It can produce text that looks like reasoning. It can even produce text with mostly sound logic, but there is no internal experience or reasoning that occured there just the generation of language.
LLMs therefore tend to be very bad at tasks that involve meta cognition. I've yet to successfully convince one to tell me when it knows something.
w.r.t. this post : let's define 'reasoning' here, because there are definitions of 'reason' and 'reasoning' that would fit to a simple condition comparison let alone a massively complex llm.
as for the meta cognition bit : show me a human that can accurately affirm when they know something. These kind of things aren't binary, nor can they be.
https://rintintin.colorado.edu/~vancecd/phil201/Searle.pdf
People have been having these discussions since 1980 at least. I'm not going to bother rehashing the issue endlessly in shortform internet comments, but this paper exists if you're really interested in the subject.
https://www.anthropic.com/research/global-workspace
However, we don't /want/ them to have too much internal experience, because we want to know what they're thinking* for safety reasons.
* or, we want to be able to assume that the answer text is causally related to the thinking text
This is a near daily experience for me when using a coding harness. I will ask it for some favts about the environment, and it will continuously explore the environment until it exhausts reasonable exploration, or it finds the facts.