I knew that there was no real moat from the very start, I mean, these things were close enough from the very start, how could it not result in a race to the bottom, especially as you can't really prevent distillation reliably?
A race to the bottom is where you lower standards, wages, or regulations to cut costs and attract business. What's actually happening is the opposite: a race to the top. Every model is trying to get better. Simultaneously they also happen to be getting more cost effective, but it's sort of a coincidence. Companies still require very good models, but they are not picking the "absolute best at any cost" anymore, because it turns out "any cost" isn't worth it.
I support and use open models as much as possible, but I'm not totally convinced that OAI or Anthropic have no moat, even as open models catch up to the frontier. Serving and inference are still hard problems when you're talking about a 2 trillion parameter model. Fine-tuning, if that remains a realistic need for businesses, is also a difficult infra problem at that scale. In the most bearish case, where there is no competitive advantage to using their models, big labs still have an advantage in this area.
Maybe there is some threshold where the price/quality math for your standard business tips in favor of smaller models and self-hosting the entire stack. I'd certainly love that.