[D] No free lunch theorem and LLMs

I have a question that can be stupid, but the ["No free lunch theorem"](https://w.wiki/4wSw) (Wolpert and Macready) states that for any model, any improved performance over one class of problems is offset by performance over another class. It also states that any two models are equivalent when their performance is averaged across all possible problems.

But what happens with LLMs? If the performance is averaged across all possible problems, the average will be higher than the rest of the models? …

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