OpenAI says its new models are much better at COBOL and other old languages
Sorted AI20 OctOpenAI says its latest models have improved sharply at low-resource programming languages such as COBOL, Fortran and Visual Basic, which underpin many banking and government systems but have little training data. It reports the gains on two of its own evaluations. On MultiLangBench, which asks a model to build a SQLite-compatible database engine across 20 languages, OpenAI says GPT-6 Astra reached an average pass rate of 87.4%, up from 26.8% for GPT-5.6 Sol. On an in-house COBOL migration test, it says GPT-6.1 Sol scored 86.6% at low reasoning effort against 5.4% before, reaching 97.9% at higher effort. OpenAI cautions that using this on production software still requires expert review and testing against the system's own business rules, and it is releasing the MultiLangBench setup on GitHub. These are OpenAI's own results.
Why it matters: If your organisation still runs COBOL or other legacy code, these models may help you understand, fix or migrate it, but keep an expert in the loop and test against your real business rules before changing anything live.
OpenAI ↗AI-assisted, reviewed by Sorted AI
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