I cannot judge his research output at Meta but he failed pretty bad at the LLM race. Since so many other organizations succeeded at creating open source models of far higher quality at much lower cost, it would be instructive to understand what exactly went wrong there.
Kind of hilarious to me to consider him "failing" with LLMs. Given his remit was a research time horizon of 8-10 years, and the fact that he's gone on record saying that he expects the technology will stall out in the time horizon, it seems he can only take Ws and ties. Indirect influence on open-sourcing the models to propel research forward (which is pretty important for a chief scientist) which added benefit for Meta's other products.
And as a poker player, I can say that this game is much more challenging for computers than chess, writing a program that can play poker really well and efficiently is an unsolved problem.