ProgramBench Reveals Why Language Models Struggle With Full-Stack Development

As language models are increasingly deployed to autonomously develop software projects, ProgramBench provides the first comprehensive benchmark measuring what truly matters: building complete, production-ready systems end-to-end. The findings are sobering—no language model fully resolved any of the 200 tasks, and even the best achieved only 95% test success on 3% of problems. This exposes a fundamental gap in current AI: models excel at isolated code components but falter when facing architectural decisions and system-wide design requirements.