PDFs and ChatGPT vs. Claude vs. Gemini: analysis, capabilities, limits, and uses

As businesses rely increasingly on AI to extract and analyze information from complex documents, the ability to interpret large PDFs accurately and responsively has become a core differentiator among the leading language models.

PDF processing is no longer a peripheral feature in 2025... it has become central to how AI is used in legal research, academic summarization, enterprise documentation, and technical audits.

ChatGPT (OpenAI), Claude (Anthropic), and Gemini (Google) have each invested in PDF capabilities, but their approaches diverge significantly in how they manage context length, interface behavior, integration with productivity tools, and multimodal comprehension.

Here we examine the real-world performance of each assistant’s latest version — ChatGPT with GPT-4o and o-series, Claude Opus 4 and Sonnet 4, and Gemini 2.5 Flash and Pro — without referencing outdated or deprecated models. The comparison focuses strictly on the current-generation behavior across web apps, pro-tier platforms, and enterprise configurations.

ChatGPT uses o-series models to unlock high-volume file analysis with multimodal precision

OpenAI’s PDF pipeline supports large files and multimodal pages, but performance depends on model selection and document structure.

In the August 2025 deployment of ChatGPT’s toolset, file upload functionality is now directly tied to the GPT-4o, o3, o3-pro, and o4-mini models. Users accessing ChatGPT through Plus, Team, or Enterprise plans can upload PDFs up to 512 MB, translating into approximately 2 million tokens of extractable data. However, GPT-4o can only load 110,000 tokens per file into active memory, with the remainder being indexed for semantic lookup rather than full in-context visibility.

The interface allows users to:

• Ask direct questions about the content of a document,

• Extract full tables or figure captions,

• Perform keyword searches and topic clustering,

• Rewrite or rephrase entire sections.

If the document contains visual elements — such as scanned pages, graphs, or charts — GPT-4o leverages its multimodal capacity to interpret them. Users can query images directly (“What does this chart show?”) or request a description of entire pages. However, PDFs with multicolumn layouts, dense footnotes, or decorative formatting can introduce parsing errors, particularly in lateral reading of tables.

The system includes a visible memory pane for each document, but once a file exceeds the context threshold, only the most recent or referenced portions remain live. Users must phrase follow-ups with specific anchors (“In Section 2.3 of the uploaded PDF…”) to avoid confusion.

The feature remains disabled for legacy GPT-4.1 or 3.5-turbo models, and free-tier users can only upload 3 PDFs per day, each under 20 MB. Enterprises gain higher caps and background processing queues.

Claude Opus 4 dominates long-form PDF reasoning with unmatched context depth and memory fidelity

Anthropic’s Claude treats entire books, legal bundles, and technical drafts as single inputs, sustaining detailed reasoning across hundreds of pages without fragmentation.

Where ChatGPT emphasizes multimodal breadth, Claude Opus 4 specializes in depth of understanding across large text corpora. Its defining advantage is the 200,000-token context window, which allows the assistant to ingest long documents — including statutes, scientific theses, contracts, and litigation exhibits — in a single uninterrupted session. The entire PDF remains in working memory, enabling the assistant to cite or cross-reference any part of the document without reloading or re-prompting.

As of August 2025, Claude accepts:

• PDFs up to 30 MB through the web app interface,

• Up to 500 MB via Anthropic’s API,

• Up to 10 concurrent documents in Pro and Max tiers.

This makes it uniquely suited for professionals handling complex or nested content. Law firms, for example, upload entire case bundles to analyze internal contradictions or locate precedent.

Scientists load preprints with appendices and figures, asking Claude to generate critiques or identify overlooked hypotheses. Technical reviewers feed in 800-page engineering reports and receive coherent diagnostics within a single prompt flow.

Parsing quality is extremely high on well-formatted documents. Tables with merged cells or irregular grid structures may require rephrased requests, but Claude typically preserves the original layout and section hierarchy without manual intervention.

Opus 4 is available only to paid users (Claude Pro or Claude Max), with weekly usage limits of 40–80 hours depending on plan tier. The Sonnet 4 model, included in the free tier, supports similar file ingestion but with a reduced reasoning span and response length.

Gemini 2.5 integrates PDF functionality directly into Google Workspace, prioritizing workflow over document scale

Google’s AI offers structured extraction, smart summaries, and export-ready outputs, but is constrained by narrower context limits and occasional feature gating.

Gemini’s PDF handling is embedded within its broader Deep Research and Workspace integration suite, allowing users to pull files from local storage or Google Drive, analyze them within the Gemini interface, and directly export results to Google Docs, Slides, or Canvas.

The system currently supports:

• Up to 10 PDFs per prompt,

• Individual file size capped at 100 MB,

• Context window of 32,000 tokens in free tier and up to 1 million tokens in Gemini Pro and Ultra tiers (applies to Google One and Workspace plans).

The focus is on collaborative output generation. A single research PDF can be used to:

• Generate an outline for a presentation in Google Slides,

• Extract definitions and examples into a glossary,

• Transform long articles into question sets for Google Classroom,

• Summarize technical proposals into product pitch templates using Canvas.

While Gemini performs well on most document types, its PDF parser occasionally struggles with scanned content, mixed languages, or embedded forms. In those cases, the system defaults to a fallback summary based on text layers or OCR results. Split-screen editing is supported but limited to Drive-hosted documents.

In May, Gemini temporarily restricted file upload access for education-linked accounts, but Google’s July 2025 release notes confirmed full restoration of the functionality.

Gemini’s strength lies in its native app linkage, not in raw document size or in-depth legal reasoning. It excels when the PDF is a stepping stone to content creation or shared project development — not when it’s a subject of legal or scholarly scrutiny.

Summary: three assistants, three philosophies in how they handle PDF data today

Each of the major models now offers reliable PDF ingestion, but their strengths align with distinct professional needs:

• ChatGPT enables multimodal interpretation with strong extraction, layout-aware summaries, and massive file size limits, but remains bound by a lower working context (110k tokens) unless upgraded to Enterprise.

• Claude delivers the widest uninterrupted reasoning window by far, capable of handling extremely large, dense, or technical PDFs as unified logical objects, making it ideal for law, academia, and code-heavy documents.

• Gemini emphasizes tight integration with the Google ecosystem, transforming PDFs into usable outputs inside Workspace, especially effective for educators, marketers, and cross-functional teams — though its raw parsing and context limits are narrower.

Choosing between them depends less on surface features and more on operational context. If you need to collaborate, annotate, and publish — Gemini is the most seamless. If you need to retain full continuity across 400 pages of legal theory — Claude is the most dependable. If you’re managing 300MB of scanned PDFs with embedded charts and forms — ChatGPT with GPT-4o remains the most flexible, provided the layout is manageable and model selection is precise.

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