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 can afford to offer its LLM for free, creating immense pricing pressure on competitors like OpenAI. This strategy aims to eliminate competition by making their business models unprofitable, securing a monopoly for Google before it begins to monetize.

Google's latest AI model, Gemini 3, is perceived as so advanced that OpenAI's CEO privately warned staff to expect "rough vibes" and "temporary economic headwinds." This memo signals a significant competitive shift, acknowledging Google may have temporarily leapfrogged OpenAI in model development.

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.

Google's strategy may be to offer its powerful AI models for free or at a significant loss. As a trillion-dollar company, it can sustain these losses indefinitely, forcing smaller competitors like OpenAI into an "endless sea of red ink" until they collapse, thereby securing a market monopoly.

As competitors like Google's Gemini close the quality gap with ChatGPT, OpenAI loses its unique product advantage. This commoditization will force them to adopt advertising sooner than planned to sustain their massive operational costs and offer a competitive free product, despite claims of pausing such efforts.

OpenAI is now reacting to Google's advancements with Gemini 3, a complete reversal from three years ago. Google's strengths in infrastructure, proprietary chips, data, and financial stability are giving it a significant competitive edge, forcing OpenAI to delay initiatives and refocus on its core ChatGPT product.

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.

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.