Multi-LCB: Extending LiveCodeBench to Multiple Programming Languages

Code generation benchmarks have become central to how the AI community measures progress, but nearly all of them default to Python — a language that dominates training data and may be inflating model scores. Real software engineering, however, demands fluency across Rust, Go, Java, TypeScript, and many others. Multi-LCB extends the established LiveCodeBench framework to twelve languages while preserving its contamination controls, exposing a clear pattern of Python overfitting in leading models. This benchmark directly supports decisions about which models to deploy in polyglot engineering environments, and highlights where additional training investment is needed.