The economics of the GPU invert intuitive assumptions about where value lies: Memory matters more than silicon. Packaging matters more than processing. Software matters more than hardware. Systems matter more than components.
Memory > Silicon: HBM at 45% of production cost exceeds logic fabrication at 14%. Nvidia’s chip design brilliance is necessary but not sufficient; memory supply determines what can actually ship.
Packaging > Processing: Advanced packaging plus yield loss exceed the cost of the GPU dies themselves. TSMC’s CoWoS capacity, not its fab capacity, is the binding constraint.
Software > Hardware: CUDA’s 17-year ecosystem creates switching costs that protect margins even as competitors approach hardware parity. The moat is in the stack, not the chip.
Systems > Components: Nvidia’s strategic direction is toward selling complete solutions – racks, clouds, platforms – rather than individual chips. Margin compression at the component level is offset by deeper lock-in at the system level.
Why This Matters
The $6,400 chip that sells for $30,000-$40,000 embodies these dynamics. Nvidia captures extraordinary value not because silicon is expensive, but because it has assembled a position where memory suppliers, packaging providers, and software developers all depend on – and feed into – its platform.
Structural Implications
For the AI infrastructure buildout: supply constraints will persist, margins will remain elevated, and access to compute will determine competitive outcomes.
The companies that can secure hardware – through capital, relationships, or vertical integration – will lead. The others will wait.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
