The AI buildout needs more capital than backstops can cover.

A $500 billion financing structure for AI infrastructure needs 240 GW of compute capacity, but NVIDIA's balance sheet can only backstop 46 GW. The proposal uses tranched debt with equity losses cascading upward, letting different investors absorb different risk levels, since traditional lenders and guarantees can't cover the full buildout.
And this is the kind of the most interesting one is a $500 billion capital partnership because this gets into how can we actually, you know, to your point, right? You talked about lenders as one commodity, but it's actually very different. There's bank lenders, insurance lenders. They don't want to take a lot of risks. You've got private equity. They want to take a lot of risks. You got private credit right in the middle.
They all syndicate into these things as well, right?
Well, it's about creating different products for different types of investors. So the $500 billion capital partnership, this is what we think it could look like. And what you do is you can have an AI lab. They don't have to be IG, but what you do is you tranche the risk. So you have equity and then you've got a B piece, which, which doesn't have any residual value guarantee. And then you have an A1, A2, you can put one senior to the other. And then NVIDIA is giving a 25% residual value guarantee in this $500 billion partnership. Maybe you can attach this 25% to this tranche or this tranche. But because let's say there are losses in this program, you know, in this business, then the equity will take the loss first, then the B piece. And then part of the A2. And so it will have to go all the way down to this. The loss has to be so severe to affect the senior tranche, which is how you can create different risk profiles and open up the market. But anyway, all this depends, right, on NVIDIA having the capacity to do this. So we analyzed the balance sheet, you know, and, you know, if you kind of love talking about this, you know, this is all we're going to do. But, you know, here's the kind of conclusion of this, Jordan, right? They, we think they have the capacity. This is not our forecast, but we think they have the capacity to support up to 46 gigawatts of capacity. We haven't done it for the hyperscalers yet, but that's still not enough. There's 240 gigawatts that's going to come in. And so what I'm saying here is, is the lending market has to evolve to take risks outside of backstops. And that's what, you know, we're all about understanding that question. And it's, it's really the biggest question of our time, to be honest, which is why we're starting an entire group around this question.
More from Dylan

"It's like a zombie apocalypse, but you don't know how many waves of zombies are coming."

Open-source models are already taking the easier tasks. The bull case for frontier labs rests on one

A $200 AI subscription can be worth $12,000 in tokens. Which plan delivers it is not close.

Ep. 036 - Anthropic Subscriptions Beat OpenAI 5x, Depending on Your Workload (Tokenomics)

Ep. 035 - Tech DD’s, Performance Projections, Supply Chain, Investment Thesis (Consulting)

Ep. 034 - The Fight for Fast Tokens, TPU v7, Vera Rubin, and Engrams (AI Supply Chain, InferenceX)




