14 H100 GPUs per user that they serve

Not per user, but probably decent rough estimate to that per vibecoding dev that is continually running agents 8+ hours/day. Some people's "workflows" involve running multiple parallel agents sometimes or even a significant portion of the time (using the git worktree feature), so I think that's probably a decent rough estimate. I imagine the limit would be serving 10 of these types of "devs." Of course, there's batching and stuff that can be done, but I think it still slows everybody else down near linearly. H100s aren't the only accelerators used for inference; I just chose it as an example. Google has ~5 million H100 equivalent accelerators, Microsoft has 3.5 million, and Amazon has 2.5 million (https://www.networkworld.com/article/4156949/google-owns-the-most-ai-compute-and-it-built-it-its-way.html).