It must have some internal models of some things, or else it wouldn’t be possible to consistently make coherent and mostly reasonable statements. But the fact that it has a reasonable model of things like grammar and conversation doesn’t imply that it has a good model of literally anything else, which is unlike a human for whom a basic set of cognitive skills is presumably transferable. Still, the success of LLMs in their actual language-modeling objective is a promising indication that it’s feasible for a ML model to learn complex abstractions.
if I copy a coherent sentence into my clipboard, my clipboard becomes capable of consistently making coherent statements
Yes, but that’s not how LLMs work. My statement depends heavily on the fact that a LLM like GPT is coaxed into coherence by unsupervised or semi-supervised training. That the training process works is the evidence of an internal model (of language/related concepts), not just the fact that something outputs coherent statements.