Uber's genius was getting their workers (sorry, 'contractors') to carry the capital costs of providing the fleet of vehicles they use.

Uber's in a business where you have some amount of network effect - you need both drivers available using your app, as well as customers hailing rides. Without a sufficient quantity of either, you can't really turn a profit.

LLM providers don't, really. As far as I can tell, their moat is the ability to train a model, and possessing the hardware to run it. Also, open-weight models provide a floor for model training. I think their big bet is that gathering user-data from interactions with the LLM will be so valuable that it results in substantially-better models, but I'm not sure that's the case.