My hypothesis is that a model fails to switch into a deep thinking mode (if it has it) and blurts whatever it got from all the internet data during autoregressive training. I tested it with alpha-blending example. Gemini 2.5 flash - fails, Gemini 2.5 pro - succeeds.

How presence/absence of a world model, er, blends into all this? I guess "having a consistent world model at all times" is an incorrect description of humans, too. We seem to have it because we have mechanisms to notice errors, correct errors, remember the results, and use the results when similar situations arise, while slowly updating intuitions about the world to incorporate changes.

The current models lack "remember/use/update" parts.