ARC-AGI-3 is an interactive reasoning benchmark which challenges AI agents to explore novel environments, acquire goals on the fly, build adaptable world models, and learn continuously.
A 100% score means AI agents can beat every game as efficiently as humans.
Instead of solving static puzzles, agents must learn from experience inside each environment—perceiving what matters, selecting actions, and adapting their strategy without relying on natural-language instructions.
As long as there is a gap between AI and human learning, we do not have AGI.
ARC-AGI-3 makes that gap measurable by testing intelligence across time, not just final answers—capturing planning horizons, memory compression, and the ability to update beliefs as new evidence appears.
ARC-AGI-3 includes replayable runs, a developer toolkit for agent integration, and a UI designed for transparent evaluation.
Inspect agent behavior through preview replays—track decisions, actions, and reasoning in a structured timeline.
Integrate your agent using the ARC-AGI-3 toolkit, then use the interactive UI to test and iterate.
Everything you need to build agents: environments, API usage, and integration guidance.