I agree that LLMs are unlikely to be the final form for AGI, but what you are talking about is orthogonal to the IQ and for most cases general utility. It's like looking at a savant chained to a workstation reading tasks from a conveyor belt and saying that it will never have human level capabilities.
The model doesn't "know" how to generate tokens any more than it knows how to stop generating tokens. The sampler simply stops pulling values when it outputs a "stop token", which is a token the same way every other token is.
That is to say, it stops when it's statistically the most likely to.