In this guide · 8 sections
- 01Claude vs Gemini for long documents: the short version
- 02Context windows and what fits
- 03What the long-context benchmarks show
- 04File upload limits and plans
- 05Privacy terms for confidential documents
- 06How to review a contract with AI and check the answers
- 07Do it yourself or get help?
- 08Frequently asked questions
Short answer
Both handle long documents well. On Artificial Analysis' long-context reasoning test (AA-LCR), Claude Opus 5.5 scored about 85% and Gemini 4 Argon about 80% (October 2026). Claude takes 20 files per chat and PDFs up to 1,000 pages; Gemini takes 10 files. Always verify clauses yourself.
Claude vs Gemini for long documents: the short version
Claude (Anthropic)
Higher long-context scoreTeam US$20/user/mo (annual)
- Claude Opus 5.5: about 1M-token context, 128K max output
- AA-LCR: 84.7% (Opus 5.5, Max)
- Up to 20 files per chat, PDFs up to 1,000 pages
- Projects keep reference files across chats
Best for: Contracts, tenders and reports uploaded as PDFs or Word files.
Gemini (Google)
Lives in your DriveIncluded in Workspace from S$18.80/user/mo for Docs
- Gemini 4 Argon: 1M-token context window
- AA-LCR: 79.7% (Gemini 4 Argon, High)
- Up to 10 files per prompt, 100 MB each for documents
- Works on files already in Google Drive and Docs
Best for: Teams whose documents already live in Google Workspace.
Prices are approximate, as of October 2026. If you also use ChatGPT, see our wider comparison of ChatGPT vs Claude vs Gemini for business.
Context windows and what fits
A context window is the amount of text, in tokens, a model can work with in one go. Our explainer on the context window covers tokens in detail; as a rule of thumb, 1 million tokens is roughly 750,000 English words.
| Model | Context window | Max output | API price per 1M tokens (in / out) |
|---|---|---|---|
| Claude Opus 5.5 | About 1M tokens | 128K tokens | US$4 / US$20 |
| Claude Sonnet 5.5 | About 1M tokens | 128K tokens | Lower than Opus; see Anthropic pricing |
| Gemini 4 Argon | 1M tokens | Long decodes up to 1M tokens | US$2 / US$10 to 30 Nov 2026, then US$4 / US$20 |
Sources: Claude pricing, Anthropic models overview, Gemini models and Gemini API pricing. Claude's pricing page lists the context window as 'up to 1M, varies by model' on every plan, including Team. A typical 50-page contract is well under 50,000 tokens, so either tool can hold several at once.
What the long-context benchmarks show
A big window does not guarantee good reading. Artificial Analysis' Long Context Reasoning benchmark (AA-LCR) tests 100 questions over document sets of 10,000 to 100,000 tokens, drawn from company reports, legal documents, government consultations and academic papers. Each question needs facts from different parts of the documents to be found and combined.
| Model (setting) | AA-LCR v1.1 score | Artificial Analysis Intelligence Index |
|---|---|---|
| Claude Opus 5.5 (Max) | 84.7% | 58 |
| Gemini 4 Argon (High) | 79.7% | 53 |
| Top score on AA-LCR: Kimi K3 (Max) | 88.7% | Not compared here |
The gap of about five points is meaningful but not dramatic. Both still get roughly one question in seven to one in five wrong on this test, which is why checking matters. The highest settings are also the slowest and most expensive; chat apps may not run at maximum effort by default.
File upload limits and plans
For contracts, the practical limits are how many files and pages you can attach in one go.
- Claude: Anthropic's upload help article allows up to 20 files per chat, 500 MB per file, and PDFs up to 1,000 pages. Claude reads charts and images in PDFs of 100 pages or fewer; for longer PDFs it processes the text only. Project files are limited to 30 MB each.
- Gemini Apps: Google's upload help article allows up to 10 files per prompt, with documents up to 100 MB each, and files can be added straight from Google Drive if your admin allows it.
- Gemini in Workspace: Gemini works inside Docs and Drive from Business Standard (S$18.80 per user per month); Starter includes Gemini in Gmail.
- Claude Team: US$20 per seat per month on annual billing, for teams of 2 to 150.
Privacy terms for confidential documents
Contracts and tenders are often confidential, and some contain personal data. Use business plans, not personal accounts.
- Claude Team and Enterprise: Anthropic's pricing page states no model training on your content by default. Personal Free, Pro and Max plans list training as opt-out.
- Gemini in Google Workspace: Google's Workspace AI privacy hub says your content is not human reviewed or used for generative AI model training outside your domain without permission.
- Your obligations still apply: confidentiality clauses, the PDPA and client agreements may restrict uploading documents to any third-party service. Check before you upload a client's contract.
How to review a contract with AI and check the answers
AI is a fast first reader, not a lawyer. Use it to find and organise, then verify. Our guide on AI hallucinations as a business risk explains why fluent answers can be wrong.
Upload the clean source file
Use the final Word or PDF version, not a scan or an email thread. Name it clearly, such as 'Lease v3 final'.
Ask focused questions
'List every termination right, with clause number and notice period' works far better than 'summarise this contract'.
Demand quotes and references
Ask the model to quote the exact wording and give the clause or page for every point it makes.
Spot-check against the document
Open the original and check at least the money, liability, termination and renewal clauses yourself.
Ask what is missing
Ask 'which standard protections are absent from this contract?' as a separate question; models are better at finding what is there than noticing gaps.
Get legal advice where it matters
For high-value or unusual contracts, use the AI summary to brief a lawyer, not to replace one.
For large libraries of documents, a retrieval set-up that finds the relevant passages first is more reliable than pasting everything in; see our guide to RAG and chatting with your documents.
Do it yourself or get help?
Most teams can start tomorrow: pick the tool that matches where your files live, use a business plan and follow the checking steps above. If you also write proposals and emails with AI, our Claude vs ChatGPT for business writing guide covers that side.
Staff habits are the main risk: uploading client documents to personal accounts or trusting summaries unchecked. Our Security Awareness Training (S$390) sets up short monthly lessons with completion tracking; pair it with a one-page rule on which AI tool is approved and what may be uploaded.
Frequently asked questions
On Artificial Analysis' long-context reasoning benchmark in October 2026, Claude Opus 5.5 at its highest setting scored 84.7% and Gemini 4 Argon 79.7%, so Claude was ahead. Both list context windows of about one million tokens. If your files live in Google Drive, Gemini's integration may matter more than the score gap.
Claude accepts up to 20 files per chat, each up to 500 MB, with PDFs up to 1,000 pages; it analyses images in PDFs of 100 pages or fewer. Gemini Apps accept up to 10 files per prompt, with documents up to 100 MB each. Very long inputs can still lead to missed details.
Yes. Even top models fail some questions on long-document benchmarks, and research shows details in the middle of long inputs are often missed. Ask focused questions, request exact quotes with clause numbers, and check the important clauses yourself against the original document.
Use a business plan. Claude Team states no model training on your content by default, and Google says Gemini in Workspace does not use your content to train models outside your domain without permission. Also check your confidentiality obligations and the PDPA before uploading other parties' documents.
No. This guide uses Artificial Analysis' published long-context benchmark results, vendor documentation for context windows and upload limits, and vendor pricing pages, with dates. We recommend testing both tools on one of your own past contracts where you already know the answers.