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The scoring doesn't tell you how many levels the models completed, but how efficiently they completed them compared to humans. It uses squared efficiency, meaning if a human took 10 steps to solve it and the model 100 steps then the model gets a score of 1% ((10/100)^2).
Edit: Also, "humans" means at least 6 out of 10 volunteers must have been able to solve some puzzle for it to be included, not 10 out of 10. Thus the test, even ignoring the previous caveat, is comparing the AI not against humans but against 40th percentile of humans. bottom of page 15
Indeed, there's almost nothing scientific about the scoring system of ARC-AGI-3; the test itself is kinda neat, and still highlights something that smart humans do (somewhat) better than the best LLMs, but it's dropped any pretense at being an actual measure of "general intelligence", and frankly they deserve to be ridiculed for the sensationalist scores.
Why is completion speed the main factor? Why is the difference squared? Speedruns are not how we define intelligence. If the squirrel in your backyard can solve sudokus, but a top-10th-percentile-of-self-selected-sudoku-solvers human can do it faster, you don't laugh and say "ha ha, this squirrel is so dumb". Also note that the test cuts the model off if it takes 5x longer than the smart human, and later questions build on earlier ones, so if a model goes slowly once it's handicapped for the rest of the test. (Again, this is probably completely intentional, to help deflate scores further.) They used a majority-of-self-selected-humans-can-solve-this metric for puzzle inclusion but not for the scoring. Why? Pure showmanship.
I suspect that average humans who take the test would probably also get a very low score! The old tests and metrics (including ARC-AGI-2) were useful because they showed something that humans genuinely find easy, but LLMs fail at. Those metrics have almost reached saturation, so I guess now we're switching to puzzles that some humans can solve but LLMs ... uh ... solve a bit slower. Ok?
But hey, the "0.5%" number does help low-information AI skeptics like OP point and laugh, so it's another "win" for AI journalism.
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Note the "human baseline" isn't based on the human average, it's based on the "second-best first-run human playthrough" among the 10 people tested for each individual puzzle.
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Many of the puzzles have a limited amount of steps in which they can be completed. The puzzle it loads by default, for example, has an energy bar that is depleted with each move you make. You have to be able to actually reason about the rules of the game and the objects within the levels to be able to complete them at all, you only have maybe a 10% buffer of energy for mistakes and/or choosing a less efficient route/method to solve them.
Correct, that's why I suggested people in the 100-110 iq range (roughly) or higher would likely be able to solve them.
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