The AI Infrastructure Bottleneck: Physics, Not Funding

The AI Infrastructure Bottleneck: Physics, Not Funding

The AI infrastructure buildout has entered a phase where Blackwell supply—not capital—is the primary constraint.

NVIDIA Blackwell Status

  • Sold Out Through Mid-2026: 3.6 million unit backlog from major cloud providers alone
  • Blackwell Dominance: GB200/B200 projected at 80%+ of NVIDIA’s high-end GPU shipments in 2025
  • GB300 “Blackwell Ultra”: Already in sampling/validation; 60,000 rack shipments projected for 2026
  • Price Points: GB200 systems at ~$3M per rack; 30x performance vs. H100 for LLM inference

The Constraint Cascade

Constraints have shifted from capital to physics:

Constraint Reality
Power OpenAI’s targets would consume electricity equivalent to India; xAI’s Memphis complex targeting 2GW
Memory (HBM) Shortages constraining chip production; may be more severe than GPU supply
Liquid Cooling GB200 NVL72 requires liquid cooling infrastructure; “liquid cooling gold rush” for specialized components

Stargate Status

Oracle has pushed ahead with massive infrastructure buildout on OpenAI’s behalf, borrowing heavily. The Abilene, Texas flagship facility became partially operational in 2025.

Total commitment: $500B — whether this materializes depends on continued funding velocity and power availability.

The Reality

AI scale is increasingly governed by physics, not funding. The constraint is now power, memory, and cooling infrastructure.


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