Claude vs Gemini: the better analyst or the better Google assistant

Give Claude a 300-page tender document and a question about its liability clauses, and you'll get a careful answer with the reasoning laid out. Give Gemini the same, from inside Google Drive, and you'll get an answer without having moved the file. Both are useful. They're useful to different people.

We'd pick Claude for most analytical work: research, reports, spreadsheets, contracts, anything where the quality of the reasoning is the product. We'd pick Gemini for people whose working day already runs on Gmail, Docs and Drive, and for anyone who wants images or video from the same subscription. The best counter-argument to our view is in the next section: on a specialist legal benchmark, Gemini 4 Argon matches Claude almost exactly.

Prices from claude.com/pricing and gemini.google, checked 22 October 2026.

This pair shows why a single "accuracy" score misleads.

Broad knowledge and reasoning. On the Artificial Analysis Intelligence Index, a blend of ten evaluations, Claude Opus 5.5 is first at 58 and Gemini 4 Argon (high) scores 53. On AA-Omniscience, 6,000 knowledge questions that penalise confident wrong answers, Opus 5.5 leads at 46, and the highest raw accuracy belongs to Claude Fable 5.1 (67%) and Opus 5.5 (66%). Argon isn't in the top three on either measure (Artificial Analysis, checked 22 October 2026).

A specialist task. Vals AI's LegalBench has Claude Fable 5 at 88.56%, Fable 5.1 at 88.51% and Gemini 4 Argon at 88.30% (Vals AI, 13 October 2026). That's a tie, and a reminder that a general lead doesn't carry over to every domain.

Summarising a document. The newest models aren't measured yet. The previous generation was close: Claude Sonnet 4.6 added unsupported facts to 10.6% of summaries, Gemini 3.1 Pro (preview) to 10.4% (Vectara, updated 16 October 2026).

What the scores don't show. Two-thirds accuracy at the top of AA-Omniscience still leaves a third of the questions missed. And the lowest hallucination rates on that board belong to small models such as MiniCPM5-1B, which mostly decline to answer. Getting more right and knowing when to stop are different skills, and the public evidence for comparing these two on the second is thin.

Our reading: Claude is the stronger model on the broad measures, which is why we'd pick it for analysis. The margin is small enough that your own test should outrank it. More in the most accurate AI.

Your own test is quicker when every claim is labelled. Count connects to Claude and shows what each one rests on: a source you can open, an assumption, or nothing.

Claude Pro ($20, or $17 billed annually) adds Research, Claude Code, unlimited Projects, Claude in Chrome and Microsoft 365, scheduled tasks and Opus alongside Sonnet and Haiku. Fable 5.1, Anthropic's most capable model, is on Pro only through paid usage credits. Limits reset on a rolling five-hour window with weekly limits on top and "no fixed message count" (claude.com/pricing).

Google AI Pro ($19.99) adds Gemini 4 Argon, four times the free usage, Gemini in Gmail, Docs and Vids, Antigravity, YouTube Premium Lite and 5 TB of storage. Limits are compute-based and also refresh "every 5 hours until you reach your weekly limit" (Google support).

Under $20, only Google has an answer: AI Plus at $4.99 gives the Flash model and a 128K context. Above it, Claude Max costs $100 or $200 for five or twenty times Pro's per-session usage, plus $100 or $200 a month of API credits. Google AI Ultra costs $99.99 or $199.99 for five or twenty times AI Pro's usage. The symmetry is almost suspicious.

On the free tiers, Gemini gives away more: Deep Research and image generation are included, while Claude Free has web search, code execution, memory and up to five Projects but no Research and no Opus. Free Gemini's 32K context is the catch, which brings us to documents.

Most work questions are really questions about a document: a contract, a board pack, a data export. Here the two differ in practice more than in the specification.

Claude takes up to 20 files per chat and PDFs of up to 1,000 pages; PDFs of up to 100 pages are read with their charts and images, longer ones as text only (Claude help centre). Anthropic's own prompting guidance is built around long inputs: documents first, the question last, quotes before the answer. Claude can also produce the output as a Word file, spreadsheet or deck.

Gemini on AI Pro has a 1M-token context too, and Google's guidance agrees on the order: long context first, "your specific instructions or questions at the very end of the prompt". Its real advantage is that your files are probably already in Drive. On the free tier, though, 32K tokens is a small window, and a long document will be read in part and answered in full.

For any calculation, both should run code rather than reason in prose. Google says so explicitly: code execution "whenever the model needs to perform any kind of arithmetic, counting, or calculation" (Gemini API docs). An illustrative test: upload a year of subscription data and ask for monthly churn. Then ask whether it divided by customers at the start of the month or the average, and whether it counted downgrades.

Claude's Research runs searches that build on each other, reads across the web and any connected apps (Google Workspace included), and returns a cited report. It runs on Opus 5.5 whatever model you've selected, most reports take 5–15 minutes, and Anthropic says complex ones can take up to 45 (Claude help centre). Gemini's Deep Research is on every tier, free included.

The independent evidence is lopsided. Gemini has been tested and fared badly: in the EBU and BBC's study of news answers from four assistants, 45% of responses had a significant issue and Gemini's figure was 76% (EBU/BBC, October 2025). In the Tow Center's citation test, Gemini gave a completely correct answer once (March 2025). Both predate Argon.

Claude wasn't in either study, and we found no independent evaluation of Claude Research's citations. Absence of evidence isn't a clean bill of health. It means you are the evaluation. See Claude Research for how to get checkable citations out of it.

Pick a long document you've already read closely: a contract you negotiated, a report you wrote. Give it to both with the same question.

A two-minute check

1. Ask for page references. For each claim, "which page and which sentence?" Open three and read them.
2. Ask something the document doesn't answer. This is the test no index runs for you. A good answer says it isn't in there; a bad one invents a plausible clause.
3. Ask about the end. If the key detail is on the last pages, a model reading part of a long file will miss it.
4. Make the numbers run as code. Then check which figures it took from the document and which it assumed.
5. Ask for its assumptions. "Which parts of your answer aren't stated in the document?"

Claude will probably give you more. Step 2 tells you whether you can trust the more. It's also why Count exists: connect it to Claude, or any assistant that supports MCP, and it splits the answer into claims, labelling each as a citation you can open, an assumption, model knowledge or a hallucination, with the reasoning chain behind it.

We've written about why the most fluent answer gets the least scrutiny in the trust trap.

Is Claude better than Gemini?

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Can Claude generate images like Gemini?

Is Gemini or Claude better for long documents?

Can I use Claude with Google Docs and Gmail?