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Hyperscaler capital expenditureData-centre electricity demandRack power density by generationLargest announced AI campusesTraining compute of notable modelsNuclear power deals signed for AI demandHigh-bandwidth memory

Hyperscaler capital expenditure

USD billions

The four largest cloud and AI platform companies have roughly tripled their combined capital spending in three years, with the overwhelming share going to AI data centers, accelerators and power. 2025 figures are company guidance, not final actuals.

202320242025 (g)
0 50 100 Microsoft (FY) — 2023: 32.2 USD billions 32.2 Microsoft (FY) — 2024: 55.7 USD billions 55.7 Microsoft (FY) — 2025 (g): 88.2 USD billions 88.2 Alphabet — 2023: 32.3 USD billions 32.3 Alphabet — 2024: 52.5 USD billions 52.5 Alphabet — 2025 (g): 92 USD billions 92 Amazon — 2023: 52.7 USD billions 52.7 Amazon — 2024: 83 USD billions 83 Amazon — 2025 (g): 125 USD billions 125 Meta — 2023: 28.1 USD billions 28.1 Meta — 2024: 39.2 USD billions 39.2 Meta — 2025 (g): 71 USD billions 71 Microsoft (FY) Alphabet Amazon Meta
 202320242025 (g)
Microsoft (FY)32.255.788.2
Alphabet32.352.592.0
Amazon52.783.0125.0
Meta28.139.271.0

출처 및 근거: Company 10-K/10-Q filings and stated guidance, as of late 2025. Microsoft figures are fiscal years ending June and include finance leases; Amazon figures are purchases of property and equipment; 2025 values marked (g) are company guidance.

Data-centre electricity demand

TWh per year, global

The IEA estimates global data centres consumed about 415 TWh of electricity in 2024 — around 1.5% of world demand — and projects roughly 945 TWh by 2030 in its base case, with AI the dominant driver of the growth. Projections carry wide uncertainty bands; the 2030 figure is a scenario, not a fact.

0 500 1000 2024 (IEA estimate): 415 TWh per year, global 415 2030 (IEA Base Case projection): 945 TWh per year, global 945 2024 (IEA estimate) 2030 (IEABase Case projection)
 TWh per year, global
2024 (IEA estimate)415
2030 (IEA Base Case projection)945

출처 및 근거: IEA, "Energy and AI" (April 2025): 2024 estimate and Base Case 2030 projection. Scenario ranges in the same report span materially higher and lower outcomes.

Rack power density by generation

kW per rack (typical / vendor spec)

A conventional enterprise rack draws under 10 kW. An air-cooled H100 rack runs around 40 kW; a GB200 NVL72 rack is specified around 120 kW and is liquid-cooled by requirement; NVIDIA's announced Rubin Ultra NVL576 targets roughly 600 kW per rack for 2027. Cooling and power distribution, not floor space, now define data-center design.

0 200 400 600 Enterprise rack (typical): 8 kW per rack (typical / vendor spec) 8 HGX H100 rack, air-cooled (typical): 40 kW per rack (typical / vendor spec) 40 GB200 NVL72 (vendor spec): 120 kW per rack (typical / vendor spec) 120 Rubin Ultra NVL576 (announced target, 2027): 600 kW per rack (typical / vendor spec) 600 Enterprise rack (typical) HGX H100rack, air-cooled (typical) GB200 NVL72(vendor spec) Rubin UltraNVL576 (announced target, 2027)
 kW per rack (typical / vendor spec)
Enterprise rack (typical)8
HGX H100 rack, air-cooled (typical)40
GB200 NVL72 (vendor spec)120
Rubin Ultra NVL576 (announced target, 2027)600

출처 및 근거: Typical enterprise figure: industry rule of thumb. H100/GB200 figures: NVIDIA system specifications and partner deployment documentation. Rubin Ultra: NVIDIA GTC 2025 announcement — a stated target, not a shipping product.

