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This projects that there is demand to make AI training another 15-30X of compute beyond 1 million B200s. This would be 3 million Rubins, Ultrarubin chips or Dojo 3 or Dojo 4 chips in 2027. 3X more chips and chips that are perhaps 10X the compute.
Summary Timeline
Dec 31, 2025: 1 million GPUs, 1,641 MW, 15,625 racks. [Can delay by 3 month or more as everything has to go right. 800K chips with delays beyond 1.2 GW]
Dec 31, 2026: 2 million GPUs, 3,281 MW, 31,250 racks.
Dec 31, 2027: 3 million GPUs, 4,922 MW (or 3,150 MW with efficiency), 46,875 racks.
Acceleration Factors
GPU Pace: From 100k chips set up in 122 days, 92 days and projected to 60 days per 100,000 GPUs reflects Musk's optimization (e.g., Tesla Shanghai: 12 months to production).
Power Pace: 33 MW/month to 100 MW/month + bursts aligns with xAI's rapid turbine deployment and TVA's 1.2 GW pledge by 2027.
Constraints Mitigated: 750,000 sq ft and 13 MGD cooling suffice; chip supply (NVIDIA's $1.08B deal, $5Billion Dell/Nvidia deals) and permits (Memphis support) keep pace.
This timeline assumes xAI sustains its aggressive scaling, leveraging parallel workflows and regional cooperation.
1. AI Rack Density Power from $5 Billion in Dell B200-Enabled Servers
Given:
Colossus has a 750,000 square foot facility with 200,000 H100/H200 chips currently installed and are using less than 250 MW of power.
Tesla megapacks are used to prevent any power demands impacting peak power usage for other residential and business customers
A $5 billion investment in Dell B200-enabled servers is used for the expansion to 1 million chips.
Rack density power refers to the power consumed per rack of servers, typically measured in kilowatts (kW) per rack.