconsistent formatting: Files exported from rich editors (Word, Pages) may contain hidden styles. Converting to plain text or CSV improves stability.
Upload failures in API: Exceeding the 32 MB message limit triggers request_too_large. Use the Files API for these cases.
Parsing errors in Bedrock: Caused by files exceeding strict size caps; resizing or reformatting is required.

Following these operational guidelines ensures consistent reading accuracy and prevents context overflow in long or complex analyses.

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Operational summary.

Claude AI’s file processing architecture balances user accessibility with high technical limits through the API. The web interface provides simplicity with 30 MB per file and 20 attachments per chat, while Projects extend this to organized multi-file workspaces. Developers gain large-scale ingestion through the 500 MB Files API.

Together, these mechanisms allow Claude to read documents as both text and visual input, offering flexible pathways for researchers, analysts, and enterprises who depend on document-rich workflows.

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DATA STUDIOS

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