To counter the competitive threat from Google's TPUs, NVIDIA avoids direct price cuts that would hurt its gross margins. Instead, it offers strategic equity investments to major customers like OpenAI, effectively providing a "partner discount" to secure their business and maintain its dominant market position.
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NVIDIA's deep investment in OpenAI is a strategic bet on its potential to become a dominant hyperscaler like Google or Meta. This reframes the relationship from a simple vendor-customer dynamic to a long-term partnership with immense financial upside, justifying the significant capital commitment.
By funding and backstopping CoreWeave, which exclusively uses its GPUs, NVIDIA establishes its hardware as the default for the AI cloud. This gives NVIDIA leverage over major customers like Microsoft and Amazon, who are developing their own chips. It makes switching to proprietary silicon more difficult, creating a competitive moat based on market structure, not just technology.
Nvidia's staggering revenue growth and 56% net profit margins are a direct cost to its largest customers (AWS, Google, OpenAI). This incentivizes them to form a defacto alliance to develop and adopt alternative chips to commoditize the accelerator market and reclaim those profits.
NVIDIA's financing of customers who buy its GPUs is a strategic move to accelerate the creation of AGI, their ultimate market. It also serves a defensive purpose: ensuring the massive capital expenditure cycle doesn't halt, as a market downturn could derail the entire AI infrastructure buildout that their business relies on.
NVIDIA's polite PR statement regarding Google's competing TPU chips contrasts sharply with the aggressive marketing of modern tech leaders. This 'old school' approach is seen as a weakness, suggesting their marketing 'war muscle' has atrophied from years of unchallenged dominance.
NVIDIA's vendor financing isn't a sign of bubble dynamics but a calculated strategy to build a controlled ecosystem, similar to Standard Oil. By funding partners who use its chips, NVIDIA prevents them from becoming competitors and counters the full-stack ambitions of rivals like Google, ensuring its central role in the AI supply chain.
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.
![Gavin Baker - Nvidia v. Google, Scaling Laws, and the Economics of AI - [Invest Like the Best, EP.451] thumbnail](https://megaphone.imgix.net/podcasts/d97fee14-d4d7-11f0-8951-8324b640c1c1/image/d3a8b5ecbf3957de5b91f278a191c9ff.jpg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress)
Jensen Huang counters accusations of inflating revenue by investing in customers. He clarifies the investment in OpenAI is a separate, opportunistic financial bet, while chip sales are driven by market demand and funded independently by OpenAI's own capital raising—not by NVIDIA's investment.
While competitors like OpenAI must buy GPUs from NVIDIA, Google trains its frontier AI models (like Gemini) on its own custom Tensor Processing Units (TPUs). This vertical integration gives Google a significant, often overlooked, strategic advantage in cost, efficiency, and long-term innovation in the AI race.
