Story 02 · cost simulator

Build an AI data center

Walk from a single 8-GPU box up to a 1 GW hyperscale campus — in 3D. Hover any part to see who makes it. The surprise isn't where the dollars sit — it's the gap between where the money is and what actually stops you building.

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Hover or tap a part of the data center to see who makes it.
Total capex
GPUs
Power
$ / GPU
Where the money goes
What actually gates this build
The line items
And then you run it — operating cost
Efficiency (PUE):
Electricity / year
Cooling overhead
5-year power bill
vs the chips

The money is always the chips. Even with realistic power and cooling — roughly $9–12M per megawatt of facility — the GPUs (with their HBM and packaging) are the majority of the capital cost, typically two-thirds to three-quarters of a GPU-dense build. The facility is expensive; the silicon inside it is still bigger.

But cost isn't the constraint. What stops you building changes as you grow. A single box fits in space you already have. A rack is the first time you need liquid cooling. A cluster waits on TSMC's packaging line, not the chips. And once you cross ~40 MW, the thing you genuinely cannot buy is electricity — a grid connection runs ~24 months, and at 1 GW you're competing with cities for transmission. The grid gear is a minority of the bill and the entire reason the project slips a year.

That gap — money in the silicon, bottleneck in the grid — is the whole investing story of the AI buildout. It's why the unglamorous power-and-cooling names (Vertiv, Eaton) get a multi-year demand surge even though they'll never be where most of the dollars land.

Method & sources

The dollar figures here are rounded, illustrative estimates, assembled from public reporting to show the shape of the spend — where the money concentrates and what gates the build — not exact quotes. Real systems vary, big buyers get steep discounts, and prices move fast. Verify against primary sources before relying on any number.

  • GPU & server pricing, AI capex — NVIDIA investor materials; reporting from The Information, Reuters, Bloomberg and Tom's Hardware on HGX / Blackwell systems.
  • Data-center cost structure & power as the bottleneckSemiAnalysis data-center TCO work; Dell'Oro Group (data-center capex & AI networking); Uptime Institute.
  • Memory / HBMTrendForce.
  • Power, cooling & switchgear — Vertiv and Eaton investor presentations & earnings calls.
  • Grid-connection timelinesLawrence Berkeley National Lab interconnection-queue studies; EPRI; utility interconnection filings.
  • Build cost per MW — industry benchmarks run ~$11–20M/MW for the facility (liquid cooling alone ≈ $4.5–5.2M/MW) and ~$45–55B/GW all-in for AI campuses (Construct Elements, iRecruit benchmarks). Our line-items land a touch conservative on facility infrastructure.
  • Operating cost — electricity is ~40–70% of opex; PUE averages ≈ 1.55 industry / 1.1–1.2 hyperscale (Uptime Institute survey); US industrial power ≈ 8.5¢/kWh (EIA). Servers refresh every ~3–6 years.
The global build-out

Where AI data centers are — and where they're going

A snapshot of the largest AI data-center campuses worldwide. Hover or tap a dot for the operator, capacity, status and source. Dot size ≈ announced power; colour = status.

Active / online Under construction Planned / announced
N. America Europe Middle East India E. Asia
* Capacity is the announced full-build target; most sites phase in over several years. Locations are approximate. Figures are from public reporting and change frequently — verify before relying on them.
The investment angle

What the buildout pays each company

Each data center writes the same checks to a handful of vendors. Pick a size, set how many get built each year, and watch the revenue stack up for each company over your horizon.

Data-center type
Built per year: 50
Horizon

Illustrative: this is the capital spend a buildout of this one archetype routes to each vendor — not a company's total revenue (they all have other businesses), and a real fleet mixes sizes. Built on the same cost model and sources above.

This is a story told as an app.
An AI agent researched the costs and built this interactive — the same way the rest of Investory is made. Build your own on cerver.ai →