Oktopeak
Legal Tech November 5, 2026 · 10 min read

Which Claude Model Should Review a Contract? We Tested All Four

We hid 8 traps in two software contracts and ran Haiku, Sonnet, Opus and Fable 24 times. All found all 8. Costs, list lengths and the flaw most runs missed.

By Saša Sladić · Co-Founder & CEO
Which Claude Model Should Review a Contract? We Tested All Four

[ KEY TAKEAWAYS ]

For a first scan of a standard vendor contract, the cheapest Claude model is enough: Haiku found all 8 traps we planted in every run, for under a cent. For a contract your firm will live with for years we'd use Sonnet or Opus, because their lists were shorter. That last part is a judgment call, and two contracts can't prove it.

Tests run 4 November 2026 on Claude Haiku 5.5, Sonnet 5.5, Opus 5.5 and Fable 5.1. API list prices checked 28 October 2026. Contracts, answer keys, every answer and the script are public on GitHub.

24 of 24

reviews found all 8 planted traps, across four models and two contracts.

80x

is the price gap between Haiku and Fable on the harder contract: $0.003 against $0.23 a review.

$1.80

paid for all 24 reviews together, at API list prices.

0 of 12

runs noticed the unplanned flaw in the first contract, on any model.

Which model for which job

A quick first scan of a standard vendor contract
Haiku. It found every planted trap, and a review costs a fraction of a cent. Expect a long list with ordinary clauses mixed in.
A contract the firm will live with for years
Sonnet or Opus. Opus wrote the shortest lists on the first contract. On the second, both caught the flaw Haiku mostly missed. Either way it costs cents.
Thinking of paying for Fable on contract work
Nothing in this test separated it from Sonnet or Opus, and it cost about three to five times more. Two contracts can't rule out a difference on harder ones.

How we ran it

We wrote a software contract of the kind a law firm signs for its case management system, 12 sections, mostly boring, and hid a trap in eight of them. Each model got the same instruction: you're reviewing this for a 12-lawyer firm about to sign it, list every risky clause. Three runs per model, default settings, no special instructions.

Those traps were obvious on purpose. Real contracts tend to put the bad part in a definition at the top and use it twenty paragraphs later, so we wrote a second contract with the same 8 dangers hidden that way. There, a trap only counted when the answer named the actual danger. Citing the right section wasn't enough.

Results: every model found every planted trap

All four models found all 8 traps in all 24 runs. The most expensive review cost 78 to 80 times the cheapest, for the same 8 traps. What changed between models was the number of issues a lawyer has to read through.

Contract 1Traps foundCost a reviewIssues listed
Haiku 5.58 of 8$0.00216 to 19
Sonnet 5.58 of 8$0.0315 to 16
Opus 5.58 of 8$0.058 to 10
Fable 5.18 of 8$0.1610 to 13
Contract 2, hidden trapsTraps foundCost a reviewIssues listed
Haiku 5.58 of 8$0.00323 to 24
Sonnet 5.58 of 8$0.0516 to 17
Opus 5.58 of 8$0.0813 to 18
Fable 5.18 of 8$0.2315 to 16

Average cost per review at API list prices, three runs per contract per model. Per million tokens, input and output: Haiku $0.10 and $0.50, Sonnet $2 and $10, Opus $4 and $20, Fable $10 and $50. Check the cost calculator for your own volumes.

On the first contract Opus listed 8 to 10 points, almost all of them the real traps. Haiku listed 16 to 19. Some of its extras were fair points to negotiate, and others were clauses most firms sign without a second look: the 99.5% uptime promise, the right to cancel if the vendor breaks the contract, Delaware law. At these prices the AI is the cheapest part of the review, so the shorter list usually matters more than the price of the model. That gap narrowed on the second contract, where Opus listed up to 18.

The flaw we didn't plant

Both contracts cap the vendor's liability at the fees paid in the month before the claim, and both have the firm pay once a year. So in most months the cap is zero. We wrote that by accident. No model noticed it in the first contract. In the second, three models caught it in every run and Haiku in one of three.

ModelContract 1Contract 2
Haiku 5.50 of 3 runs1 of 3 runs
Sonnet 5.50 of 3 runs3 of 3 runs
Opus 5.50 of 3 runs3 of 3 runs
Fable 5.10 of 3 runs3 of 3 runs

A run counts when the answer says the cap falls to zero or near zero because fees are paid annually. Answer key in the repo.

Fable's second run put it plainly: "the cap is zero in eleven months of the year." Haiku's first run said the cap "is a very small amount", which is true and misses the point.

