GPT-5.5 TOPS NEW CODING BENCHMARK AT 70%

The DeepSWE benchmark challenges AI models with real-world software engineering tasks, moving beyond simplified assessments that have masked performance differences between top models. The test covers multiple languages and repositories, providing a more realistic evaluation of coding capabilities than previous benchmarks. Datacurve's results indicate GPT-5.5 maintains a measurable advantage over competing models in practical coding scenarios. The benchmark addresses a longstanding gap in AI evaluation—prior leading benchmarks suggested top models performed similarly despite operational differences. DeepSWE's task diversity and scale reveal meaningful performance distinctions that matter for enterprise deployment. As AI agents gain coding capabilities, standardized benchmarks become critical for informed purchasing decisions. The 70% baseline from GPT-5.5 establishes a reference point for evaluating next-generation models across production-grade code repositories.