The bill for frontier AI is now measured in gigawatts
Frontier AI spending has shifted from clever algorithms to power and concrete. A single gigawatt data center now costs about 30 billion dollars to build.
7 stories tagged compute.
Frontier AI spending has shifted from clever algorithms to power and concrete. A single gigawatt data center now costs about 30 billion dollars to build.
AI chip performance per dollar improves about 37 percent a year, yet each new flagship costs more upfront. The GB300 delivers 24 times the value of a P100 at nine times the price.
The United States holds about 75 percent of global GPU cluster performance. That concentration shapes pricing, latency, and policy for everyone building elsewhere.
Training compute for frontier models has grown about 5 times a year since 2020. The scatter looks clean, but every data point sits to the left of the real question.
Frontier training costs climb about 3.5 times a year while algorithms get 3 times more efficient. The two trends are racing, and the gap decides who can still compete.
The largest AI data center already rivals 700,000 H100 chips, and a 5-million-equivalent campus is due by 2027. Power and concrete, not chips, set the new pace.
The installed stock of AI chips is growing 3.4 times a year, doubling every seven months. The capacity question has quietly shifted from chips to power and buildings.