I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.
> It's clear that the human language network is not like LLM in that sense.
Is it though? If rhythm or tone changes meaning, then just add symbols for rhythm and tone to LLM input and train it. You'll get not just words out that differ based on those additional symbols wrapping words, but you'll also get the rhythm and tone symbols in the output.
However ... language production and perception are quite separated in our heads. There's basically no parallel to LLMs. Note that the article doesn't give any, and is extremely vague about the biological underpinnings of language.