This article provides an in-depth comparison of the real-world performance of two AI models, Gemini 3 Pro and 2.5 Pro, in the game Pokémon Crystal. Gemini 3 Pro emerged as the champion, standing out with its higher efficiency (halving the number of turns and reducing token consumption by 60%) and superior capabilities, winning every match without a single loss. In contrast, the 2.5 Pro model encountered looping challenges in areas like the Olivine Lighthouse. The study highlights Gemini 3 Pro’s significant advantages in spatial awareness, token-perception navigation, multitasking, and long-term planning, while also revealing its weaknesses, such as making unverified assumptions. This experiment offers valuable insights into the development of AI agents in complex environments, emphasizing the critical value of intelligent planning and tool use in long-horizon tasks.