Largest announced AI campuses

GW, announced ultimate capacity (reported)

Announced ultimate capacities of the flagship AI campuses. These are targets reported by the companies or credible press — build-outs are phased over years and plans change; first-phase capacities are far smaller.

Meta Hyperion (Louisiana): 5 GW, announced ultimate capacity (reported) Meta Hyperion (Louisiana) 5 Amazon New Carlisle / Rainier (Indiana): 2.2 GW, announced ultimate capacity (reported) Amazon New Carlisle / Rainier (Indiana) 2.2 Stargate Abilene (Texas): 1.2 GW, announced ultimate capacity (reported) Stargate Abilene (Texas) 1.2 xAI Colossus 2 (Memphis): 1 GW, announced ultimate capacity (reported) xAI Colossus 2 (Memphis) 1

출처 및 근거: Company announcements and reporting by mainstream outlets, as of the site's snapshot date. Each campus's record page lists its specific sources.

Training compute of notable models

training FLOP (floating-point operations)

Frontier training compute has grown roughly 4–5× per year for over a decade (Epoch AI estimate). Because the range spans nine orders of magnitude, it is shown as a table rather than a chart.

ModelYearTraining computeBasis
AlexNet 2012 ~4.7×10¹⁷ FLOP Epoch AI estimate
GPT-2 2019 ~1.5×10²¹ FLOP Epoch AI estimate
GPT-3 2020 3.1×10²³ FLOP disclosed in paper
Llama 3.1 405B 2024 ~3.8×10²⁵ FLOP computed from disclosed GPU-hours
GPT-4 2023 ~2×10²⁵ FLOP Epoch AI estimate
Grok 3 2025 ~4–5×10²⁶ FLOP Epoch AI estimate

출처 및 근거: Published papers where disclosed (GPT-3, Llama 3.1); Epoch AI estimates otherwise. Estimates carry significant uncertainty.

Nuclear power deals signed for AI demand

Hyperscalers have signed the first wave of nuclear offtakes in a generation — restarting shut reactors, buying existing output and backing SMR fleets. Restart and deployment dates are company targets and can slip.

DealAnnouncedScaleStatus / target
Microsoft – Constellation, Crane Clean Energy Center (Three Mile Island Unit 1 restart) Sep 2024 835 MW, 20-year PPA Restart targeted 2027; work under way
Amazon – Talen Energy, Susquehanna Mar 2024 (expanded Jun 2025) Up to 1,920 MW carbon-free supply arrangement Operating plant; supply ramps to 2032
Meta – Constellation, Clinton Clean Energy Center Jun 2025 1,121 MW, 20-year agreement Begins 2027 when state support expires
Google – Kairos Power SMR fleet Oct 2024 Up to 500 MW across multiple reactors First deployment targeted ~2030
Microsoft — Holtec Palisades context: first US restart — 800 MW (Holtec restart, DOE loan; not a Microsoft deal) Returned to service Oct 2025 — first restarted US reactor

출처 및 근거: Company announcements (Constellation, Talen, Holtec, Kairos Power, Amazon, Microsoft, Meta, Google), as reported 2024–2025.

High-bandwidth memory

HBM is the scarcest input in AI hardware: every leading accelerator depends on it, three companies make it, and supply has been sold out generations in advance.

3companies make HBM at scaleSK hynix, Samsung, Micron — see the Memory section
HBM3E 12-highshipping generation through 202536 GB per stack; used by B300, MI325X/MI355X, TPU v6 and peers (vendor specs)
HBM4sampling 2025 → volume 2026~2 TB/s per stack targeted; SK hynix and Micron vendor statements
~50%+SK hynix share of HBM, 2024–2025TrendForce estimates — estimate, not a reported figure

출처 및 근거: Vendor statements (SK hynix, Samsung, Micron) and TrendForce market estimates, as of the site's snapshot date.