All the models are pre-trained on the same one Internet.
The chance of different models hallucinating the same plausible sounding but incorrect building codes, medical diagnoses, etc, would be incredible unlikely, due to arch differences, training approaches, etc.
So when two concur in that manner, unless they're leaning heavily on the same poisoned datasets, there's a healthy chance the result is correct based on a preponderance of known data.