It's tempting to read that as proof the expensive models see more, and two contracts don't support it. The second contract spells the cap out through a "Fee Period" definition, which may be what made the flaw easier to spot, and on the first contract Fable missed it in all three runs just as Haiku did. We'd treat it as a reason to look closer. It's also a reminder that a clean result on the traps you planted says nothing about the ones you didn't think of.

The 8 traps, and what to ask for instead

These are worth knowing whether or not you ever use AI on a contract.

TrapHow it read in contract 1Ask for
The long renewalRenews for 3 years unless you cancel 4 months before the end, by letter only12-month renewals and notice by email
Price changes by websiteThe vendor raises the price by updating its pricing page, mid-contract, with no noticeFixed fees for the term, a capped yearly increase, written notice
Client files train their AIA permanent right to use your data to build its products, surviving the end of the contractDelete the clause. Your data runs the service and nothing else
Paying for your own dataA full export costs $4,000 a time, takes up to 60 days and comes in the vendor's formatA free full export, at any time, in a format other software can open
Locked out over one invoiceOne payment past due and they can cut access, including to your files, with no warningWritten notice, a cure period, and read access to your files no matter what
The vendor owes one month's feeIf they leak client data, the most they owe is what you paid in the prior monthA cap of at least 12 months of fees, higher for data breaches
You pay for their mistakesYou cover the vendor's losses from your use of the software, even when the vendor caused themEach side covers its own fault
Deleted a week after you leaveSeven days after the contract ends, everything is goneAt least 60 days to get it out, and written confirmation before deletion

How the same traps hide in a real contract

The second contract keeps every danger and moves it out of sight. Four examples from it:

Every model connected those. Haiku did the $250 times 16 math itself, and it spotted that "Losses" quietly includes the vendor's own fault.

What this test doesn't prove

Before you use a real contract Whatever you review goes to Anthropic to be processed. Check your confidentiality duties and your agreement with Anthropic before you put a client document through this, and read which Claude plan fits a law firm and how zero data retention works first. Nothing here is legal advice.

Run it on your own contract

Download the contracts as PDFs: contract 1 and contract 2. Both are fictional. The GitHub repo has those, the answer keys, all 24 answers and a small Python script that sends any PDF or text contract to the models you pick and saves what each one said and what it cost. You need an Anthropic API key, and reviews are charged to it. The script shows a rough cost and asks before it spends anything.

Frequently asked questions

Which Claude model is best for contract review?

Our test didn't separate them on the traps we planted: Haiku, Sonnet, Opus and Fable each found all 8 in all 24 runs. The differences were cost and list length. Haiku cost about $0.003 a review and listed up to 24 issues. Opus cost about $0.08 and listed 8 to 18. For a first scan Haiku is enough. For a contract the firm will live with for years we'd use Sonnet or Opus, which is a judgment call the test doesn't settle.

Is the cheapest Claude model good enough to review a contract?

It found every trap we planted, in both contracts, in every run. It caught the flaw we didn't plant in only 1 of 3 runs on the second contract, and it listed up to twice as many issues as Opus for a lawyer to read. That makes it fine for a first scan and weak as the only read of a contract that matters.

How much does it cost to review a contract with Claude?

Our two contracts cost between $0.002 and $0.23 per review at API list prices, depending on the model. All 24 reviews together cost $1.80. A longer contract costs proportionally more. The lawyer reading the result costs far more than any of these.

Can a law firm put a client contract into Claude?

Check your confidentiality duties and your agreement with Anthropic first, because the contract text goes to Anthropic to be processed. Which terms apply depends on the plan. Team doesn't train on your content by default. The API can run under a zero data retention agreement, which also limits which models you can use.

Does this mean AI can replace a lawyer on contract review?

No. We wrote both contracts ourselves, and a contract drafted by a vendor's lawyers is harder. No lawyer reviewed our answer keys or the model answers, and finding a trap isn't the same as giving good advice. What the test shows is what a lawyer can expect to get as a first pass.

Can I run this test on my own contract?

Yes. The script, both contracts, the answer keys and all 24 answers are public on GitHub under an MIT license. You need Python and an Anthropic API key, and reviews are charged to your key. The script shows a rough cost and asks before it spends anything.

Choosing a model for your firm's documents?

Thirty minutes on what your firm reviews, which plan you're on and where the documents can safely go. You leave with a model and a data path you can defend.

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Saša Sladić

[ WRITTEN BY ]

Saša Sladić

Co-Founder & CEO

Co-Founder and CEO at Oktopeak. Works with founders in legal, healthcare and fintech to get stalled, broken and inherited products into production.

[ LEGAL TECH ]

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