ARC-AGI-2

What it measures

The harder static ARC successor: human-calibrated colored-grid abstraction tasks, now pressured by 2026 frontier systems.

Primary metric

task success rate on the public evaluation split (%)

Judge model

not judged by a model

Human baseline

100The official ARC Prize leaderboard lists a Human Panel score of 100% on the ARC-AGI-2 semi-private axis. The arXiv paper also reports 66% across all human evaluations and attempts, 75% aggregated by task, and 100% solvability by at least two independent non-expert human testers.

Languages

Language-neutral

Health

The public evaluation set has 120 tasks, so one solved task moves the score by 0.83 points. The official leaderboard uses the semi-private axis, while Kaggle competitions use private evaluation. Identify the split, attempt budget, and cost budget before comparing scores.

Status evidence

ARC-AGI-2 remains the current static colored-grid ARC benchmark, but the official ARC Prize leaderboard generated on 2026-07-23 lists GPT-5.6 Sol Max at 92.5% and GPT-5.6 Sol xHigh at 90.0% on the ARC-AGI-2 semi-private axis. Because competition/private-set validation and efficiency constraints still matter, this page marks it nearing saturation rather than fully saturated.

Saturated since

not saturated

Refresh cycle

static

Test set public

yes

ARC-AGI-2 keeps public training and evaluation data for open research, but adds semi-private and fully-private test sets for lower-leakage leaderboard and competition use. The public evaluation split is still public, so repeated tuning against it should be treated as contamination.

History & lineage

Hand-maintained, not part of the benchwiki record above — each line cites the paper or leaderboard it comes from.

1. 2019-11ARC-AGI-1 introduces static colored-grid abstraction tasks.
2. 2025-03ARC-AGI-2 keeps the static grid format but raises difficulty and improves human calibration and private-set controls.
3. 2026-04ARC-AGI-3 appears as arXiv:2603.24621v2, introducing interactive turn-based environments and RHAE scoring.
4. 2026-07The official leaderboard generated on 2026-07-23 lists GPT-5.6 Sol (Max) at 7.78% on the ARC-AGI-3 semi-private axis, with substantially higher cost than static ARC runs.

Further reading

• ARC-AGI-3 overview
• ARC-AGI-3 paper
• ARC-AGI-3 HTML paper
• ARC Prize verified leaderboard
• ARC-AGI-2 paper

Models scored on this benchmark

The reverse lookup, which is this site’s addition: every model here with a score on this benchmark. Independent measurements and vendor-reported numbers are kept apart rather than interleaved, because they are different claims.

Trajectory

Best score measured on this site

As benchwiki records it

Where results are tracked

Leaderboards benchwiki lists for this benchmark. These are links out, not sources this site ingests — no score below comes from any of them.

• ARC Prize leaderboardofficial
• ARC Prize 2025 competitionofficial