Nobody said that nature is optimal. Wheels are trivial, however not present in biology. Nature creates tentacles, not jet engines, nuclear energy etc.
Majority of human brain computation is spent on things that are simply not necessary for computer models (how to wiggle limbs, mouth, eyes etc).
Current LLM are impressive, but we know they can be much more efficient - we're using very low quality training data, we don't use any methods to question training input/evaluate it against current knowledge etc. Our current language models are based on reciting/memorization/force-feeding, not true learning.
Computer models have massive underlying advantage of working on CPU/GPUs where they can be modeled, cloned, retrained, have binary accuracy, can integrate with specialized code instantly, have access to massive memory storage, they are insanely fast and precise etc.
Looking at it from first principles, there is no reason to think that near optimal runtime should not be more efficient than human brain on currently available computers.
We don't need to simulate full brain just like we didn't have to create super fancy legs to go to the Moon.