LLMs get things wrong due to different factors than humans (humans lose focus, LLMs have randomness applied when sampling their responses to improve results). But clearly we have to choose a goal somewhat below 100% if we want a test that doesn't conclude that humans are incapable of reasoning.
There's deeper philosophical questions about what reasoning actually _is_, and LLMs have made those sharper, because they've shown it's clearly possible for a complex statistical model to generate words that look like reasoning, but the question is whether there's a difference between what they're doing and what humans are doing, and evidence that they're _not_ reasoning - evidence that they're just generating words in specific orders - weighs heavily against them.
But more importantly, if you want to show that LLMs can't reason you obviously have to use a test that when applied to humans would show that humans can reason. Otherwise your test isn't testing reasoning but something more strict.
You can make mistakes and still reason. Very often people given the same premises will disagree in thier reasoning as we are doing right here.
Apple AI researchers released a paper on it. They say no.