LLMs are accurate with everything you don't know but are factually incorrect with things you are an expert in is a common comment for a reason.
It reminds me of someone who reads a newspaper article about a topic they know and say its most incorrect but then reading the rest of the paper and accepting those articles as fact.
That being said, I do agree with your general point. These tools are useful for exploring topics and answers, we just need to stay realistic about the current accuracy and bias (eager to agree).
"do llms give wrong information often?"
"Yes. Large language models produce incorrect information at a non-trivial rate, and the rate is highly task-dependent."
But wait, it could be lying and they actually don't give false information often! But if that were the case, it would then verify they give false information at a non trivial rate because I don't ask it that much stuff.