Huawei AI clears 25 games using RSI! 56% fewer operations than humans

Huawei Noah's Ark Lab, together with teams such as UCL, proposed the Memento 3 agent system, which cleared all 25 games and 183 levels in the ARC-AGI-3 public set, achieving a perfect RHAE score of 100. The system uses Claude Opus 5 as the base model, without updating weights or fine-tuning for games, and performed 7,518 operations in total, about 56% fewer than the human's 17,135. The core method, Code as Model, lets the AI maintain a Markdown rulebook and an executable Python world model, first reasoning through then acting, and when rules are wrong, modifying them and verifying against the 64×64 frames cell by cell. As a comparison, Claude Opus 5 achieves an average RHAE of about 40.7 under the official ARC Prize framework. The research team also had the system challenge Atari Pong, scoring 21:0 in three consecutive games without further invoking the large model.