So, I have somewhat of a hot take. The big labs already are behind in two very important ways. What are the leading personal agents? Muse and Instinct. Not the big labs. I know they all launched dots, we'll see what happens, but Muse and Instinct are out in front leading in those two. When you look at specific applications, legal, finance, etc., the large language models are not the leading models. They're leading in general purpose, but when you start to get specific, they're not. When you look at it on a cost perspective, I can just go off of our data. If I process 500 million tokens on Claude, about $5,000. If we process the same 500 million tokens on our own model and our own hardware, it's 97% cheaper.
So, what I think is going to happen, and the fact that you and I don't agree on this actually is maybe the story of nobody really knows, right? Is you're going to start to see the large language models say, we got to pick our battles. Where do we go and fight to win? Because just having the general purpose model is actually not going to be as valuable because of the commoditization. And so, we should accelerate into specific use cases. Anthropic recently announced that they're going to go really heavy into bio and all the biotech stuff they want to go do. It feels like they think that is a massive opportunity if they can win there, that is trillions of dollars of value that they can create. OpenAI is saying dots and personal assistant. They've always been more of a consumer type company than an enterprise type company. And so, I don't think it's just like, hey, go all in on one specific use case, but it does feel like they're now realizing that the general purpose model can serve as a foundation, but the monetization of this and the sustainable moat is going to be in the applications.
And this goes back to the idea of in crypto, if you go back to 2017 or so, there used to be this thing called the fat protocol thesis. And the whole idea was like all the value accrues to the protocol layer. And I could be wrong on this, but I just continue to go back to the fat protocol thesis. The equivalent in the AI is like the fat model lab thesis, where all the value accrues to the model lab. What we found in crypto was there was definitely some value that accrues to the protocol, obviously Bitcoin, Ethereum, etc. But actually a ton of the value accrued to either the infrastructure underlying it in terms of miners and things like that, or the application layer. It feels like that's the same thing happening here, whereas the technology gets built out, we have tons of infrastructure that's making money, we have tons of applications that are yet to be built.
But I just find it really hard if like Anthropic and OpenAI just stayed as general for small providers. I just think that is like a cutthroat business. It's all like kind of a race to zero. Who can get the highest level intelligence for the cheapest cost? And so like what's the moat? What is the thing that defends against everybody else? But I don't know, maybe you think differently.
Again, they have a couple of decisions they need to make, but let's use Instinct as a Muse kind of proxy. What they very clearly are trying to do is they want to get as much transaction volume going through that personal agent as they can, and they think they can basically take a vig. And my guess is that they will go and start pressuring, whether it is the credit card companies, the payment processors, the merchants, etc., and say, 'Hey, I'll route stuff your way, but you got to give me something, right?' So, Muse or Instinct is going after a transaction-based revenue model. He has said that he would like to keep it free forever.
