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
CoreWeave IL01	CoreWeave	Chicago, IL, USA	H100	32	1.22
Azure North Central US	Microsoft Azure	Chicago, IL, USA	H100	300	1.20
Equinix CH2	Equinix	Chicago, IL, USA	Mixed	30	1.40

AI Datacenters in

Company → Datacenter → GPU → Customer → Industry