@dabit3: FrontierCode measures "would a maintainer merge this PR?" Essentially intelligence + codebase fluency + judgement, whic…
Summary
Cognition introduces FrontierCode 2.0, a coding benchmark that evaluates whether a model's pull request would actually be merged by a maintainer — testing intelligence, codebase fluency, and judgement beyond simply meeting a spec.
View Cached Full Text
Cached at: 10/29/26, 05:48 AM
FrontierCode measures “would a maintainer merge this PR?”
Essentially intelligence + codebase fluency + judgement, which is what all engineers actually want, not just the raw intelligence most benchmarks test.
Cognition (@cognition): Introducing FrontierCode 2.0: our new coding benchmark that measures a model’s ability to go beyond the spec.
Most coding evals measure a model’s ability to write code that meets a spec. With FrontierCode 1.0, we asked a new question: would you actually merge the PR?
Similar Articles
@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: FrontierCode 1.1 is now on @ArtificialAnlys! Built with open-source maintainers, FrontierCode is the first benchmark to…
FrontierCode 1.1 is now available on Artificial Analysis; built with open-source maintainers, it is the first benchmark measuring end-to-end code quality and mergeability — whether a maintainer would actually merge the PR.
@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.
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.
FrontierCode: a coding eval that raises the bar for difficulty & quality.
FrontierCode is a new coding evaluation benchmark designed to increase difficulty and quality standards for AI code generation.