Inside ARC-AGI-3 Leaderboard: Balancing Interactive Adaptability and Compute Cost
GregKamradt · x · 2026-08-01
The ARC-AGI benchmark has evolved to its third version (ARC-AGI-3), challenging AI agents to dynamically adapt in novel interactive environments.
The official leaderboard uses a scatter plot to visualize the critical relationship between cost-per-task and performance, emphasizing that true intelligence requires solving problems efficiently with minimal resources. The board categorizes systems into three main types:
- Reasoning Systems: Displaying connected points for the same model at different reasoning levels, typically showing asymptotic performance gains with more thinking time.
- Base LLMs: Single-shot inference results from standard models like GPT-4.5 and Claude 3.7 without extended reasoning.
- Kaggle Systems: Purpose-built, efficient methods designed under strict computational constraints (a $50 compute budget for 120 tasks).
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