Google successfully trained its top model, Gemini 3 Pro, on its own TPUs, proving a viable alternative to NVIDIA's chips. However, because Google doesn't sell these TPUs, NVIDIA retains its monopoly pricing power over every other company in the market.

Google training its top model, Gemini 3 Pro, on its own TPUs demonstrates a viable alternative to NVIDIA's chips. However, because Google does not sell its TPUs, NVIDIA remains the only seller for every other company, effectively maintaining monopoly pricing power over the rest of the market.

Even if Google's TPU doesn't win significant market share, its existence as a viable alternative gives large customers like OpenAI critical leverage. The mere threat of switching to TPUs forces NVIDIA to offer more favorable terms, such as discounts or strategic equity investments, effectively capping its pricing power.

Anthropic's choice to purchase Google's TPUs via Broadcom, rather than directly or by designing its own chips, indicates a new phase in the AI hardware market. It highlights the rise of specialized manufacturers as key suppliers, creating a more complex and diversified hardware ecosystem beyond just Nvidia and the major AI labs.

Major AI labs aren't just evaluating Google's TPUs for technical merit; they are using the mere threat of adopting a viable alternative to extract significant concessions from Nvidia. This strategic leverage forces Nvidia to offer better pricing, priority access, or other favorable terms to maintain its market dominance.

This theory suggests Google's refusal to sell TPUs is a strategic move to maintain a high market price for AI inference. By allowing NVIDIA's expensive GPUs to set the benchmark, Google can profit from its own lower-cost TPU-based inference services on GCP.

The current AI landscape mirrors the historic Windows-Intel duopoly. OpenAI is the new Microsoft, controlling the user-facing software layer, while NVIDIA acts as the new Intel, dominating essential chip infrastructure. This parallel suggests a long-term power concentration is forming.

NVIDIA investing in startups that then buy its chips isn't a sign of a bubble but a rational competitive strategy. With Google bundling its TPUs with labs like Anthropic, NVIDIA must fund its own customer ecosystem to prevent being locked out of key accounts.

The narrative of endless demand for NVIDIA's high-end GPUs is flawed. It will be cracked by two forces: the shift of AI inference to on-device flash memory, reducing cloud reliance, and Google's ability to give away its increasingly powerful Gemini AI for free, undercutting the revenue models that fuel GPU demand.