Hallucination is fundamental to how LLMs work, and is mostly unrelated to how large or smart they are.

Everything that an LLM outputs is just a statistical language-based (no real grounding) prediction. Luckily with a model based on a large training set most common questions may elicit coherent responses from the training data, but you don't need to veer too far off into "questions less asked" territory to get responses based on training data mashups that amount to best guesses that are wrong, aka hallucinations. The unfortunate part of this is that as a user you may only catch this when asking a question about something you are already fairly knowledgeable about, then you give some pushback to the model and it cheerfully acknowledges "you're right - I made that up".