gpt‑4o‑mini) for both player policies and the judge

GPT-4o-mini serves as a high-speed, cost-effective engine for simultaneous agent policy execution and automated judging.

OpenAI's GPT-4o-mini delivers 128k context windows and a 15-M-token-per-minute rate limit, making it the optimal choice for multi-agent simulations. By deploying this model for both player policies and the judge, developers achieve sub-second latency and a 99% cost reduction compared to GPT-4o. This unified architecture ensures consistent reasoning patterns across the game loop: the model generates strategic moves for players while simultaneously providing structured evaluations of those actions with high reliability (scoring 82% on the MMLU benchmark).

https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/