Document analysis needs three things: a context window large enough for the whole file, careful instruction-following, and a low rate of invented facts. Claude Sonnet 5.5 is the most reliable default for contract review and structured extraction, with a 1M-token window at $2/$10. Claude Opus 5.5 is the step up for long, interlinked documents. For high-volume extraction — invoices, forms, receipts — Claude Haiku 5.5 or Gemini 3.8 Flash cut the cost sharply, and Gemini reads scanned pages natively.
The safest document analysis default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Claude Sonnet 5.5 is the strongest answer here for document analysis — pick it when quality of output matters more than the $2.00/1M/1M input you pay for it.
Gemini 3.8 Flash handles the same job for about 63% less per token. Start here and only move up if the output is not good enough.
Claude Opus 5.5 is the fastest of these for document analysis — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Claude Sonnet 5.5 is the best default for contract review and structured extraction.
Current models all hold about a million tokens, so most documents fit in a single pass.
For high-volume extraction, Claude Haiku 5.5 or Gemini 3.8 Flash cost a fraction of a mid-tier model.
Choose Claude Sonnet 5.5 for legal, financial and compliance review where accuracy matters.
Choose Claude Opus 5.5 when documents are long and interlinked and a missed clause is expensive.
Choose Gemini 3.8 Flash for scanned documents and bulk forms, and Claude Haiku 5.5 for plain-text extraction at volume.
Switch the scoring lens to see whether the document analysis answer changes when cost, speed, or long-document depth leads the decision.
Anthropic / Balanced / Oct 10, 2026
Near-Opus 5.5 quality on scoped work at half the price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
The work is long, ambiguous and multi-step — Anthropic positions Opus 5.5 for exactly that — or you need the lowest possible price, where Haiku 5.5 costs a twentieth as much.
Where the document analysis recommendation shifts once you weigh price or latency differently.
Near-Opus 5.5 quality on scoped work at half the price.
Anthropic's new coding default — top SWE-bench Pro score at a lower price than Opus 5.
Google's fast agentic workhorse — strong coding at Flash pricing.
Near-Astra capability at Sol pricing — OpenAI's value pick.
Anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Claude Sonnet 5.5Anthropic | $2.00/1M | $10.00/1M | $40 | 1M tokens | Fast | 98 | 98 | 95 |
| Claude Opus 5.5Anthropic | $4.00/1M | $20.00/1M | $80 | 1M tokens | Deliberate | 100 | 97 | 99 |
| Gemini 3.8 FlashGoogle | $0.75/1M | $3.75/1M | $15 | 1M tokens | Very fast | 92 | 86 | 89 |
| GPT-6.1 SolOpenAI | $2.00/1M | $10.00/1M | $40 | 1.1M tokens | Balanced | 98 | 94 | 97 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for document analysis, what it is genuinely good at, and where we would steer you away from it.
Our pick for document analysis. It scores 98/100 on the coding axis we weight this page by, and nothing else in this shortlist matches it on output quality.
Anthropic's September 28, 2026 Sonnet — built for well-scoped everyday work like features, bug fixes, documents, slides and spreadsheets, priced at $2/$10 and close to Opus 5.5 on most of Anthropic's launch rows.
The work is long, ambiguous and multi-step — Anthropic positions Opus 5.5 for exactly that — or you need the lowest possible price, where Haiku 5.5 costs a twentieth as much.
The model most people should default to in the Claude lineup. Sonnet 5.5 lands within a few points of Opus 5.5 on most of Anthropic's launch rows, beats it on Terminal-Bench 4.0, and costs half as much. Step up to Opus 5.5 only when the task is open-ended and long.
Full pricing, benchmark table and release notes on the Claude Sonnet 5.5 page.
Here for latency: it answers fastest of anything listed for document analysis, at 100/100 on coding.
Anthropic's September 22, 2026 Opus — a step up from Opus 5 on agentic coding, long-running agent work and vision, at a lower $4/$20 list price and with fewer tokens spent per finished task.
Your tasks are well-scoped and latency-sensitive — Sonnet 5.5 is half the price and Anthropic says it is the fastest Sonnet yet.
The new premium coding default from Anthropic. Opus 5.5 posts the highest SWE-bench Pro figure in any launch table we track and costs less than Opus 5 did. Fable 5.1 still makes sense for the hardest open-ended research at $10/$50; for almost everything else Opus 5.5 is the better buy, and Sonnet 5.5 at half the price is close behind on well-scoped work.
Full pricing, benchmark table and release notes on the Claude Opus 5.5 page.
The value option for document analysis: about 63% less per token than Claude Sonnet 5.5, at 92/100 on coding. Worth starting here and moving up only if the output disappoints.
Google's fast agentic workhorse — strong coding at Flash pricing. Full Gemini 3.8 Flash review →
Rounds out the shortlist for document analysis at 98/100 on coding.
Near-Astra capability at Sol pricing — OpenAI's value pick. Full GPT-6.1 Sol review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Claude Sonnet 5.5 for most PDF analysis — it follows extraction prompts closely and rarely invents details. For scanned PDFs and large batches, Gemini 3.8 Flash reads pages natively at a lower price.
Yes, with careful prompting. Claude Sonnet 5.5 and GPT-6.1 Sol both handle financial tables well. Tell the model to report only figures it reads directly, and check key numbers by hand — even strong models make arithmetic slips.
Give the model the full document and ask specific extraction questions rather than for a general summary. Claude Opus 5.5, Sonnet 5.5, Gemini 3.1 Pro and the GPT-6 models all take about a million tokens. Long inputs cost more per question, so prompt caching helps if you ask many questions of the same file.