TL;DR
For one long document where coherence matters — an 80-page report, a contract, a research paper — Claude (Opus 4.7 / Sonnet 4.6) is the safer default. It holds a true 1M-token window at standard pricing and paraphrases less when you ask it to quote. For structured extraction from financial filings or spreadsheets, ChatGPT wins because it runs Python on the file. The catch most people miss: ChatGPT’s in-app context on Plus is far smaller than the headline numbers suggest, and a 100-page PDF can silently overflow it.
The rest of this guide gives you the exact limits (as of June 2026) and a task-by-task verdict so you stop choosing by whichever tab is already open.
The numbers that actually decide this
The single most common mistake is comparing “context windows” from marketing pages. The window that matters is the one the chat app gives you, not the API maximum.
| Spec (June 2026) | Claude Pro ($20) | ChatGPT Plus ($20) | ChatGPT Pro ($200) |
|---|---|---|---|
| In-app context | 1M tokens | GPT-5.5 Instant ~32K; Thinking 256K (128K in / 128K out) | Full 1M-token window |
| Max file size | 500 MB per file | 512 MB per file | 512 MB per file |
| Files per chat | 20 | 10 per message, ~80 uploads / 3 hrs | Unlimited uploads |
| PDF handling | Text + visuals under 100 pages; text-only over 1000 | Text extracted; large files truncated at ~2M tokens | Same as Plus, larger working window |
| Runs code on files | Limited (code execution beta) | Yes (Advanced Data Analysis / Python) | Yes |
Two things fall out of this table:
- Claude Pro gives you the full 1M-token window for $20. ChatGPT only matches that on the $200 Pro plan; Plus is meaningfully smaller, and GPT-5.5 Instant on Plus is just ~32K tokens — roughly 50 pages before it starts forgetting the front of the document.
- File size is rarely the wall. Both accept ~500 MB files. The wall is the working context window and the PDF page handling. A clean 90-page PDF is comfortable for Claude; the same file on ChatGPT Plus Instant will overflow long before you hit any “file too large” error.
Official limits: Claude file uploads, ChatGPT pricing & plans.
Where each tool actually wins
This is the part you came for. Verdicts are based on the failure modes each tool shows on real documents, not benchmark scores.
| Task | Reach for | Why |
|---|---|---|
| Summarize one 80-page report | Claude | Holds coherence across the whole doc; fewer dropped middle sections |
| Find every mention of a clause across 5 contracts | ChatGPT (file search) or both side-by-side | Sharper retrieval on “find X” queries |
| Translate a 100-page document | Claude | Preserves nuance and register; ChatGPT is faster but flattens tone |
| Extract structured tables from a 10-K filing | ChatGPT (Advanced Data Analysis) | Actually runs Python on the file; numbers stay exact |
| Draft new prose grounded in a 50-page brief | Claude | Stronger fidelity to source; less invented detail |
| Quote-and-cite work where exact wording matters | Claude | Paraphrases far less, even mid-document |
| 900-page PDF in one shot | Gemini 3.1 Pro | 1M window ingests ~900-page PDFs in a single prompt |
The two-line summary: drafting, translation, and faithful quoting go to Claude; structured number extraction goes to ChatGPT. If a task needs both — say, extract a table and summarize the narrative around it — run the extraction in ChatGPT and the summary in Claude.
Sizing a document before you upload
Rough token math, so you know which window you’re fighting:
- English prose: ~400 tokens per page. A 50-page contract is ~20K tokens; a 200-page textbook is ~80–100K.
- Dense formatting, tables, or code: 1.5–2x more. A 50-page financial filing can be 40–60K tokens.
- Scanned (image) PDFs: higher token cost and higher error rates on both tools. OCR-clean it first if you can.
Map that against the table above. Under ~30K tokens, both tools fit comfortably and you should choose on workflow fit (Projects, file naming, ecosystem). Above ~120K tokens, ChatGPT Plus is out — use Claude Pro, ChatGPT Pro, or split the document. Above ~250K tokens, even Claude’s recall degrades before the hard limit, so chunk by section.
