Maybe you can't determine that with certainty, but there may be statistical tools you can use to estimate the probably that some content came from one of the LLMs we know about based on their known writing styles?
Someone did something like that to identify HN authors (as in correlating similar writing styles between pseudonyms) a few years back, for example: https://news.ycombinator.com/item?id=33755016
Of course, LLM output can be tweaked to evade these, just like humans can alter their writing style or handwriting to better evade detection. But it's one approach.
Someone did something like that to identify HN authors (as in correlating similar writing styles between pseudonyms) a few years back, for example: https://news.ycombinator.com/item?id=33755016
Or a study applying similar analysis to LLMs: https://arxiv.org/pdf/2308.07305
Of course, LLM output can be tweaked to evade these, just like humans can alter their writing style or handwriting to better evade detection. But it's one approach.