https://techcrunch.com/2026/04/30/elon-musk-testifies-that-x...
While there is no moat as such, there is still a lot of expertise that goes into training SOTA models. There's a reason Google was willing to pay $2.7B just to get Noam Shazeer back to improve Gemini.
And good luck not staying behind when you can't monetize your gargantuan investments and have little incentives to make your models better as the world moves on.
They've been bringing out open weight models competitive with frontier models. How could they do that if they had a compute deficit?
I'm using GLM-5.2 daily for my own stuff, and during Chinese business hours, specially on their afternoon, it's a festival of rate limits.
For how long ? year ? how long till model that is year behind will be fine for 90%+ use cases ?
Much of the arms race for better LLMs exists to satisfy only the IT industry's needs.