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

Claude AI supports direct file uploads across chat, Projects, and API environments, allowing users to analyze documents, spreadsheets, and images through natural language interaction. Whether used in its web interface or integrated via the Anthropic API, the model reads both text-based and multimodal content, transforming unstructured data into summaries, insights, and answers. However, each environment applies distinct rules for file formats, size limits, and context usage.

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File uploads in the Claude app.

In the Claude web app, users can attach up to 20 files per chat, with a maximum size of 30 MB per file. Supported file formats include PDF, DOCX, TXT, CSV, TSV, HTML, RTF, EPUB, and other common text-based structures. The platform also accepts images in JPEG, PNG, GIF, and WebP formats, up to 8,000 × 8,000 pixels and 30 MB per file.

Claude automatically extracts text and interprets visual elements, enabling mixed-content understanding such as charts, scanned pages, or tables inside documents. When working with Claude Projects, the same per-file limit applies—30 MB—but Projects can hold unlimited files, effectively functioning as long-term document repositories. The usable content in each prompt, however, is governed by Claude’s context window, meaning that not all stored material can be processed simultaneously.

For practical workflows, it is best to group related documents within a Project and then specify in the prompt which ones should be considered for each query.

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How Claude reads documents and data.

Claude distinguishes between text extraction and multimodal reasoning:

• Text extraction applies to standard formats such as TXT, DOCX, RTF, and CSV. The model reads and indexes text line by line, identifying structure and keywords for summarization or analysis.

• Multimodal reasoning activates when reading PDFs or image files. In this mode, Claude interprets both text and visuals—detecting embedded images, graphs, and layout information. This allows it to analyze complex materials such as presentations, scanned contracts, or reports containing charts.

Because multimodal reading consumes more tokens than plain text, large PDFs should be split into smaller sections to ensure complete and accurate processing. A 100-page PDF with many images can reach the context ceiling faster than a plain text file of similar size.

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File handling through the Anthropic API.

Developers can interact with Claude programmatically through the Anthropic API, which introduces additional tiers of file management. There are three main endpoints relevant to file ingestion:

1. Messages API — the standard request endpoint with a 32 MB total request limit.

2. Batch API — allows asynchronous or offline processing of larger requests up to 256 MB.

3. Files API — a dedicated system for uploading reusable files up to 500 MB each, which can then be referenced by a file_id in subsequent API calls.

This structure enables the reuse of large datasets or document collections without re-uploading them for every interaction. Developers can upload reference materials once, store them for extended periods, and query specific files within the size and context limits.

If the payload of a Messages API request exceeds the 32 MB limit, the request is automatically rejected with a “request too large” response, making the Files API the proper channel for scalable workflows.

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File handling in Amazon Bedrock integrations.

When Claude is accessed through Amazon Bedrock, file limits are smaller due to stricter platform-level constraints. Bedrock allows up to five document attachments, each limited to 4.5 MB, and up to twenty image files, each limited to 3.75 MB. All attachments must be placed in user messages—Bedrock does not allow file references in system or assistant roles.

This configuration suits lightweight document interactions within enterprise environments, but it requires preprocessing for larger files. To handle lengthy or data-heavy materials on Bedrock, organizations typically split files into multiple smaller segments before analysis.

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Table — File upload limits by environment.

Environment	Per-file size	File count	Notes
Claude app (chat)	30 MB	20 files per chat	Docs and images supported; context limits apply
Claude Projects (knowledge)	30 MB	Unlimited	File count unbounded; governed by context window
Anthropic API – Messages	32 MB per request	—	Total payload size limit per call
Anthropic API – Batch	256 MB per request	—	Asynchronous processing
Anthropic API – Files API	500 MB per file	—	Upload once, reuse via file_id
Amazon Bedrock (Claude)	Docs 4.5 MB; Images 3.75 MB	5 docs / 20 images	Payload ≤ 20 MB; files in user messages only

This table illustrates the difference between consumer-facing uploads and developer-level data ingestion.

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Supported file formats and applications.

Claude supports a broad range of file types suitable for analytical, creative, or technical tasks.

• Documents: PDF, DOCX, TXT, RTF, HTML, and EPUB for general reading and summarization.

• Data files: CSV and TSV for structured analysis, ideal for numeric and tabular workflows.

• Images: JPEG, PNG, GIF, and WebP for multimodal interpretation of visual content.

The combination of these formats allows Claude to perform both textual reasoning and cross-modal analysis. For structured data, CSV remains the preferred format because it minimizes noise and maintains clear column boundaries.

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Common issues and solutions.

• Truncated or incomplete answers: Often caused by reaching the model’s context limit, not a file-size cap. Divide documents into smaller sections or query them sequentially.

• API upload failures: If requests exceed 32 MB, switch to the Files API and reference files by ID.

• Bedrock rejections: Resize documents and images to comply with Bedrock’s 4.5 MB and 3.75 MB per-file caps.

• Loss of image interpretation: Ensure the uploaded file format is supported (JPEG/PNG) and under the resolution limit.

These adjustments prevent loss of information and maintain the integrity of Claude’s responses when handling extensive materials.

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Recommended operational workflow.

1. Split large files logically. Divide long PDFs or text documents by chapter or subject area.

2. Use Projects for grouped content. Store many related documents and reference them selectively in prompts.

3. Adopt the Files API for scaling. Upload once (up to 500 MB) and reuse across prompts by referencing the same file ID.

4. Keep Bedrock policies in mind. When operating under Bedrock, prepare smaller files and batch them in sequence.

5. Prefer CSV for data analysis. It ensures the model reads structured data without formatting inconsistencies.

Following these steps helps balance accessibility, performance, and accuracy when using Claude for professional document processing.

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Operational summary.

Claude AI’s file upload architecture combines accessibility for individuals with robust capacity for enterprise developers. The Claude app provides simplicity—30 MB per file, 20 files per chat—while Projects enable persistent repositories. Developers using the Anthropic API can handle significantly larger documents through the Files API (up to 500 MB per file), whereas Amazon Bedrock users must operate within smaller constraints due to stricter payload policies.

Across all environments, Claude reads documents through text extraction and multimodal understanding, handling both structured and visual information effectively when files are correctly formatted and within limits.

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