The Claude long-document workflow that works
For a 150-page report in Claude, this sequence is repeatable:
- Upload the PDF. Confirm it landed: ask Claude to quote the first sentence of section 3 before trusting anything.
- Ask for a table of contents with section page ranges. This becomes your navigation map.
- Drill section by section, with an explicit instruction: “Quote the exact phrasing; do not paraphrase. Cite the page number for every claim.”
- Ask for a unified executive summary only after the section passes — summarizing first invites it to skip the middle.
If you need this across many files, Claude Projects keeps filenames addressable, so naming inputs contract-2024.pdf and addendum-A.pdf lets you say “quote from addendum-A” and verify the source fast. See the Claude long-document workflow and Claude Projects advanced workflow for the full setup.
The ChatGPT extraction workflow
When the document is data-heavy — a 10-K, a budget spreadsheet, a table-laden report — ChatGPT’s Advanced Data Analysis is the right tool because it writes and runs Python on the actual file:
- Upload the file and ask it to “parse the financial tables on pages 12–18 into a single CSV; show the code you ran.”
- Make it show the code. If it parsed the wrong columns, you’ll see it immediately instead of trusting a hallucinated table.
- Spot-check three numbers against the source PDF. Extraction errors cluster at merged cells and footnoted figures.
On Plus you get ~80 uploads per 3-hour window and 10 files per message, which is fine for iterative work; only the $200 Pro plan removes the cap and unlocks the full 1M-token window.
Verifying the output (non-negotiable on both tools)
Both tools’ default failure on long documents is paraphrasing instead of quoting, and the paraphrase often softens the one clause that matters.
- Verify quoted clauses verbatim against the source. Treat any quote you didn’t check as a paraphrase.
- Require a page number for every numerical extract — dates, dollar amounts, table cells. No page cite means treat the figure as unverified.
- Re-run the same prompt and compare. If the two runs disagree on a number, the source is ambiguous or the tool guessed.
Common mistakes
- Choosing by headline context window. ChatGPT advertises huge numbers; the in-app Plus window is ~32K on Instant. Match the tool’s real working window to your token count.
- Assuming one tool always wins. It’s task-dependent: drafting → Claude, table extraction → ChatGPT.
- Trusting a 200-page summary unverified. Both miss sections at scale, and the miss is often the most important paragraph.
- Comparing tools on different prompts. To compare fairly, the prompt must be identical down to the punctuation.
- Not confirming the upload. Always make the tool quote a known sentence before you trust its analysis.
- Doing serious long-doc work on a free tier. Both throttle context hard below a paid plan.
FAQ
- Does Claude really have more usable context than ChatGPT for long documents?: For the $20 tier, yes. Claude Pro gives the full 1M-token window; ChatGPT Plus gives ~32K on GPT-5.5 Instant and 256K when you switch to Thinking. ChatGPT only matches Claude’s 1M window on the $200 Pro plan (as of June 2026).
- What’s the largest PDF I can upload?: Both accept files up to ~500 MB (Claude 500 MB, ChatGPT 512 MB). Page handling matters more: Claude reads text and visuals in PDFs under 100 pages and text-only above 1000; ChatGPT extracts text but truncates very large files near a ~2M-token limit.
- Can I use both?: Yes, and many heavy users do. Pay for the one you use daily and reach for the other when you hit its wall — Claude for faithful drafting, ChatGPT for table extraction.
- What about Gemini for long documents?: Gemini 3.1 Pro on Google AI Pro ($19.99) holds a 1M-token window and can ingest a ~900-page PDF in one prompt; NotebookLM now runs on it and is strong at synthesizing across many sources. Worth testing if you routinely top out Claude and ChatGPT.
- How should I handle confidential documents?: Use enterprise plans with no-training data terms, or redact before upload. Consumer Free/Pro plans are not appropriate for client-confidential material.