The previous poster is correct for a very slightly different definition of the word "model". In context, I would even say their definition is the more correct one.
They are including the random sampler at the end of the LLM that chooses the next token. You are talking about up to, but not including, that point. But that just gives you a list of possible output tokens with values ("probabilities"), not a single choice. You can always just choose the best one, or you could add some randomness that does a weighted sample of the next token based on those values. From the user's perspective, that final sampling step is part of the overall black box that is running to give an output, and it's fair to define "the model" to include that final random step.