Probably more expensive than the subsidized costs.

Of course, but that's exactly the problem. OpenAI and Anthropic are preparing to IPO, so they must now demonstrate profits on inference. The time to take advantage of subsidized compute is in the past, and the subscription and per-token prices that they offer for inference are skyrocketing, overwhelming the budgets of companies that somehow did not see this bait-and-switch pricing coming.

per vibecoding dev

No lol. These same hardware requirements would apply to the cloud hosted models as well, so if that's how it worked, you're suggesting that Anthropic, OpenAI, Meta, and Google have purchased ~14 H100 GPUs per user that they serve???

That would be literally billions of GPUs, while it is estimated that in 2024, Google's AI division owned only 26,000 H100 GPUs and Meta owned the most H100 GPUs of any company at 350,000 units. These GPUs have very high throughput for inference and can serve many users, because that is exactly what they have been designed to do.

I’m not sure the cloud models use quantization

they absolutely do, yeah