Dynamic Languages Faster and Cheaper in 13-Language Claude Code Benchmark
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Empirical multi-language benchmark for AI coding assistants with cost insights.
In a 13-language benchmark, Claude Code implemented a simplified Git (init, add, commit, log, status, diff, checkout, reset) over 600 runs. Ruby ($0.36, 73.1s), Python ($0.38, 74.6s), and JavaScript ($0.39, 81.1s) were fastest, cheapest, and most stable; static languages like Go ($0.50, 101.6s, high variance) and Rust ($0.54, test failures) lagged. Type checking (mypy, Steep, TypeScript) increased generation costs 1.6–3.2×, likely due to higher token usage for type reasoning.
Evaluate type checking overhead in AI-assisted development workflows to balance code safety against generation cost and speed.
The type system overhead directly impacts your AI coding workflow efficiency and cost management for agent orchestration and developer tooling.