aiaimodel.cards
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ARC-AGI-1

Abstract visual reasoning puzzles that test learning new rules from a few examples.

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  1. 1Claude Fable 5.1 · Anthropic
    97.5%
  2. 2Claude Opus 5 · Anthropicbest value
    97.5%
  3. 3Claude Opus 4.7 · Anthropicbest value
    92.0%

“Best value”: no other model here reports a higher score at a lower cost for your workload. Scores are self-reported by each maker with different settings, so treat close calls as ties.

How each maker reported it

  • Claude Fable 5.1 Table 8.1.A, p.167

    Fable 5.1 and Mythos 5.1 share weights, so column 0 covers both (likewise Fable 5 / Mythos 5). Claude results use adaptive thinking at max effort, averaged over five trials. Terminal-Bench 4.0 values are from §8.6, p.171 (Mythos 5.1: 60.9%; GPT-5.6 Sol from the public leaderboard). Competitor figures come from the developers' own published results or leaderboards.

  • Claude Opus 5 Table 8.1.A, p.148–149

    Claude Opus 5 results use adaptive thinking at max effort, averaged over five trials (ARC-AGI-3 at high effort). GPT-5.6 Sol's FrontierBench figure uses Codex and its ARC-AGI-1 figure is at xhigh. The Fable 5 HealthBench Professional figure carries a footnote reading "Mythos 5". Competitor figures come from the developers' own published results or leaderboards.

  • Claude Opus 4.7 Table 8.1.A, p.191–192

    Opus 4.7 uses adaptive thinking at max effort with default sampling, averaged over 5 trials (Terminal-Bench 2.0 with thinking disabled; Finance Agent at high effort). Competitor figures come from the developers' own published cards or leaderboards.

Only each model's own maker's number is shown; scores a maker reports for rival models are left out.