Google Gemini File Uploading: Supported File Types, Maximum Size Limits, Upload Rules, And Document Reading Features

Google Gemini supports uploading files across its app experiences, developer API endpoints, and cloud‑based document understanding surfaces, with each surface defining its own supported formats, size limits, retention rules, and reading behaviors. These capabilities make it possible to upload documents, media, and structured content for question answering, extraction, and multimodal analysis.

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Supported File Types In Gemini Apps And APIs Include Common Documents, Media, And Text Formats.

The Gemini Apps filing system accepts a wide range of content, with app documentation referring to “most file types” including audio and video alongside text‑centric formats. In practice, users can upload mixed media such as images, documents, audio clips, and video files when interacting with the assistant in consumer experiences.

For developers using the Gemini API, the Files API lets applications upload various media file types for inference and integration workflows. Document understanding workflows, particularly for text extraction and reasoning, explicitly list PDF and text formats as input types, with additional structured formats available based on the model and surface.

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Google Gemini Supported File Types By Surface

Surface	Supported File Types
Gemini Apps	Mixed media including images, audio, video, common documents
Gemini API Files API	Media files for inference and reference
API Document Processing	PDF, text/plain, plus documents supported by model workflows
Vertex AI Document Understanding	PDF, text/plain, and selected document formats

Text and document formats are supported across API and app surfaces.

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Maximum File Size Limits And Storage Constraints Vary By Upload Context.

The Gemini Apps interface supports practical per‑file limits such as a 2 GB cap for videos and smaller caps (e.g., 100 MB) for other file types when attached in a prompt. Users can attach up to 10 files per prompt in the app environment, enabling multimedia and long content uploads in a single interaction.

In the Gemini API’s Files API, files can be much larger at the storage layer, with uploads supported up to 2 GB per file and a total workspace storage cap of 20 GB per project. However, these stored files are held only temporarily—typically 48 hours—during which they can be referenced in chat or inference requests.

Separate from generic file storage, document processing workflows such as PDF reading are governed by tighter caps. PDFs are supported up to 50 MB and up to 1,000 pages per document for analysis workflows, regardless of whether the file is uploaded inline or via the Files API.

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Google Gemini File Size Limits And Storage Rules

Surface	Max Per‑File Size	Attachment Rules	Retention
Gemini Apps	Video up to 2 GB; other files ~100 MB	Up to 10 files per prompt	Platform‑managed
Files API	Up to 2 GB per file; 20 GB/project	Stored for reference	48 hours
PDF Document Processing	Up to 50 MB or 1,000 pages	Document reading cap	Request‑bound
Vertex AI Uploads	50 MB via API/Cloud Storage; smaller via console	Model‑dependent limits	Cloud retention

Size caps differ between casual app use and developer document workflows.

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Upload Rules Govern Prompt Attachments, Storage Lifetimes, And Inference Behavior.

In the Gemini Apps and broader Google AI Studio experience, users attach files to prompts through the UI, with a per‑prompt cap on the number of attachments. Uploaded files linked to a prompt contribute to context and are consumed as part of generation or reasoning tasks. Media length limitations for audio and video may also apply, especially when performance and latency are factors.

Developers using the Files API must handle file metadata, upload, and reference logic within the project quota limits. Files cannot be downloaded back from the API and are used solely as a reference for model inference during the retention window. Once the retention period expires, developers need to re‑upload files for continued use.

Vertex AI’s document understanding function adds its own upload rules, including file size and upload method distinctions; for example, console uploads may have stricter size caps compared to API or Cloud Storage ingestion.

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Google Gemini Upload Rules And Practical Constraints

Rule	Impact On Usage
Per‑prompt attachment count	Limits simultaneous reference files
Storage retention window	Files expire after set period
File download not supported	Uploaded files are reference‑only
Media length caps	Performance and latency boundaries
API vs console upload caps	Operational differences by surface

Developers must design workflows around these upload rules.

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Document Reading Features Include PDF Analysis, Token Budgeting, And Context‑Aware Extraction.

Gemini’s document processing pipeline for PDFs and similar content integrates text extraction, layout interpretation, and token budgeting. PDFs are treated as multimodal inputs where the model extracts text and interprets visual structure to support summarization and question answering.

For PDF workflows, each page is budgeted as a token equivalent (e.g., roughly 258 tokens per page for accounting purposes), which affects how much content from a large document can be actively used in a single inference call. Long documents can consume context quickly, necessitating selective extraction, multi‑turn queries, or targeted page ranges to stay within model limits.

Vertex AI’s document understanding surfaces extend these features with support for text/plain inputs and model‑specific constraints on pages per request and total input size, making it suitable for enterprise document ingestion and structured data extraction.

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Google Gemini Document Reading Capabilities

Feature	Description
PDF text extraction	Reads embedded text and interprets structure
Layout interpretation	Analyzes tables, headings, diagrams
Token budgeting	Pages mapped to token cost
Targeted extraction	Selects relevant sections from long files
Multimodal support	Supports images, text, and charts within docs

Document reading balances thoroughness with context limits.

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Google Gemini File Uploading Enables Rich Multimodal And Document Workflows With Clear Limits And Inference Integration.

Google Gemini’s file uploading ecosystem supports a wide variety of file types, from media to documents, across consumer app and developer API surfaces. Size and retention limits vary by surface, with document processing workflows subject to tighter caps designed for reasoning and context management. Understanding these supported formats, storage rules, and document reading features allows users and developers to build effective multimodal interactions and extract insights from complex files.

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