FrontierCode: a coding eval that raises the bar for difficulty & quality.
Summary
FrontierCode is a new coding evaluation benchmark designed to increase difficulty and quality standards for AI code generation.
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FrontierCode
FrontierCode is a new benchmark from Cognition AI that measures AI models' ability to write high-quality, maintainable code by evaluating mergeability. Results show even top models like Claude Opus 4.8 score only 13.4% on the hardest subset, highlighting a significant gap in code quality.
@denizbirlikci: To understand why we built FrontierCode, read @METR_Evals's blog post on why "many SWE-bench-passing PRs would not be m…
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.
@Murderlon: FrontierCode finally dropped, a coding agents benchmark for the real world. Human-verified through an extensive hardeni…
FrontierCode is a new benchmark for coding agents, human-verified with a continuous scoring model, designed to evaluate real-world performance.
@dabit3: FrontierCode is the first eval to measure the metric that matters most in real software engineering: would you actually…
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.
@cognition: We’ve made improvements to the FrontierCode methodology and are releasing FrontierCode 1.1 with clearer guidelines for …
Cognition releases FrontierCode 1.1, an updated benchmark for evaluating code quality with refined guidelines for fair internet use and grading criteria, along with new model scores for Sonnet 5 and Fable 5.