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FrontierCode is a new coding evaluation benchmark that measures code mergeability, claiming 81% fewer misclassification errors than SWE-Bench Pro. Tasks were crafted by maintainers of open-source projects like Celery, uppy, and Mattermost.
FrontierCode is a new coding benchmark from METR and Cognition that evaluates AI models on code maintainability and quality, revealing that many models produce unmergeable code. It includes over 1000 hours of work and shows that even top models struggle, with Opus 4.8 achieving only 13.8% on the hardest tier.
Cognition announces FrontierCode, a new coding evaluation benchmark that goes beyond unit tests to measure code quality, scope, test correctness, and human reviewer approval, addressing the issue of agents writing sloppy code that passes tests but is not maintainable.
Cognition introduces FrontierCode, a high-quality coding benchmark that goes beyond unit tests to measure code maintainability, regression safety, and quality, with 150 handcrafted tasks by open-source developers.
SanthProject praises Cognition's new FrontierCode coding evaluation benchmark, calling it a fair alternative to the DeepSwe benchmark.