Research from the benchmark
How the models score on real pull requests, and what the numbers leave out.
When an AI reviewer misses a bug, the code was usually right there
We classified 615 missed bugs across ten models. 80% were real misses, where the relevant code was available and the model did not find the problem. Only 5% were artifacts of the test setup.
One model on our board is right 74% of the time and finds 12% of the bugs
Gemini 3.7 Flash has the best precision we measured and the worst recall. That is not a defect, it is a posture, and which posture you want depends on what the review is for.
The cheapest model on the board finds more bugs per dollar than the most expensive
Cost per pull request ranges from $0.10 to $1.62 across ten models. Recall does not follow. The cheapest option costs $0.08 per bug found; the most expensive costs $1.25.
A three point gap between two AI reviewers is probably noise
Every entry on this leaderboard is one run. We measured how much the score moves from sampling and from the judge alone, and the answer is enough to reorder the middle of the table.
AI reviewers are four times worse at Java than at Go
The same ten models, the same harness, the same scoring. Mean recall on Go pull requests is 57.5%. On Java it is 13.1%. Every model shows the gap.
The best AI code reviewer finds fewer than half the bugs
We ran ten models over the same thirty merged pull requests, scoring them against bugs that human reviewers actually flagged. The top scorer found 44% of them. None broke 50%.