Meta AI File Upload and Reading in late 2025.

Meta AI has expanded its multimodal capabilities across web, mobile, and messaging platforms, enabling users to upload images, documents, and text for interpretation, extraction, and structured analysis. In late 2025 the system supports image uploads universally and document uploads through a progressive regional rollout. File reading depends on the interface—Meta.ai on the web, the Meta AI mobile app, WhatsApp, Messenger, Instagram, and developer access through the Llama API. The reading pipeline combines layout recognition, OCR, text parsing, and multimodal reasoning, allowing Meta AI to handle screenshots, PDFs, presentations, visual documents, and mixed-format materials.

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Meta AI supports native file uploads in web and mobile interfaces, enabling interpretation of images, PDFs, and text-based documents.

Meta AI’s web interface includes an “Add media or files” option that accepts images and selected document formats. Once uploaded, the assistant extracts structure, identifies layout sections, reads charts and tables, and enables queries that reference specific pages or elements. Document uploads remain in phased release, meaning availability varies by region and by user account. Image uploads, however, are fully rolled out and work consistently across Meta.ai, the Meta AI app, WhatsApp, Messenger, and Instagram.

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........Platform Support for File Uploads — Meta AI

Platform	File Types Supported	Capabilities	Rollout Status
Meta.ai Web	Images, PDFs, DOCX	Full multimodal reading	Expanding globally
Meta AI App	Images, selected documents	Mobile file analysis	Partial rollout
WhatsApp	Images	Vision interpretation	Fully available
Messenger	Images	Vision interpretation	Fully available
Instagram DMs	Images	Vision interpretation	Fully available
Llama API	Text + images	Developer ingestion workflows	Available via API

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The file interpretation pipeline identifies visual structure, extracts text, and processes layout elements for document reasoning.

When a file is uploaded, Meta AI converts the document into structured segments. Images undergo vision-based parsing to identify objects, text blocks, diagrams, and relationships between elements. PDFs and text documents are processed through OCR, layout detection, and text extraction. The system reconstructs the content so users can request summaries, highlight key data, or ask targeted questions such as locating specific references inside long reports.

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........File Interpretation Processes — Meta AI

File Type	Processing Method	Extracted Elements	Typical Output
Images	Vision model	Text, diagrams, objects	Descriptions and insights
PDFs	OCR + layout parsing	Sections, tables, charts	Summaries and analysis
DOCX	Text extraction	Headings, paragraphs	Structured outputs
Screenshots	UI element detection	Buttons, menus, labels	Explanations and workflows

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Messaging integrations focus on image uploads, allowing Meta AI to answer visual questions across WhatsApp, Messenger, and Instagram.

Meta AI’s messaging integrations emphasize image-based interaction. Users can upload photos, ask for explanations, extract visible text, evaluate charts, interpret screenshots, or request edits such as cropping or enhancing. These platforms do not yet support direct document upload for reading, but Meta AI’s vision features are consistent across all messaging surfaces.

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........Messaging Behavior — Meta AI Vision Features

Platform	Input Type	Interpretation Strength	Uses
WhatsApp	Images	Very strong	Photo analysis, OCR
Messenger	Images	Very strong	UI explanation, diagrams
Instagram	Images	Very strong	Editing, descriptive tasks

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Developers access file-based workflows through the Llama API, which supports text and image inputs for custom ingestion pipelines.

The Llama API does not yet include a native “upload PDF file” endpoint. Developers instead process documents by extracting text locally or rendering pages as images. These inputs can then be sent to the model for reasoning. This approach enables flexible document workflows, including multi-page analysis, text extraction, table explanation, and chart interpretation, although preprocessing remains the responsibility of the developer’s system.

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........Developer File Handling — Llama API

Input Route	Accepted Formats	Workflow Requirements	Ideal Use Case
Text Input	Extracted document text	Local preprocessing	Document Q&A
Image Input	PNG, JPG, WebP	Page-to-image conversion if needed	Chart and layout reading
Hybrid Processing	Combined text + images	Client orchestration	Reports with visuals

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File support varies by region, and privacy settings determine how uploaded media is processed inside Meta AI.

Document uploads are not yet universally available, and some users may not see the upload button due to phased rollout. Meta continues to expand document support across geographic regions and account types. Privacy controls allow users to delete conversation history and uploaded files. Messaging integrations handle images according to app-level privacy settings, while the Meta AI app may request additional permissions such as camera-roll access. These settings determine whether media is processed entirely on device or uploaded to Meta’s cloud for analysis.

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........Availability and Privacy — Meta AI File Handling

Factor	Behavior	Effect on File Reading	Notes
Regional Rollout	Gradual	May limit document uploads	Varies by country
Account Eligibility	Feature-flagged	Upload button may not appear	Staged activation
Privacy Settings	User-controlled	Limits cloud processing	Important for images
Data Retention	Session-bound	Media removable	Controlled by user

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Meta AI’s file-upload capabilities continue to mature, enabling image interpretation, document analysis, and developer workflows across an expanding ecosystem.

The system’s multimodal abilities extend across web and mobile apps, messaging platforms, and API-based development. Image uploads are fully established, while document uploads continue to expand during late 2025. Meta AI’s layered interpretation pipeline enables structured extraction, visual understanding, and text reasoning across formats, creating a versatile foundation for creative, analytical, and technical work.

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