The Decoder · 10/21/2026, 00:40:29
OpenAI GPT-6 Boosts Coding in Legacy Languages Like COBOL
OpenAI announced significant improvements for legacy programming languages like COBOL and Fortran. GPT-6 Astra achieved an 87.4% average pass rate on MultiLangBench, up from 38% for GPT-5.6 Terra. On the COBOL migration benchmark, GPT-6.1 Sol reached 97.9% accuracy with high reasoning effort, addressing critical infrastructure modernization needs.
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OpenAI improved its latest AI models for "low-resource" languages like COBOL, Fortran, and Visual Basic. These languages have far less available training code than something like Python, but according to OpenAI, they prop up critical infrastructure worldwide. IBM estimates that COBOL powers more than 40 percent of online banking systems and 95 percent of all ATM transactions.
OpenAI built two evaluations to measure progress. MultiLangBench (GitHub) asks models to build a SQLite-compatible database engine from scratch. With maximum reasoning effort, GPT-6 Astra hits an average test pass rate of 87.4 percent across 20 languages, up from about 38 percent for GPT-5.6 Terra. GPT-6 Luna scores 40.3 percent, barely edging out GPT-5.6 Terra (37.9 percent) but at a much lower cost.
Average test pass rate on MultiLangBench across 20 programming languages. GPT-6 Astra and GPT-6.1 Sol both reach about 87 percent, while older models like GPT-5.6 Terra top out at around 38 percent. | Image: OpenAI
On the COBOL migration benchmark, which translates COBOL into C++, Java, Kotlin, Python, or Rust, GPT-6.1 Sol reaches 86.6 percent accuracy at low reasoning effort, compared to 5.4 percent for GPT-5.6 Sol. Cranking up reasoning effort pushes accuracy to 97.9 percent.