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) |
|---|---|---|---|---|
| Google TPUv5eEpoch AI GPU Clusters | — | AI training | Operational | 24 |
| Google Oklahoma TPU v4 PodsEpoch AI GPU Clusters | US | AI training | Operational | 24 |
| NexGen Cloud Hyperstack AQ Compute SupercomputerEpoch AI GPU Clusters | NO | AI training | Operational | 23 |
| Oracle OCI Supercluster H100sEpoch AI GPU Clusters | US | AI training | Operational | 23 |
| Yotta Shakti Cloud D1Epoch AI GPU Clusters | IN | AI training | Announced | 23 |
| Yotta Shakti Cloud NM1 Phase 2Epoch AI GPU Clusters | IN | AI training | Announced | 23 |
| ORNL Frontier (Exascale HPC)Scrutica internal fixture record | US | HPC center | Operational | 23 |
| Microsoft GPT-4 clusterEpoch AI GPU Clusters | US | AI training | Operational | 21 |
| Microsoft Azure EagleEpoch AI GPU Clusters | US | AI training | Operational | 21 |
| Gemini 1.0 Ultra training cluster AEpoch AI GPU Clusters | US | AI training | Operational | 20 |
| DayOne SG1 SingaporeDayOne corporate disclosures (May 2026) | SG | Colocation | Under construction | 20 |
| xAI Fulton GeorgiaEpoch AI GPU Clusters | US | AI training | Announced | 20 |
| Equinix SG3Company disclosure (press / IR) | SG | Colocation | Operational | 20 |
| Scaleway DC5 (PAR2)Scaleway corporate disclosures | FR | Hyperscale DC | Operational | 20 |
| Port Jeff -Mt. Sinai Energy StorageGridStatus | US | Hyperscale DC | Decommissioned | 20 |
| Jupiter, JülichEpoch AI GPU Clusters | DE | AI training | Operational | 18 |
| Sakura's B200s Phase 2Epoch AI GPU Clusters | JP | AI training | Announced | 16 |
| Oak Ridge NL TitanEpoch AI GPU Clusters | US | AI training | Decommissioned | 16 |
| Meta 2017 V100 ClusterEpoch AI GPU Clusters | US | AI training | Operational | 16 |
| TensorWave MI300X Cluster 1 Phase 2Epoch AI GPU Clusters | US | AI training | Announced | 15 |
| TensorWave MI300X Cluster 2Epoch AI GPU Clusters | US | AI training | Announced | 15 |
| Imbue 10k ClusterEpoch AI GPU Clusters | US | AI training | Operational | 15 |
| Tesla 10k H100 ClusterEpoch AI GPU Clusters | US | AI training | Operational | 15 |
| XTX Markets ClusterEpoch AI GPU Clusters | — | AI training | Operational | 15 |
| Eni HPC6Epoch AI GPU Clusters | IT | AI training | Operational | 14 |
| Poolside 10k ClusterEpoch AI GPU Clusters | — | AI training | Announced | 14 |
| iGenius ColosseumEpoch AI GPU Clusters | IT | AI training | Announced | 14 |
| Meta Research SuperCluster (RSC-1) Phase 2Epoch AI GPU Clusters | US | AI training | Operational | 13 |
| Oak Ridge NL SummitEpoch AI GPU Clusters | US | AI training | Decommissioned | 13 |
| EuroHPC LeonardoEpoch AI GPU Clusters | IT | AI training | Operational | 13 |
| S. Korea 6th national supercomputerEpoch AI GPU Clusters | KR | AI training | Announced | 12 |
| EuroHPC LUMIEpoch AI GPU Clusters | FI | AI training | Operational | 12 |
| Saudi Data & AI Authority Sovereign AI factoryEpoch AI GPU Clusters | SA | AI training | Announced | 12 |
| Equinix LD5 (London)Company disclosure (press / IR) | GB | Colocation | Operational | 12 |
| Alps Supercomputer Phase 2Epoch AI GPU Clusters | CH | AI training | Operational | 12 |
| Sesterce NordicsEpoch AI GPU Clusters | — | AI training | Operational | 12 |
| Lawrence Livermore NL SierraEpoch AI GPU Clusters | US | AI training | Operational | 12 |
| Amazon Titan training clusterEpoch AI GPU Clusters | US | AI training | Operational | 11 |
| Magic G4 Google Cloud RentalEpoch AI GPU Clusters | US | AI training | Operational | 11 |
| Foxconn Hon Hai Kaohsiung SupercomputerEpoch AI GPU Clusters | TW | AI training | Announced | 11 |
| Google Hypercomputer TPU v5p podEpoch AI GPU Clusters | — | AI training | Operational | 10 |
| AIST ABCI 3.0Epoch AI GPU Clusters | JP | AI training | Operational | 9 |
| Aramco Groq Inference ClusterEpoch AI GPU Clusters | SA | AI training | Operational | 9 |
| SoftBank Planned B200 SuperpodEpoch AI GPU Clusters | JP | AI training | Announced | 8 |
| University of Bristol Isambard-AIEpoch AI GPU Clusters | GB | AI training | Operational | 8 |
| LUMI Supercomputer (CSC Finland)Scrutica internal fixture record | FI | HPC center | Operational | 7 |
| Sustainable Metal Cloud Singapore Phase 2Epoch AI GPU Clusters | SG | AI training | Announced | 7 |
| Nebius ISEG2Epoch AI GPU Clusters | IS | AI training | Operational | 7 |
| Lawrence Berkeley NL NERSC PerlmutterEpoch AI GPU Clusters | US | AI training | Operational | 7 |
| Scaleway DC3 (PAR1)Scaleway corporate disclosures | FR | Colocation | Operational | 7 |