That’s misunderstanding why these models are behind. A large part of why they’re behind is they aren’t able to do the reinforcement learning post-training steps that takes a pre-trained model and turns it into a frontier model like GPT 5 or Opus. Instead they do their best to recreate these models using distillation.

Fundamentally, you can never distill your way to being the teacher, so these approaches will not advance the frontier.

[edit, after thinking about it I think my phrasing is unfair. It's not necessarily that aren't able to do it, but they haven't yet shown that they are willing to do it.]

Chinese companies giving away expensive models for free is a symptom of the AI bubble, too. It's not a law of nature that they'll always be able to scrounge up the money for yet another training run.