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Short answer: on the one public benchmark either tool has been scored on, the two best AI code reviewers land within two points of each other and one of them costs about a sixth as much per run. What follows is every figure this repo has collected on that comparison, each kept with the sentence it was published in and the date it was read. Corrections and counter-numbers are the point of this thread.
The figures that exist, and where each came from
43.1% and 41.2% — "On ReactBench, GPT 5.6 Sol and Fable 5 posted Pass@1 scores of 43.1% and 41.2%." (2026-08-21)
$1.43 vs $9.05 — "A single run costs about $1.43 on the first and $9.05 on the second." (2026-08-21)
43.1% — "A 43.1% filter is useful in front of a reviewer and useless in place of one." (2026-08-21)
1/9 — "Open Code Review requires 1/9th the tokens of standard agents and offers a 20% higher accuracy rate." (2026-08-12)
60% — "It integrates with GitHub Actions and CircleCI, and its structured review comments cut false positives by 60%." (2026-08-10)
What none of these are. ReactBench is one benchmark on one kind of task, and both models were built for something broader than code review. The 1/9 and 60% rows are vendor self-reports restated in a write-up, not independent measurements. The 95% row is in the list because the write-up quoted it in order to doubt it — a figure that gets repeated everywhere is still a figure someone published, and dropping it would make this list look more settled than it is.
The part that decides the bill. A score within two points and a price six times apart means the cheap one is the one you can afford to run on every pull request, and the expensive one is the one you run once a week and then stop running. Coverage, not accuracy, is usually what changes.
Every figure quoted next to each name, on one page:
The one thing worth replying with: if you run an AI reviewer on real pull requests, what share of its comments do you actually act on — and what does one review cost you? A one-line reply with a ratio and a price is worth more than any row above, and it goes into the table with your wording kept.
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Short answer: on the one public benchmark either tool has been scored on, the two best AI code reviewers land within two points of each other and one of them costs about a sixth as much per run. What follows is every figure this repo has collected on that comparison, each kept with the sentence it was published in and the date it was read. Corrections and counter-numbers are the point of this thread.
The figures that exist, and where each came from
43.1%and41.2%— "On ReactBench, GPT 5.6 Sol and Fable 5 posted Pass@1 scores of 43.1% and 41.2%." (2026-08-21)$1.43vs$9.05— "A single run costs about $1.43 on the first and $9.05 on the second." (2026-08-21)43.1%— "A 43.1% filter is useful in front of a reviewer and useless in place of one." (2026-08-21)1/9— "Open Code Review requires 1/9th the tokens of standard agents and offers a 20% higher accuracy rate." (2026-08-12)60%— "It integrates with GitHub Actions and CircleCI, and its structured review comments cut false positives by 60%." (2026-08-10)95%— "That 95% export-issue figure gets quoted everywhere." (2026-08-10)What none of these are. ReactBench is one benchmark on one kind of task, and both models were built for something broader than code review. The
1/9and60%rows are vendor self-reports restated in a write-up, not independent measurements. The95%row is in the list because the write-up quoted it in order to doubt it — a figure that gets repeated everywhere is still a figure someone published, and dropping it would make this list look more settled than it is.The part that decides the bill. A score within two points and a price six times apart means the cheap one is the one you can afford to run on every pull request, and the expensive one is the one you run once a week and then stop running. Coverage, not accuracy, is usually what changes.
Every figure quoted next to each name, on one page:
Write-ups with the full context:
The one thing worth replying with: if you run an AI reviewer on real pull requests, what share of its comments do you actually act on — and what does one review cost you? A one-line reply with a ratio and a price is worth more than any row above, and it goes into the table with your wording kept.
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