OpenAI says GPT-6 Astra sharply improves coding in COBOL, Fortran and Visual Basic
OpenAI published research saying its latest models are substantially better at building and migrating software in low-resource languages such as COBOL, Fortran and Visual Basic, which it says have far less training code than Python or JavaScript yet support critical infrastructure. On MultiLangBench, which asks models to build a SQLite-compatible database engine from scratch in 20 languages, OpenAI reports GPT-6 Astra reached an 87.4% average test pass rate at maximum reasoning effort versus 26.8% for GPT-5.6 Sol, with COBOL rising from 10.9% to 72.1% and cheaper GPT-6 Luna averaging 40.3%. On a separate COBOL-to-C++, Java, Kotlin, Python or Rust migration benchmark, OpenAI says GPT-6.1 Sol scored 86.6% at low reasoning effort versus 5.4% for GPT-5.6 Sol, and 97.9% at higher effort. OpenAI cautions that applying such migration results to production software still requires expert review and testing against business rules and dependencies.
OpenAI says COBOL supports more than 40% of online banking systems, 80% of in-person credit card transactions and 95% of ATM transactions, so better model support for these languages could help teams maintain and modernize software that essential services depend on.
Our latest model advances bring stronger capabilities for building and migrating software in low-resource programming languages such as COBOL, Fortran, and Visual Basic. These languages have less code and documentation available for models to learn from than languages like Python and JavaScript, yet support critical infrastructure and essential services around the world. COBOL supports(opens in a new window) more than 40% of online banking systems, 80% of in-person credit card transactions and 95% of ATM transactions, while Fortran is used in weather forecasting(opens in a new window) and nuclear reactor safety analysis(opens in a new window). Improving AI’s ability to work in these languages could help teams maintain and modernize the software that essential services depend on.
This work is guided by feedback from developers and enterprise customers who have told us that coding models often struggle with these languages. Maintaining and modernizing this software can be difficult: documentation may be incomplete, original developers may have left the company, and important business rules may only exist in code. Whether teams are fixing bugs or migrating to another language, they need to preserve the behavior their systems depend on.
#OpenAI#GPT-6 Astra#GPT-6.1 Sol#GPT-6 Luna#GPT-5.6 Sol#COBOL#Fortran#Visual Basic#MultiLangBench#SQLite