The Architecture of Constraint: Three Bottlenecks Money Cannot Solve

NVIDIA’s ability to ship GPUs depends on three critical chokepoints, none of which it controls. Understanding these constraints explains why money alone cannot solve the AI compute shortage.

Bottleneck 1: High Bandwidth Memory (HBM)

The HBM Triopoly:

• SK Hynix — 50% market share
• Samsung — 40% market share
• Micron — 10% market share

“We have sold out our entire 2026 HBM supply.” — SK Hynix CFO

Stargate Demand: 900K wafers/month by 2029 = 40% of global DRAM output

Bottleneck 2: CoWoS Packaging

TSMC Monopoly: The only advanced packaging provider at scale

• Capacity sold out through 2025-2026
• Growth: 75K → 95K → 135K wafers/month (2025-2027)
• NVIDIA controls 70%+ of capacity

Bottleneck 3: Energy Infrastructure

Grid Saturation:

• 7-year wait for grid interconnection
• Power demand: 61.8 GW → 134.4 GW (2025-2030)
• $1 Trillion utility CapEx 2025-2029

The Layer 1 Insight

Physical constraints define AI’s ceiling. HBM, CoWoS, and advanced logic form interdependent bottlenecks. NVIDIA’s supply agreements create years-long structural advantage.

This is part of a comprehensive analysis. Read the full analysis on The Business Engineer.