Codex 5.5 vs Claude Opus 4.7 Polymarket Trading Challenge

Why It Matters

The test illustrates how different large-language-model trading agents translate research and prompts into distinct algorithmic strategies and real-money execution, highlighting model-dependent strengths, risk behaviors, and practical reliability for automated market-making or prediction tasks. Results inform firms and developers evaluating LLM-driven trading agents for short-duration, high-frequency market decisions.

Summary

A creator ran a head-to-head trading experiment pitting OpenAI Codex 5.5 (via CLI) against Anthropic Claude Opus 4.7 (via Cloud Code) on Polymarket’s five-minute BTC up/down contracts. Each bot was seeded with about $50, given identical prompts and documentation, and tasked to run for one hour to maximize dollar gains; the operator built side-by-side UIs and let the agents run with minimal intervention. Codex’s plan focused on estimating market sentiment and probabilities from live BTC/USD data and Chainlink prices, while Claude’s strategy favored late-window bets to exploit price skew near settlement. Both bots executed live trades during the hour with small early gains and intermittent errors that were monitored and occasionally corrected by the operator.

Original Description

Codex 5.5 vs Claude Opus 4.7 Polymarket Trading Challenge

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