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4,573 tracked

Entities

Registers of the facilities, companies and countries on record, with the ownership chains between them.

710 of 4,257 facility records carry an operational measure

4,257 facility records are individually browsable here, of which 710 carry an operational measure: power, GPU or FLOP capacity, or a substantive description. The other 3,547 establish that a site exists and stop there. Which of the two a record is depends almost entirely on the catalogue it arrived in.

Two counts on this page

Two counts appear on this page and they are not the same quantity. The masthead stamps 4,573 tracked records: the full corpus across 110 countries, the figure used site-wide. The register and the plate count the 4,257 that are individually browsable; the 316 in between are rows a licensing term keeps from being served as their own record. They inform aggregates and they are not hidden. They cannot be opened, so a figure about what a reader can inspect must not count them. The same universe is plotted in space on the map, rolled up by jurisdiction on Countries, and the organisations that own and operate these sites are in the company register.

  1. Epoch AI Frontier Data Centers7064 measured91.4%
  2. Epoch AI GPU Clusters437397 measured90.8%
  3. PeeringDB facility registry1,56963 measured4.0%
  4. IM3 / PNNL data-center corpus3912 measured0.5%
  5. OpenStreetMap (tagged data centers)1,1731 measured0.1%
  6. OpenStreetMap2310 measured0.0%
  7. Microsoft Azure region documentation560 measured0.0%
  8. Oracle Cloud region documentation450 measured0.0%
  9. 43 smaller catalogues285183 measured64.2%
Coverage by catalogue. Each band is one catalogue: its length is that catalogue’s share of the largest one’s row count, and the inked run inside it is the rows carrying at least one operational measure (power, GPU or FLOP capacity, or a substantive description). Nothing here is schematic; both lengths are measured proportions of the counts printed beside them. No share-of-megawatts is drawn: every megawatt-bearing row satisfies the measured predicate by construction, so a capacity share would be a tautology. Counts cover the full individually-browsable set, 4,257 rows, read 25 August 2026. The smallest catalogues are folded into one band whose run is hatched, because it averages catalogues of both kinds. Each named catalogue’s key opens the register below scoped to its rows.

Epoch AI Frontier Data Centers runs 91.4% measured across 70 records; OpenStreetMap runs 0.0% across 231. No single catalogue falls in between; the hatched band does, but it is the fold of 43 smaller catalogues and reads mid-scale only because it averages the two kinds. The separation exists because the two kinds of catalogue do different jobs: one is a research dataset built by measuring sites, the other an infrastructure registry built by recording that they exist. Any band’s key below opens the register scoped to that catalogue’s rows.

This is why the register opens on the measured cohort and says so; shown whole, most of the 4,257 rows could not answer the question a reader arrived with. The positional records are not filler: a site that exists is a real fact, and for a governance reader tracing where capacity might appear it is often the fact that matters. But it is a different fact from a megawatt figure, and a register that prints them in one undifferentiated count makes a uniformity claim its records do not support.

The register

Showing all 4,257 records, including the 3,547 positional ones with no capacity figure attached. Show only the 710 measured.

