this post was submitted on 01 Jul 2026
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There is also a commercial aspect...
Bigger models are more expensive to train and serve..
Inference is currently insanely profitable if you have the hardware and the automation in place to support and serve it. At that point, it's a money printing machine, and you want to squeeze as much out of it as you can.
While training new models is extremely expensive, and serving them probably makes less profit (at least initially).
Having an external brake applied to the frontier labs is likely good for their bottom line, while increasing hype and directing customers' annoyance away from them.
It's likely only a temporary benefit, though. The dragon will catch up and apply more pressure, both on inference price and capabilities.
Can you cite your source on the claim that "inference is currently insanely profitable"? Everything I read suggests that openai and anthropic lose money on their plans.
I suspect it's profitable in the abstract - and their accountants would be bad at their jobs if they couldn't work out what utilisation rate you need to pay for the server runtime.
However how aggressively you amortise the cost of the training is the key, especially if you keep releasing new models every 6 months.