Benchmark Leaderboards
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Track which models hold the current SOTA on the benchmarks the field actually uses. Click a column header to sort; the leading row is highlighted.
ARC-AGI-1 (Semi-Private Eval) β the original Abstract Reasoning Corpus benchmark by FranΓ§ois Chollet. 400 novel visual reasoning tasks designed so memorisation cannot substitute for genuine generalisation. Human Panel baseline is ~98%. Scores are on the withheld semi-private evaluation set (not the public eval set). Each model is shown at its best score across compute budgets; Human and Kaggle competition entries are excluded. Accuracy is the % of tasks solved.
Metric: Accuracy β higher is better Β· Source β