OpenAI's deal structures highlight the market's perception of chip providers. NVIDIA commanded a direct investment from OpenAI to secure its chips (a premium). In contrast, AMD had to offer equity warrants to OpenAI to win its business (a discount), reflecting their relative negotiating power.

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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.

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.

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.

OpenAI's strategy to lease rather than buy NVIDIA GPUs is presented as a shrewd financial move. Given the rapid pace of innovation, the future economic value of today's chips is uncertain. Leasing transfers the risk of holding depreciating or obsolete assets to the hardware provider, maintaining capital flexibility.

SoftBank's strategy of selling its Nvidia stake to fund companies like OpenAI, whose main expense is buying Nvidia chips, creates a circular flow of capital within the AI ecosystem. This financial loop suggests that major investment funds are not just placing bets but actively fueling the valuation cycle between AI infrastructure and application layers.

Seemingly strange deals, like NVIDIA investing in companies that then buy its GPUs, serve a deep strategic purpose. It's not just financial engineering; it's a way to forge co-dependent alliances, secure its central role in the ecosystem, and effectively anoint winners in the AI arms race.

Instead of simple cash transactions, major AI deals are structured circularly. A chipmaker sells to a lab and effectively finances the purchase with stock warrants, betting that the deal announcement itself will inflate their market cap enough to cover the cost, creating a self-fulfilling financial loop.

NVIDIA's multi-billion dollar deals with AI labs like OpenAI and Anthropic are framed not just as financial investments, but as a form of R&D. By securing deep partnerships, NVIDIA gains invaluable proximity to its most advanced customers, allowing it to understand their future technological needs and ensure its hardware roadmap remains perfectly aligned with the industry's cutting edge.

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.

Beyond capital, Amazon's deal with OpenAI includes a crucial stipulation: OpenAI must use Amazon's proprietary Trainium AI chips. This forces adoption by a leading AI firm, providing a powerful proof point for Trainium as a viable competitor to Nvidia's market-dominant chips and creating a captive customer for Amazon's hardware.