Only for well defined tasks. There's not really a practical upper bound. We will keep throwing more complex tasks at it to the extent that it can handle them. Like if you just need fancy OCR, then a specific model will probably suffice, but there will be an appetite for human- or superhuman-level intelligence that never gets tired and has no rights.
SaaS and legal market caps have already contracted a multiple of the combined OpenAI + Anthropic valuations just based on the _threat_ of what they may be able to accomplish.
They'll have the data + knowledge edge over open alternatives and be able to implement + deploy (see the story about Anthropic employees being at GS for 6 months already[0])
[0] https://www.cnbc.com/2026/02/06/anthropic-goldman-sachs-ai-m...
+ r&d costs
Of course, if one does not "pay" for investment, benefits are easily made ..
But project out forwards.
- What happens when Google builds a similar model? Or even Meta, as far behind as they are? They have more than Anthropic in cash flow to pour into these models.
- What happens when OSS is "enough" for most cases? Why would anyone pay 60% margins on inference?
What is Anthropic's moat? The UX is nice, but it can be copied. And other companies will have similarly intelligent models eventually. Margins will then be a race to the bottom, and the real winners will be GPU infra.
Others are made of different stuff, and are going to go right back to work, even though they could go off to a beach for the rest of forever somewhere.
Doesn't this require their private market valuations to go well into the trillions?
You MUST accrue the lifetime value of the assets against the capital expense (R&D in this case) to determine the answer to this question.
The company (until this announcement) had raised $17B and has a $14B revenue rate with 60% operating margin.
It is only negative on margin if you assume the prior 14B (e.g. Claude 4.6 plus whatever’s unreleased) will have no value in 24 months. In that case, well, they probably wasted money training.
If you think their growth rate will continue, then you must only believe the models have a useful 9 months or so life before they are break even.
Anthropic is, according to Dario, profitable on every model <<—- they have trained if you consider them individually. You would do best to think “will this pattern continue?”