LamBench: A Lambda Calculus Benchmark Suite for AI Coding Agents
Victor Taelin released LamBench v1, a benchmark framework designed to test AI coding agents on lambda calculus problems. The project is hosted on GitHub at github.com/VictorTaelin/LamBench and includes a live site at victortaelin.github.io/lambench/.
Key Details
- Metrics: The benchmark measures three axes:
:intelligence,:speed, and:elegance. - Components: A set of
:problemsand a:matrixfor scoring results. - Version: v1 (initial release).
LamBench is part of a broader effort by Taelin to create rigorous evaluations for AI systems in symbolic computation. For context, lambda calculus is a formal system in mathematical logic and computing, often used to test reasoning and functional programming capabilities — making this benchmark particularly relevant for AI coding agents that need to handle symbolic manipulation, recursion, and higher-order functions.
Who It's For
AI researchers and developers building or evaluating coding agents, especially those working with functional programming or symbolic reasoning tasks.
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