Compute Shortages & The Cloud, AI Chip Design & Synopsys, Memory & Micron

A number of readers mentioned that they found last week’s post in their spam folder, so if you’ve missed it, here’s a link to last week’s article:

Compute Shortages & The Cloud

The central theme in AI continues to be supply chain shortages everywhere we look—all the way from the fabs and their suppliers to the data center. UBS notes that TSMC is accelerating its A14 buildout:

“Based on recent industry feedback and our analysis, TSMC is further accelerating the build-out of its leading-edge capacity. Specifically, the new A14 node should start tool move-in first at its Fab 20 in Baoshan from H226, and we believe the expansion scheduled at Fab 25 in Central Taiwan Science Park is being pulled forward to support larger capacity scale in 2028 when the node enters mass production. We estimate TSMC may build 60kwpm A14 capacity by end of 2028, above N2’s 30-40kwpm installed capacity in same stage. Looking across TSMC’s competitors, Intel targets high-volume manufacturing of 14A in 2028 with PDK 1.0 release later this year. Samsung Foundry appears to be delaying mass production of SF1.4 to 2029 due to yield challenges. We raise TSMC’s capex in 2027/28E from US $80bn/95bn to US$90bn/105bn to factor in more meaningful expansion across N3/N2 and faster ramp of A14 underpinned by Cloud AI demand and steady migration of smartphone & PC.”

Shortages in AI compute allow anyone who actually has the compute to opportunistically raise prices and boost margins—just like the memory players have been doing when it comes to semis—and both neoclouds and SpaceX are now taking advantage of this. Deutsche’s overview shows how SpaceX has been raising prices on their compute deals—from $31M per MW on their first customer to $50M per MW and then $60M per MW for their next customers:

SpaceX is printing cash on these deals and neoclouds such as Nebius and CoreWeave are now running the same playbook. This led JP Morgan to upgrade CoreWeave:

“We are upgrading CoreWeave to Overweight from Neutral, led by the favorable pricing backdrop for compute given the strong demand backdrop as well as the incremental willingness of the company to lean into short-term contracts at premium pricing, which drives our revenue and margin forecasts higher in contrast to a lackluster share price performance dictated by investor concerns around capital intensity. The stronger pricing backdrop on account of a robust demand environment, which has strengthened through this year, is evident in the following drivers: 1) July pricing changes of 25% across SKUs; 2) frequent price increases across SKUs from peers like Nebius (not covered); 3) pricing for short-term compute contracts from some peer companies tracking almost 3x the pricing range for CoreWeave on longer-term contracts; 4) CoreWeave’s leverage of the opportunity evident in its recent press release highlighting contracts signed in F3Q at ~$40M/ MW; and 5) CoreWeave management highlighting that the robust pricing is already supporting 5-10 ppts of incremental contribution margins on contracts, relative to prior contracts, dispelling any concerns that the higher price is purely a pass-through of higher costs.”

It’s clear that there is currently a massive shortage in AI compute and that anyone who can make compute available can sell it at massive premiums. Last year, when we looked at neoclouds, the consensus was still that this capacity would be sold at a rate of around $10M per MW, which already would give a nice IRR. Currently, that capacity is being sold at $40-50M per MW by CoreWeave and Nebius, and even at $60M per MW by SpaceX.

Despite this improved revenue outlook, CoreWeave’s share price has gone nowhere, unlike Nebius which already has been selling capacity opportunistically to the highest bidder:

Truist shows how Nebius has been closing compute contracts with shorter durations vs CoreWeave (below). This makes the company a much stronger play on GPU pricing moving up, similar to SpaceX.

Another reason for CoreWeave’s underperformance is that the company is heavily relying on debt to finance its AI buildout. Nebius on the other hand has been relying more heavily on customer prepayments as well as dilutive equity offerings. While debt is attractive as it’s non-dilutive, the problem is that it’s also more risky, especially as interest rates are spiking due to the US-Iran conflict:

In the case of Nebius, 55% of capex is financed by customer prepayments, strongly reducing the risk. However, the advantage of CoreWeave’s strategy is that their debt financing has allowed them to close a massive backlog:

Overall, in the current environment, SpaceX and Nebius have the much better strategies. SpaceX raised $100 billion in its recent IPO, and can raise much more cash in the markets in the years ahead, to finance their AI buildout and train Grok. Nebius is similarly relying much less on debt to finance its cloud capex. And the big attraction is that both names have been selling capacity as it comes online to the highest bidders.

While CoreWeave has a huge backlog, all of this backlog is still at the old contract rates of $10M per MW. If the company brings more capacity online in the meantime, this can be sold at premium rates. However, this won’t be easy, as the company already has a massive debt load while interest rates are spiking. So, we think that it won’t be easy for CoreWeave to massively take advantage of the currently huge spreads when it comes to short term GPU capacity vs long term contracts.

Truist notes that also Nebius will likely have to raise substantial debt going forward to finance its buildout—obviously not great when interest rates are spiking.

So, if you’re bullish on AI compute capacity remaining in a shortage and GPU pricing continuing to move higher—which is a credible bull case given the huge demand for tokens combined with the NIMBY political backlash against data centers—the best play in our view is SpaceX. The company will be at a $100 billion ARR in the coming months already, has $100 billion in cash, is excellent at building data center capacity, and at current GPU rates they can get the payback in one year or so.

SpaceX trades at a massive premium compared to the neoclouds. However, SpaceX also has the extremely valuable crown jewels with Starlink and the launch businesses, while at the same time the company is competing at the frontier in AI with Grok. Grok is currently being trained on SpaceX’s internal data with the aim of making it the world’s best engineer. So, comparing SpaceX to the neoclouds isn’t really apples-to-apples.

A lower risk play on the above theme are the major hyperscaler clouds. While neoclouds mainly offer GPUs to power AI workloads, the major clouds offer a broad ecosystem of web services to run an entire business on.

Take ChatGPT for example—a neocloud can provide GPUs to purely power AI workloads, however, a major cloud can provide the entire infrastructure to run OpenAI’s business and the ChatGPT app on, including databases, analytics, observability, tons of CPUs, data centers around the world close to end users, etc.

As moving data out of these major clouds is both costly and slow, major clouds are able to price their GPUs at premiums as Truist’s analysis shows:

The big cloud players also have strong operating cash-flow generation to finance their AI buildouts, massively reducing the risk-profile. So, for investors looking for quality companies to get exposure to the growth in AI, we continue to see the major clouds as solid long term investments.

Valuations for these names remain attractive and so we have large positions in Amazon and Microsoft, with a smaller position in Google. We’ve recently also added to the two best clouds in China—Alibaba and Tencent—as these are ridiculously cheap in our view while these are actually very good businesses.

Next, we’ll discuss our findings for:

• Synopsys & AI Chip Design
• Memory & Micron

Synopsys & AI Chip Design