MTSS48

We think tighter GPU financing is more likely to support rents than create a compute glut, because it slows new deployments while demand remains tight. (1/3)🧵

One update on the SpaceX GPU lease I walked through last week. Fitch looked at the $40B commitment and left SpaceX at BBB+, because that compute was already in its forecast. It's treating the deal like any other equipment lease. The numbers underneath are the part that got me. SpaceX had 1.7 GW of nameplate compute at the end of September, up from 0.6 GW a year earlier. Fitch's rating case assumes an average of 5 GW next year and 9.5 GW in 2028. When a ratings agency models a near 6x jump in compute in about two years and keeps the rating where it was, I think the question of whether AI compute is financeable is settled. The next one is how fast everyone else copies the structure

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Anthropic spent $5.0B on short-term compute in Q3 alone. That's the line in the new S-1 I keep coming back to. Anthropic books most of its compute on multi-year deals, 12 to 18 months before it's available. When demand runs past that plan, it buys short-term capacity, and that capacity costs significantly more. So in the quarter revenue hit $17.0B, demand ran far enough past what they'd booked that they paid up for $5.0B of extra compute. Along with a $2.0B non-cash charge, that's what swung them to a $567M operating loss after a $974M operating profit in Q2. And it's going to keep happening. They expect to use more short-term compute in the near term. The bears will call this a margin problem. To me it's the clearest demand signal in the whole filing. It also tells you where the next dollar goes. The biggest buyers of compute are already running past their long-term plans, and every provider with GPUs live today is part of the answer

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The neocloud boom is the most exciting thing happening in AI infrastructure right now, and it's also where the gap between talking and building is widest Every week I see another team announce they're "becoming a cloud". Some raised for a different idea and found that GPU capacity is the thing customers are actually paying for. Rental rates keep moving up, demand keeps outrunning supply and the capital is there, so it makes sense that people are jumping in What a lot of new entrants learn the hard way is that the business barely lives in the GPUs. You can wire money for hardware in an afternoon. Then you need power that's actually contracted, a site with the right cooling, networking that holds up under real training loads, and a crew that can get all of it live on the exact date you promised your customer That ready for service date is everything. A customer who signed for capacity in March has a model to train, a product to ship and their own investors to answer to. If you slip by two months, you've pushed their whole roadmap back So the providers who win this cycle look a bit boring from the outside. They've brought clusters online before. They know the local electrician by name. They plan for the transformer arriving late and the permit taking longer than it should. They treat a delivery date like a promise to someone else's business That's also what lenders and customers will pay up for. Plenty of buyers want to work with smaller and more flexible providers because the big clouds can't always give them the capacity, the timing or the price they need. That demand is real and it keeps growing. What they need is confidence that the capacity will actually show up The long tail of compute providers is here to stay and it's healthy for the whole market. Over the next couple of years the ones who execute will pull way ahead, and the teams who can bring a cluster online on time, every time, are going to be worth their weight in gold At Aethir we spend a lot of time on exactly this, because getting the compute to show up is the whole job If you're building in this space, go hire the people who've done it before. They're the scarcest resource in AI right now