We Let Claude Code and Codex Race Human Researchers — Elie Bakouch, Prime Intellect

This post details an experiment where AI agents (Claude Code, Codex) were used to compete in an 'Optimizer Speedrun' to train a GPT-2 level model, with both agents surpassing the human record. It observes distinct behaviors between agents: Claude Code's tendency to stop and declare records unbreakable versus Codex's continuous operation and extensive note-taking. The experiment also explored a six-day run with Claude, Codex, Kimi, and GLM, measuring efficiency in tokens and identifying that Kimi was the most token-efficient. A key finding is that none of the models invented new optimizers, instead combining existing ideas. The post introduces Prime Intellect's ongoing work on an AlphaEvolve-style loop for AI-driven discovery and argues for open research in this domain.