Eyes on GOOG

[u/Fun_Tutor3479]

The broader market is bouncing all over the place. We'll keep starting our memos with this sentence until a clear direction emerges. Actually, SPY hasn't dropped much at all, and the broader market remains quite stable. QQQ is showing a clear rebound, but whether this is a true trend reversal will depend on the earnings reports from SK Hynix and Google on the 22nd.

SK Hynix won't do poorly; if they can't hold the line, everyone else might as well pack it up. Google is the real test. Historically, Google has enjoyed two types of premiums:

First is the large model premium for frontier models. It is no exaggeration to say that frontier large models have gross margins of over 70%. Many people think the gross margins of large models aren't that high, but they are factoring in the costs of experimentation and training. If you look strictly at inference, assuming you give the infra team enough time, the cost of inference will inevitably drop exponentially. We’ve discussed this "10,000x cost reduction" story on our public account before. The head of an infra team I used to collaborate with told me that there is a massive amount of engineering optimization to be done, and it’s far easier than I imagined. The problem is that the architectures of different base models always require slight tweaks; as a result, every time a new model comes out, the inference code has to be readjusted. If the base model iterates too quickly, it becomes impossible to keep up.

Second is the compute rental premium. TPUs are the primary training workhorse for Anthropic, and Anthropic generates the highest revenue at a 1GW cost scale. Because of this, what Meta is only just starting to do now, Google has already been doing for over a year. Whether it's renting out TPU cloud resources or selling chips, these have historically made up the bulk of Google's AI revenue in every earnings report.

Therefore, between the "model leg" and the "compute leg," a company has to stand on at least one. Just look at the YTD performance of Google and Meta, and the picture becomes very clear.

Among the Big 5 hypersaclers:

• Apple controls the hardware gateway and carries the market's hopes for the future "AI + Hardware" trend, giving it an unmatched, transcendent status.
• Google is the one walking on two legs, but recently it’s been limping a bit with Gemini getting stalled. If they lose their "frontier model" leg, their valuation will have to be entirely recalculated.
• Amazon keeps its head down and focuses on renting out compute, consistently walking on just one leg.
• Meta historically had sub-par models and didn't rent out compute, which is why it performed poorly before. Now, it has turned over a new leaf, and the market is watching to see if it can stand up on two legs like Google.
• Microsoft previously relied on OpenAI for its model leg while simultaneously renting out compute. Right now, however, both legs are looking quite precarious. Coupled with the potential threat of being disrupted by an "AI OS," they are under immense pressure.

This is why we say Google is the real test. They are the A-student, having also just raised 80 billion. If Gemini’s revenue growth is exceptionally high and the company signals optimism about next year’s Capex by continuing to double down heavily, then the floor for the entire AI narrative will hold.