Which AI has the largest context window?

Gemini's flagship models accept the largest inputs, and handle the widest range of formats including video and audio.

Which AI is most accurate on long documents?

Claude is generally the most consistent at using detail from across a long document, which matters more than raw window size for contracts and filings.

Should I split a long document before uploading it?

Often yes, unless you are using a model with a very large window. Splitting improves reliability but risks losing cross-references, so keep related sections together.

The best AI for long documents

Contracts, filings, research papers and everything else that does not fit in a chat box.

Two things decide long-document work, and they are not the same thing: how much you can put in, and how reliably the middle of it is used in the answer. Context size is the advertised number; consistency is the one that costs you.

Last updated 22 September 2026

Candidates

Which model suits which work

No ranking. Each of these leads on a different kind of task.

GeminiGoogle
The largest inputs and the widest range of formats, including scans, slides and video.
Its clearest advantage: very large mixed inputs, including PDFs, slides and images, handled together without splitting them up.
ClaudeAnthropic
The most consistent reasoning across a very long single document.
Reads very long documents in one pass with unusual consistency, and holds details from the beginning of a file when answering about the end of it.
ChatGPTOpenAI
Documents that need computation as well as reading — spreadsheets, financial models.
Handles uploaded files and spreadsheets well, and can compute over them rather than only reading them. Very long inputs are better split into staged passes.
GrokxAI
Critical reading: arguing with a document rather than summarising it.
Handles large inputs, and is good at critical reading — arguing with a document rather than only summarising it.

What matters

What actually decides it

The factors that change the outcome more than the model name does.

A big window is not a promise

Accepting a million tokens is not the same as using them well. Accuracy on detail buried in the middle of a long input varies far more between models than the headline number suggests.

Ask questions the summary cannot fake

Test any model on a long document by asking about something specific and obscure in the middle of it. Summaries look convincing regardless.

Format handling saves more time than capability

Much long-document work is lost to preparation. A model that reads your scanned annex directly often beats a stronger one that needs it converted first.

Same prompt

One prompt, two answers

An illustrative example. Run it yourself to see the live result.

The prompt

“Across these three merged agreements, list every obligation that survives termination and say where each is defined.”

Claudeexample

Produces a precise list with clause references, including two obligations whose survival depends on a definition in a different agreement.

Geminiexample

Covers all three agreements plus a scanned amendment without preprocessing, and catches an obligation that exists only in that scan.

How their thinking differed

One was more precise about cross-references; the other saw more of the material. Both found obligations the other missed.

Illustrative example, not benchmark data.

Rileva

Why choose one?

Auto chooses for youRileva routes your task to the model that fits it.

Council compares themSeveral models answer, then Rileva shows where they agree and differ.

FAQ

Common questions

Which AI has the largest context window?: Gemini's flagship models accept the largest inputs, and handle the widest range of formats including video and audio.
Which AI is most accurate on long documents?: Claude is generally the most consistent at using detail from across a long document, which matters more than raw window size for contracts and filings.
Should I split a long document before uploading it?: Often yes, unless you are using a model with a very large window. Splitting improves reliability but risks losing cross-references, so keep related sections together.

Keep reading