Jason, you talked about summarizing a

document. May take 20,000 cheap tokens

to do. Of course, shoot that to a

lagging model or an open-source model.

But if you're talking about replacing a

software engineer for 2 hours, that may

take 2 million expensive tokens. And the

consequence of using something that's

95% as good is really high,

right? Because you have a long-running

task, and if the task breaks early, or

it breaks in the middle, or breaks at

the end, there's a huge cost to that. So

>> You still pay

>> the tokens, right? You And back to this

analogy I was using, you're pulling the

slot machine and you lose.

>> And the time and the compute. So, if an

AI agent is replacing a $200 an hour

consultant, right? Take that as an

example. So, three consulting firms,

they're competing, they need the

smartest consultant. If they're charging

200 bucks an hour, the difference

between spending three bucks on a cheap

model or 15 bucks on an expensive model

to replace a $200 an hour consultant,

it's just irrelevant. That inference

cost difference is irrelevant. If you're

getting something that's bulletproof for

15 bucks, and so I think that's what

we're seeing play out. The best evidence

for all of this is just revenue growth.

I'm talking about what is Anthropic's

revenue growth compared to OpenAI,

compared to the open-source models.

Millions of independent actors are

choosing every single day. The

open-source companies are growing,

right?

>> Yeah.

>> But they're growing selling something

that is really, really cheap. And

there's room in every single market for

premium products, for mid-tier products,

and for commodity products. And I think

we see a lot of this token growth.

People are speculating that the

intelligence gap between that commodity

stuff and the frontier stuff is going to

collapse to the point that people won't

pay for the frontier stuff. There is no

evidence of that on the field today.