The problem with pattern matching of sequences and transformers as an architecture is that it's something they're explicitly designed to be good at with self attention. Translation is mainly matching patterns to equivalents in different languages, and continuing a piece of text is following a pattern that exists inside it. This is primarily why it's so hard to draw a line between what an LLM actually understands and what it just wings naturally through pattern memorization and why everything about them is so controversial.

Honestly I was really surprised that all models did so poorly on ARC in general thus far, since it really should be something they ought to be superhuman at from the get-go. Probably more of a problem that it's visual in concept than anything else.