OpenAI 称 GPT-6 在 COBOL、Fortran 等遗留编程语言上表现大幅提升
OpenAI says GPT-6 is much better with legacy programming languages such as COBOL and Fortran
OpenAI 改进最新模型在 COBOL、Fortran、Visual Basic 等低资源编程语言上的能力，并构建了两个评测来衡量进展。MultiLangBench 要求模型从零构建兼容 SQLite 的数据库引擎，GPT-6 Astra 在 20 种语言上的平均测试通过率达 87.4%，而 GPT-5.6 Terra 约为 38%。
原文给出两个基准上各版本模型的通过率对比，读者可据此判断 GPT-6 系列在遗留语言上的能力跃升幅度。
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.
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.
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来源：The Decoder · the-decoder.com