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) |
|---|---|---|---|---|
| Preferred Networks MN-1bEpoch AI GPU Clusters | JP | AI training | Decommissioned | 1 |
| Yandex LyapunovEpoch AI GPU Clusters | RU | AI training | Operational | 1 |
| Petrobras GaiaEpoch AI GPU Clusters | BR | AI training | Operational | 1 |
| Naver DGX SuperpodEpoch AI GPU Clusters | KR | AI training | Operational | 1 |
| Petrobras AtlasEpoch AI GPU Clusters | BR | AI training | Operational | 1 |
| Yotta G1 (GIFT City)Yotta corporate disclosures | IN | Hyperscale DC | Operational | 1 |
| Google TPUv3 POD GenericEpoch AI GPU Clusters | — | AI training | Operational | 1 |
| University of Florida HiPerGator 3.0 SuperpodEpoch AI GPU Clusters | US | AI training | Operational | 1 |
| Microsoft Azure Pioneer-EUSEpoch AI GPU Clusters | US | AI training | Operational | 1 |
| Microsoft Azure Pioneer-SCUSEpoch AI GPU Clusters | US | AI training | Operational | 1 |
| Microsoft Azure Pioneer-WEUEpoch AI GPU Clusters | NL | AI training | Operational | 1 |
| Microsoft Azure Pioneer-WUS2Epoch AI GPU Clusters | US | AI training | Operational | 1 |
| Iris Energy Prince George clusterEpoch AI GPU Clusters | CA | AI training | Operational | 1 |
| G42 ArtemisEpoch AI GPU Clusters | AE | AI training | Operational | 1 |
| KT Internal MI250 ClusterEpoch AI GPU Clusters | KR | AI training | Operational | 1 |
| TSUBAME4.0Epoch AI GPU Clusters | JP | AI training | Operational | 1 |
| AWS Fast BERT TrainingEpoch AI GPU Clusters | US | AI training | Operational | 1 |
| Yandex ChervonenkisEpoch AI GPU Clusters | RU | AI training | Operational | 1 |
| Eni HPC2Epoch AI GPU Clusters | IT | AI training | Operational | 1 |
| Hut 8 H100 ClusterEpoch AI GPU Clusters | US | AI training | Operational | 1 |
| NHN Cloud's National AI Data CenterEpoch AI GPU Clusters | KR | AI training | Operational | 2 |
| Denvr Dataworks H100Epoch AI GPU Clusters | US | AI training | Operational | 2 |
| GreenNode Bangkok ClusterEpoch AI GPU Clusters | TH | AI training | Operational | 2 |
| IBM Blue VelaEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| LeptonAI H100 ClusterEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| Neevcloud cluster 1Epoch AI GPU Clusters | IN | AI training | Operational | 2 |
| Ori Global Cloud H100 ClusterEpoch AI GPU Clusters | — | AI training | Operational | 2 |
| SIAM AI HGXEpoch AI GPU Clusters | TH | AI training | Operational | 2 |
| Scaleway NabuchodonosorEpoch AI GPU Clusters | FR | AI training | Operational | 2 |
| NVIDIA HeliosEpoch AI GPU Clusters | — | AI training | Operational | 2 |
| Taiwania 2Epoch AI GPU Clusters | TW | AI training | Operational | 2 |
| Tesla Auto-Labeling ClusterEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| Samsung SSC-21Epoch AI GPU Clusters | KR | AI training | Operational | 2 |
| GSIC TSUBAME 3.0Epoch AI GPU Clusters | JP | AI training | Operational | 2 |
| JCAHPC MiyabiEpoch AI GPU Clusters | JP | AI training | Operational | 2 |
| GENCI AdastraEpoch AI GPU Clusters | FR | AI training | Operational | 2 |
| Petrobras DragãoEpoch AI GPU Clusters | BR | AI training | Operational | 2 |
| ExxonMobil Discovery 5Epoch AI GPU Clusters | US | AI training | Operational | 2 |
| Softbank SuperPODEpoch AI GPU Clusters | JP | AI training | Operational | 2 |
| ND A100 v4Epoch AI GPU Clusters | US | AI training | Operational | 2 |
| Ubilink.AI SupercomputerEpoch AI GPU Clusters | TW | AI training | Operational | 2 |
| Petrobras Pegasus (Pégaso)Epoch AI GPU Clusters | BR | AI training | Operational | 2 |
| Microsoft Azure Voyager-EUS2Epoch AI GPU Clusters | US | AI training | Operational | 2 |
| Core42 SuperPODEpoch AI GPU Clusters | AE | AI training | Operational | 2 |
| Sandia NL El DoradoEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| NAVER Corp SejongEpoch AI GPU Clusters | KR | AI training | Operational | 2 |
| Gcore data center Phase 2Epoch AI GPU Clusters | KR | AI training | Announced | 2 |
| Argonne NL PolarisEpoch AI GPU Clusters | US | AI training | Operational | 2 |
| Eni HPC4 Phase 2Epoch AI GPU Clusters | IT | AI training | Operational | 2 |
| Microsoft Explorer-WUS3Epoch AI GPU Clusters | US | AI training | Operational | 2 |