While competitors pay Nvidia's ~80% gross margins for GPUs, Google's custom TPUs have an estimated ~50% margin. In the AI era, where the cost to generate tokens is a primary business driver, this structural cost advantage could make Google the low-cost provider and ultimate winner in the long run.

Google's competitive advantage in AI is its vertical integration. By controlling the entire stack from custom TPUs and foundational models (Gemini) to IDEs (AI Studio) and user applications (Workspace), it creates a deeply integrated, cost-effective, and convenient ecosystem that is difficult to replicate.

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.

Unlike competitors who specialize, Google is the only company operating at scale across all four key layers of the AI stack. It has custom silicon (TPUs), a major cloud platform (GCP), a frontier foundational model (Gemini), and massive application distribution (Search, YouTube). This vertical integration is a unique strategic advantage in the AI race.

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.

As the current low-cost producer of AI tokens via its custom TPUs, Google's rational strategy is to operate at low or even negative margins. This "sucks the economic oxygen out of the AI ecosystem," making it difficult for capital-dependent competitors to justify their high costs and raise new funding rounds.

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.

AI company Anthropic's potential multi-billion dollar compute deal with Google over AWS is a major strategic indicator. It suggests AWS's AI infrastructure is falling behind, and losing a cornerstone AI customer like Anthropic could mean its entire AI strategy is 'cooked,' signaling a shift in the cloud platform wars.

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.