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 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.
- Epoch AI Frontier Data Centers7064 measured91.4%
- Epoch AI GPU Clusters437397 measured90.8%
- PeeringDB facility registry1,56963 measured4.0%
- IM3 / PNNL data-center corpus3912 measured0.5%
- OpenStreetMap (tagged data centers)1,1731 measured0.1%
- OpenStreetMap2310 measured0.0%
- Microsoft Azure region documentation560 measured0.0%
- Oracle Cloud region documentation450 measured0.0%
- 43 smaller catalogues285183 measured64.2%
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.
| Facility | Country | Type | Status | Power (MW) |
|---|---|---|---|---|
| CEA EXA1-HE Phase 2Epoch AI GPU Clusters | FR | AI training | Operational | 2 |
| Lawrence Livermore NL Lassen Phase 2Epoch AI GPU Clusters | US | AI training | Operational | 2 |
| Microsoft Ares/MaiaEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| Nebius ISEGEpoch AI GPU Clusters | FI | AI training | Operational | 2 |
| Tesla Dojo 1 Phase 1Epoch AI GPU Clusters | US | AI training | Announced | 2 |
| Jean Zay Supercomputer Phase 4Epoch AI GPU Clusters | FR | AI training | Operational | 2 |
| IBM VelaEpoch AI GPU Clusters | US | AI training | Operational | 3 |
| TotalEnergies Pangea IIIEpoch AI GPU Clusters | FR | AI training | Operational | 3 |
| MIT LLSC TX-GAIAEpoch AI GPU Clusters | US | AI training | Operational | 3 |
| JAMSTEC ZettaScaler-2.2 GyoukouEpoch AI GPU Clusters | JP | AI training | Operational | 3 |
| Cineca Marconi-100Epoch AI GPU Clusters | IT | AI training | Operational | 3 |
| Google TensorFlow Research CloudEpoch AI GPU Clusters | US | AI training | Operational | 3 |
| GSIC TSUBAME 2.5Epoch AI GPU Clusters | JP | AI training | Operational | 3 |
| Los Alamos NL VenadoEpoch AI GPU Clusters | US | AI training | Operational | 3 |
| Quebec 2k H100 ClusterEpoch AI GPU Clusters | CA | AI training | Operational | 3 |
| AIST ABCI-QEpoch AI GPU Clusters | JP | AI training | Operational | 3 |
| Horizon Compute Baobab Phase 2Epoch AI GPU Clusters | US | AI training | Operational | 3 |
| US Government Supercomputer 1Epoch AI GPU Clusters | US | AI training | Operational | 3 |
| US Government Supercomputer 2Epoch AI GPU Clusters | US | AI training | Operational | 3 |
| SoftBank CHIE-2Epoch AI GPU Clusters | JP | AI training | Operational | 3 |
| SoftBank CHIE-3Epoch AI GPU Clusters | JP | AI training | Operational | 3 |
| Northern Data Group Njored Taiga Cloud Island 5Epoch AI GPU Clusters | GB | AI training | Operational | 3 |
| Northern Data Group Taiga Cloud Island 3Epoch AI GPU Clusters | — | AI training | Operational | 3 |
| Northern Data Group Taiga Cloud Island 4Epoch AI GPU Clusters | — | AI training | Operational | 3 |
| Northern Data Group Taiga Cloud NO1 Island 1Epoch AI GPU Clusters | NO | AI training | Operational | 3 |
| Northern Data Group Taiga Cloud NO1 Island 2Epoch AI GPU Clusters | NO | AI training | Operational | 3 |
| NVIDIA Israel-1 Phase 2Epoch AI GPU Clusters | IL | AI training | Operational | 3 |
| Novo Nordisk GefionEpoch AI GPU Clusters | DK | AI training | Operational | 3 |
| Google TPU v4 PodEpoch AI GPU Clusters | US | AI training | Operational | 3 |
| JUWELS-BoosterEpoch AI GPU Clusters | DE | AI training | Operational | 3 |
| Ezra-1 Stability AI AWS ClusterEpoch AI GPU Clusters | — | AI training | Operational | 3 |
| Tesla Training ClusterEpoch AI GPU Clusters | US | AI training | Operational | 4 |
| AWS EC2 P4dEpoch AI GPU Clusters | US | AI training | Operational | 4 |
| Samsung SSC4Epoch AI GPU Clusters | KR | AI training | Operational | 4 |
| NVIDIA SATURN V Phase 3Epoch AI GPU Clusters | US | AI training | Operational | 4 |
| CEA EXA1-HE Phase 3Epoch AI GPU Clusters | FR | AI training | Operational | 4 |
| Scaleway DC2 (PAR1)Scaleway corporate disclosures | FR | Colocation | Operational | 4 |
| Google MLPerf 0.7 SubmissionEpoch AI GPU Clusters | US | AI training | Operational | 4 |
| Eni HPC5Epoch AI GPU Clusters | IT | AI training | Operational | 4 |
| FPT AI Factory JapanEpoch AI GPU Clusters | JP | AI training | Announced | 4 |
| FPT AI Factory VietnamEpoch AI GPU Clusters | VN | AI training | Announced | 4 |
| CSCS Piz Daint Phase 2Epoch AI GPU Clusters | CH | AI training | Operational | 4 |
| Paper on PaLMEpoch AI GPU Clusters | US | AI training | Operational | 4 |
| Vultr Chicago ClusterEpoch AI GPU Clusters | US | AI training | Operational | 5 |
| Microsoft Azure Meta AI RentalEpoch AI GPU Clusters | US | AI training | Operational | 5 |
| NVIDIA Selene Phase 2Epoch AI GPU Clusters | US | AI training | Operational | 5 |
| Huawei Pangu Ultra MoE 910BsEpoch AI GPU Clusters | — | AI training | Operational | 5 |
| KDDI Sharp SakaiEpoch AI GPU Clusters | JP | AI training | Announced | 5 |
| Intel Stability Gaudi 2Epoch AI GPU Clusters | US | AI training | Operational | 5 |
| Saudi Aramco Dammam-7Epoch AI GPU Clusters | SA | AI training | Operational | 5 |