This is a good/fast/cheap tradeoff, but in the form of accurate/precise/creative, or something in that ballpark anyway.

You can constrain the AI to be more accurate by having it a) equivocate (lose precision) or b) turning the temperature to effectively zero, thus losing "intelligence" and creativity.

There's no such thing as a free lunch. The models perform best out of the box, and everything you add into context makes them perform worse generally, but more likely to do what you want. Every token is a burden, but without those constraints the generation won't do anything.

So by that standard, hallucination is something completely core - you can't get rid of it without losing what makes them useful. You can make different tradeoffs, or use a very smart model in a way that is completely locked down (or adversarially verified, same result) which results in far more tokens used than if you just let the model do it's thing and validated for hallucination independently, outside of the generation loop.