301350 of 4,257Page 7 of 86
FacilityCountryTypeStatusPower (MW)
Neevcloud cluster 1Epoch AI GPU ClustersINAI trainingOperational2
Ori Global Cloud H100 ClusterEpoch AI GPU ClustersAI trainingOperational2
SIAM AI HGXEpoch AI GPU ClustersTHAI trainingOperational2
NHN Cloud's National AI Data CenterEpoch AI GPU ClustersKRAI trainingOperational2
Hut 8 H100 ClusterEpoch AI GPU ClustersUSAI trainingOperational1
Eni HPC2Epoch AI GPU ClustersITAI trainingOperational1
Yandex ChervonenkisEpoch AI GPU ClustersRUAI trainingOperational1
AWS Fast BERT TrainingEpoch AI GPU ClustersUSAI trainingOperational1
TSUBAME4.0Epoch AI GPU ClustersJPAI trainingOperational1
KT Internal MI250 ClusterEpoch AI GPU ClustersKRAI trainingOperational1
G42 ArtemisEpoch AI GPU ClustersAEAI trainingOperational1
Iris Energy Prince George clusterEpoch AI GPU ClustersCAAI trainingOperational1
Microsoft Azure Pioneer-EUSEpoch AI GPU ClustersUSAI trainingOperational1
Microsoft Azure Pioneer-SCUSEpoch AI GPU ClustersUSAI trainingOperational1
Microsoft Azure Pioneer-WEUEpoch AI GPU ClustersNLAI trainingOperational1
Microsoft Azure Pioneer-WUS2Epoch AI GPU ClustersUSAI trainingOperational1
University of Florida HiPerGator 3.0 SuperpodEpoch AI GPU ClustersUSAI trainingOperational1
Google TPUv3 POD GenericEpoch AI GPU ClustersAI trainingOperational1
Yotta G1 (GIFT City)Yotta corporate disclosuresINHyperscale DCOperational1
Petrobras AtlasEpoch AI GPU ClustersBRAI trainingOperational1
Naver DGX SuperpodEpoch AI GPU ClustersKRAI trainingOperational1
Petrobras GaiaEpoch AI GPU ClustersBRAI trainingOperational1
Yandex LyapunovEpoch AI GPU ClustersRUAI trainingOperational1
Preferred Networks MN-1bEpoch AI GPU ClustersJPAI trainingDecommissioned1
Yandex GalushkinEpoch AI GPU ClustersRUAI trainingOperational1
RPI AiMOSEpoch AI GPU ClustersUSAI trainingOperational1
NVIDIA Taipei-1Epoch AI GPU ClustersTWAI trainingOperational1
Paper on AlphaZeroEpoch AI GPU ClustersUSAI trainingOperational1
SK Telecom Titan Phase 2Epoch AI GPU ClustersKRAI trainingOperational1
Moscow State University Lomonosov 2Epoch AI GPU ClustersRUAI trainingOperational1
NVIDIA DGX SuperPOD 2019Epoch AI GPU ClustersAI trainingOperational1
Pawsey Supercomputing Centre SetonixEpoch AI GPU ClustersAUAI trainingOperational1
Microsoft Azure Immunity BioEpoch AI GPU ClustersUSAI trainingOperational1
SberCloud ChristofariEpoch AI GPU ClustersRUAI trainingOperational1
Lawrence Livermore NL RZAdamsEpoch AI GPU ClustersUSAI trainingOperational1
DeepL MercuryEpoch AI GPU ClustersSEAI trainingOperational1
NEC Corp Japan SupercomputerEpoch AI GPU ClustersJPAI trainingOperational1
SURF Snellius Phase 3Epoch AI GPU ClustersNLAI trainingOperational1
Ahrefs Yep1Epoch AI GPU ClustersUSAI trainingOperational1
Recursion BioHive-2Epoch AI GPU ClustersUSAI trainingOperational1
BNY Mellon SupercomputerEpoch AI GPU ClustersAI trainingOperational1
Japan Atomic Energy Agency and Quantum and Radiological Science and Technology HPE SGI8600Epoch AI GPU ClustersJPAI trainingOperational1
Petrobras Fênix Phase 2Epoch AI GPU ClustersBRAI trainingOperational1
EuroHPC MeluXinaEpoch AI GPU ClustersLUAI trainingOperational1
Preferred Networks MN-2Epoch AI GPU ClustersJPAI trainingOperational1
SberCloud Christofari NeoEpoch AI GPU ClustersRUAI trainingOperational1
Princeton Della Phase 2Epoch AI GPU ClustersUSAI trainingOperational1
FZJ JURECAEpoch AI GPU ClustersDEAI trainingOperational1
Meta 2017 P100 ClusterEpoch AI GPU ClustersUSAI trainingOperational1
University of Illinois NCSA DeltaEpoch AI GPU ClustersUSAI trainingOperational1