Question 1

What is an AI datacenter?

Accepted Answer

An AI datacenter is a facility purpose-built or retrofitted for GPU and accelerator workloads — typically at rack densities above 30 kW, with liquid-cooling readiness and high-bandwidth fabric (InfiniBand NDR, NVLink, or Spectrum-X). At least 40% of IT load runs AI training or inference on GPUs such as NVIDIA H100, H200, B200, or GB200 NVL72.

Question 2

Which datacenter has the most GPUs?

Accepted Answer

As of 2026, xAI Colossus in Memphis, Tennessee holds the title of the world's largest single-site GPU deployment, with more than 200,000 NVIDIA H100 and H200 GPUs in one InfiniBand domain. Meta Hyperion (Louisiana) and OpenAI Stargate Abilene (Texas) are scaling toward gigawatt-class deployments that will overtake it within the next 18 months.

Question 3

What is the largest AI cluster?

Accepted Answer

xAI Colossus is the largest contiguous AI training cluster in 2026, exceeding 200,000 NVIDIA H100/H200 GPUs on a single InfiniBand NDR 400G fabric. Meta's Hyperion build and OpenAI's Stargate program are constructing multi-site fabrics that will exceed one million accelerators across coupled campuses by 2027.

Question 4

Which GPU cloud is cheapest for H100?

Accepted Answer

On-demand: Together AI ($1.75/hr) and Voltage Park ($1.89/hr) lead. Reserved 1-year: Voltage Park ($1.20/hr) and Crusoe ($1.39/hr) are typically lowest. AWS p5 sits at the top of the price stack at ~$4.10/hr on-demand.

Question 5

How is Datacenter.computer different from a datacenter directory?

Accepted Answer

Datacenter.computer is an agent-readable intelligence layer, not a directory. It normalizes pricing, capacity, power, fabric, and latency across 240+ facilities and 40+ operators into a single queryable graph for AI agents, traders, and procurement teams.

Facility	Operator	Location	GPU	MW	PUE
Crusoe MT-01	Crusoe	Glendive, MT, USA	H100	40	1.16
Crusoe Abilene	Crusoe	Abilene, TX, USA	B200	200	1.14
Crusoe Williston	Crusoe	Williston, ND, USA	H100	35	1.15

Crusoe Wyoming

Company → Datacenter → GPU → Customer → Industry