Inspired by LMArena for LLMs, we've built a platform that allows anyone to compare code generation models side-by-side, but with a crucial difference: you can actually run the code and see what it produces. Just submit a coding task, watch two different models generate solutions, execute both programs, and vote on which model produced better results. The outcomes are organized into a leaderboard that displays the community's highest-rated models.

The field of code generation has long struggled with reliable evaluation methods. Traditional benchmarks like HumanEval test code against predefined test cases, but these represent only a tiny fraction of real-world programming tasks. Human evaluation platforms exist for general chatbots, but they fall short for code: reading raw source code and mentally simulating its execution is cognitively demanding and error-prone, especially for longer programs or complex UI applications.

You ask two AI models to build a responsive photo gallery website. Both generate code that looks syntactically correct. But which one is actually better? Without running the code, it's nearly impossible to tell. One might produce a beautiful, functional grid layout, while the other might have subtle bugs or poor styling that only become apparent when rendered in a browser.

This observation led us to a key insight: execution feedback is essential for humans to judge code quality reliably. That's exactly what BigCodeArena provides.

BigCodeArena extends the Chatbot Arena framework with powerful features specifically designed for code evaluation:

Every code snippet generated by models is automatically executed in isolated sandbox environments.

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