Inside the NVIDIA Rubin Order Rush — AI Datacenter Capex: Bubble or Inevitable?

NVIDIA Rubin is shipping, and hyperscaler order books are exploding. Microsoft, Google, Meta, Amazon, OpenAI, and xAI placed a combined ~$30B+ in one quarter, per reporting. Let's lay out the Blackwell delta, the power constraint, and whether this is a bubble.

Rubin and Rubin Ultra at a glance

• Rubin GPU: 288GB HBM4, 2.5x training / 3.3x inference vs Blackwell
• Rubin Ultra: 4-die package, 1TB HBM4 per unit, 100 PFLOPS (FP4) inference
• NVL576 rack: 72×Rubin Ultra → 4.6TB GPU memory per rack
• Power: 150kW per rack (up from Blackwell NVL72's 120kW)

A single rack burns the power of 200 apartments. A hyperscale building approaches a nuclear plant unit's output.

Order book

Rough order ranges (sourced):

• Microsoft: ~$20B/year (Azure/OpenAI)
• Google: ~$10B alongside in-house TPU v6
• Meta: ~$8B (Llama 4/5 training + Reality Labs)
• xAI: ~$6B (Memphis Supercluster expansion)
• OpenAI: ~$10B via the Stargate project

Quarterly total >$30B isn't a stretch.

Power and cooling become the bottleneck

Rubin's real constraint isn't GPU supply — it's power and cooling.

• US datacenter approvals routinely take 3 years
• Ireland, Netherlands, Singapore have paused new permits
• In Japan, Tokyo Bay and Inzai are at capacity, shifting to Hokkaido/Tohoku
• Liquid cooling gives way to immersion; facility costs jump

Jensen Huang said it plainly: "Power is the new currency of AI." Amazon, Microsoft, and Google are now investing in small modular reactors (SMRs).

On the bubble debate

Silicon Valley is increasingly split — "Rubin orders are peak bubble" / "demand is real." Real risks:

• LLM improvement curves plateauing would crater training GPU demand
• Inference moves to dedicated ASICs (Groq, Cerebras, Etched)
• China's domestic semi self-sufficiency could cut 30% of global demand

But all of these going wrong simultaneously is a low-probability scenario. My base case is "correction in 2027–28 after over-investment" — similar to post-dot-com. Survivors absorb cheap infrastructure.

What this means in Japan

• SoftBank, KDDI, Rakuten, Sakura Internet's GPU cloud businesses may be sitting on excess capacity by 2028. Long-term anchor customers locked in now matters
• Enterprise AI adoption stays "rent someone else's cloud" — buying Rubin doesn't make sense
• Semi equipment and materials (Tokyo Electron, SCREEN, SUMCO, Shin-Etsu) stay in tailwind through 2028

Related

• Geopolitics of TSMC's 1nm era
• The AI datacenter backlash