Public research, reactions and friendly banter with original sources. Scores belong to each post's date.
ARC Prize announced a new 2026 ARC-AGI-2 Kaggle high of 88.06% by Tufa Labs and said a $150,000 bonus would be split among teams scoring above 85%.
A public-board threshold announcement and major standings lead; the post does not establish a final private score.
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Linked releaseARC Prize announced Yi-Chia Chen at 59.17% on the 2026 ARC-AGI-3 Kaggle board, taking the lead over Tufa Labs.
A new public-board leader is the strongest ARC-3 standings lead; verify the current board before an edition.
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Linked releasePuget asked ARC Prize whether the 85% bonus threshold refers to the public or private leaderboard; no organizer answer was visible in the checked thread.
Flags a reporting question; avoid presenting the public score as the final prize result.
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Linked releaseKnoop said the 85% Grand Prize bonus threshold had been reached on Kaggle and called 2026 the final ARC-AGI-2 Kaggle year.
Provides organizer context for the Tufa Labs result; his expectation about future open artifacts is not yet a release.
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Linked releaseChollet reacted to ARC Prize’s Tufa Labs ARC-2 announcement by saying Kaggle scores are getting very good.
A founder reaction adds a measured voice to the organizer’s score announcement.
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Linked releaseARC Prize announced Stephen Wolfram as a keynote speaker for its 2026 Research Summit.
A current event-program lead for the meeting digest.
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Linked releaseOuellette released an ARC-AGI-3-style training-data framework with 429 playable games, solvers and demonstration generators; he said 37 games still lacked solvers. The linked repository says it combines augmented public ARC demos and other game sources.
A concrete research resource; its author describes training material, not a measured Kaggle-score gain or coverage of private games.
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Linked releaseARC Prize published verified Grok 4.7 scores: 1.8% on ARC-AGI-3 with its standard harness, 10.0% with a provider adapter, and 61.4% on ARC-AGI-2.
The harness distinction matters when comparing model scores; the post reports organizer verification.
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ARC Prize published verified DeepSeek V4.1 Flash scores of 72.9% on ARC-AGI-2 and 94.5% on ARC-AGI-1, with stated per-task costs.
A dated organizer model verification relevant to ARC-2 comparisons.
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Kamradt invited researchers to contact ARC Prize about red-teaming future ARC-AGI benchmarks and mentioned grants and credits as possible support.
A direct research-participation lead; it is an invitation, not a claim about any current contestant’s approach.
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Cole congratulated Tufa Labs on the ARC-2 result, calling it a momentous achievement.
A named competitor’s respectful reaction adds color without implying rivalry or shared methods.
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Linked releaseKamradt said he was excited Wolfram would join the ARC Prize Summit in two weeks, quoting the organizer’s announcement.
Confirms the organizer’s program announcement from the ARC Prize president.
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Linked releaseTufa Labs made a tongue-in-cheek post about a temporary setback and “overwhelming resources and compute”; the post included AI-marked imagery.
Competition banter only; the line is not evidence of the team’s actual budget, compute or methods.
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Kamradt shared images and called Ouellette’s release a “V3 inspired dataset.”
An organizer reaction to a community resource; the original release and repository hold the substantive details.
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