Imagine a football team owner who doesn’t just buy the best players, but also buys the training facilities, the grass seed company, and the stadium. He isn’t just trying to win the league; he is owning the physical ground the game is played on. If you want to play in the league, you play in his stadium, on his grass, using his equipment.
The logic here isn’t about venture capital returns in the traditional sense. When Nvidia commits $40B to equity deals—as reported by TechCrunch AI—it looks less like a bet on the success of a few labs and more like a way to subsidize their own demand. It is a circular economy. Nvidia gives a startup millions in equity, and that startup immediately spends those millions on H100s and H200s.
It feels like a landlord who lends the tenant money to renovate the apartment. The landlord gets to claim the apartment is improving in value, but the cash just flowed from the landlord’s left pocket into his right pocket via the contractor. Why let a competitor get a foothold? By tying the equity to the ecosystem, Nvidia seems to be ensuring that no one is tempted to experiment with Groq or TPU clusters. (I suspect this is exactly the point).
This creates a tiered system that, in our view, effectively kills the idea of an independent AI lab. You are either part of the Nvidia-backed inner circle, where you get priority access to the latest silicon, or you are fighting for scraps on a public cloud with three-month waitlists for a decent cluster. The “Nvidia Tax” isn’t just the price of the GPU; it is the requirement that you enter their financial orbit to survive.
Does any developer actually believe a startup can remain neutral when their primary funding source also happens to be their sole hardware provider? It is a gated community where the only innovation allowed is the kind that requires more chips. We are seeing the nationalization of the AI industry, not by a government, but by a single corporate entity.
The real friction here is the sheer burn rate of these clusters. Running a frontier model isn’t just about the initial purchase; it is the power, the cooling, and the constant need to upgrade before the hardware becomes a paperweight. If these startups cannot find a way to generate actual revenue—not just “valuation” based on hype—the equity Nvidia holds becomes worthless.
Wait, maybe I’m overestimating the equity’s influence on research? Or maybe not—see below. If you control the capital and the compute, you control the direction of the research. The inefficiency is reaching a breaking point. By Q4, we will see the first wave of these equity-funded startups admitting that the cost of maintaining their H100 clusters has completely wiped out their operational margins.
The endgame here isn’t the equity; it’s the lock-in. Even if the startups fail, Nvidia has already moved the hardware into the wild and established a dependency that is nearly impossible to break. It is like a movie studio that funds a director’s first three films just to make sure they only use one specific brand of camera for the next decade.
The risk for the rest of the industry is that we are building a house of cards where the foundation is just more GPUs. If the revenue for these AI services doesn’t materialize, the whole stack collapses. But Nvidia doesn’t care if the startup fails in three years. By the time the bubble bursts, they have already sold the hardware and captured the market share.
It is a closed loop.
