ChatGPT alternatives
By Daniel Reeve · tested and updated September 2026
Document AI is more specific than general chat. The tool must read the file correctly, preserve structure, handle OCR, cite sections, extract tables and produce usable output without inventing details.
Quick answer
Do not assume a big context window means the model read your whole document carefully. Capacity and attention are different things, and the gap between them is where document work goes wrong.
Decision map
Users who repeatedly summarize reports, contracts, research PDFs, decks or spreadsheet exports.
One-off tiny files where copy/paste into a free tool is enough.
Read this document, list the five decisions, quote the supporting page or section, extract deadlines and say what you could not read.
Failure by failure
| Area | Useful for | Watch out for |
|---|---|---|
| Normal PDFs | Useful for summaries, issue lists, timelines and document Q&A. | Ask for page or section references. |
| Scanned PDFs | Need OCR before the AI can reason over text. | OCR mistakes can corrupt names, numbers and clauses. |
| Word documents | Useful for rewriting, restructuring and extracting action items. | Tracked changes and comments can contain sensitive material. |
| Spreadsheets | AI can explain tables and spot patterns. | Verify formulas, totals and hidden sheets manually. |
| Slide decks | AI can outline or critique decks. | A good deck needs narrative, visual hierarchy and business judgment. |
What actually limits a long PDF
People assume file size is the constraint. It almost never is. Figures from OpenAI and Anthropic, checked 2026-09-10.
ChatGPT documents a 512 MB per-file limit but caps text at 2M tokens per file. A dense 400-page report can sit comfortably under the size limit and still exceed what the model will read.
Claude Opus 5 and Sonnet 5 document 1M tokens of context, GPT-6 Astra 1.05M. That is capacity for the conversation as a whole, not a per-document allowance — your prompt, the document and the answer all share it.
A model that can hold a document is not a model that weighs every page of it equally. This is the failure people mistake for hallucination: the answer is drawn from the parts it attended to.
Both ChatGPT and Gemini document a limit of around 10 files per conversation or prompt. Multi-document comparison work runs into this well before it runs into size.
Working with long documents
Give the model one section and one specific question rather than the whole file and a request to summarise. The answers are better, the errors are visible, and you can check them against a page you can find.
Ask for the page or section number with every claim, then open two of them. It takes under a minute and it is the difference between a summary you can use and one you can only hope about.
Sources
Every figure on this page was read from the official documentation below on 2026-09-10. Prices, limits and model names change without notice — the source is authoritative, this page is not.
FAQ
It can ingest one, within limits. ChatGPT documents a 2M token cap per text file and a 512 MB size limit; Claude Opus 5 and Sonnet 5 document 1M tokens of context (checked 2026-09-10). Whether it reads all 500 pages *carefully* is a different question, and the answer is usually no.
Because context capacity and attention are not the same thing. The model can hold the document; it does not weigh every page equally. Long documents are best handled in sections with explicit questions, not as one dump and one summary.
Require citations to page or section for every claim, then open two of them at random. If both hold up, the summary is probably sound; if either does not, treat the whole thing as a draft.
512 MB per file in ChatGPT, 100 MB for most file types in Gemini (Google, checked 2026-09-10). The token cap will normally stop you first.
Up to the roughly 10-file ceiling both vendors document, yes — but comparison quality drops as you add documents. Two at a time, with a specific question about what differs, beats six at once and a request to summarise.