Scoring for ARC-AGI-3 is constructed so that the median(-ish) human score is 100%, so this is not a superhuman result. However, the scaling is weird, since it's built from terms that look like (AI turns taken / median human turns) ^ 2, and it weights later levels higher than early levels. So it's not at all clear that 100% is twice as good as 50%.

Really though? I would believe something like this if a model could one shot every solution in the set. I don't pay much attention to these things and maybe this stuff is available but I would bet the session/reasoning transcript is absolutely horrendous from an intelligence standpoint.

At this point the only valid ARC-AGI benchmark left is to make up the next series of ARC-AGI benchmark puzzles that current models presumably can't handle.