TL;DR for operators A better plan can become a worse agent when the environment keeps moving while the system thinks. STAR makes that reversal unusually clear: Kimi-K2-Thinking leads the unlimited-deliberation evaluation with a rating of 1206.1 and a 1.00 win rate, then falls to 842.6 and a 0.210 win rate in real-time play, where GLM-4.6 leads at 1180.8.1 ...
TL;DR for operators A Pokémon tournament sounds unserious until you notice what it does better than many enterprise AI pilots: it forces models to make constrained, sequential, adversarial decisions, then records not only what they did but why they said they did it. The paper behind this article introduces LLM Pokémon League, a benchmark where eight models from the GPT, Claude, and Gemini families act as Pokémon trainers. Each model selects a six-member team, then makes turn-by-turn battle decisions in a zero-shot setting. The framework captures team-building rationales, move choices, switching decisions, and explanations throughout the tournament.1 ...