I think the reason OpenAI and Anthropic stay ahead in revenues right now is because the models are improving too quickly to reliably compete with them on cost.
But, once model performance reaches a plateau -- they have to at some point, though perhaps years away -- that's when ability to operate compute infrastructure at scale becomes the secret sauce.
The big AI labs are likely safe until models stop improving fast enough to protect them from competition on cost.
This similar pattern has repeated in most technical booms prior to this.
When hard drive technology was improving fast enough that old hard drives were quickly obsolete, IBM could maintain good margins making hard drives. But once hard drives got good enough and advances were slow enough that innovation was not the only factor considered by drive purchasers, commodity hard drives started to take over and IBM had to exit those businesses.
The same is likely to happen once model improvement slows.