Project
EarthCompute
Google Earth plus Wayback Machine, for compute.
Financial markets
Crypto
GPU & compute
62% of the world’s compute and GPU infrastructure mapped
0%
Global coverage
Target 90%
0
Facilities mapped
Operator-verified
0
Server SKUs
Bare metal + cloud
0
Fiber routes
Terrestrial, OSM
0
Intercontinental links
Subsea + cross-border
0
Exchange points
PeeringDB
Live inventory API
Largest live provider catalogs
Earth Compute can tell you if you’re getting ripped off.
Overpaying
0.0×
Find cheaper AI infrastructure anywhere on Earth.
The point is not just seeing infrastructure. It is finding where a qualified GPU or server costs less.
Search the planet
The same H100 class can cost about 60% less.
Current published H100-class listings show why price discovery matters before choosing where to run AI.
~60% lower
Global compute still lacks its shared intelligence layer.
AI demand
Training and inference workloads are growing rapidly, putting new pressure on compute supply.
GPU scarcity
Accelerator supply is concentrated across a relatively small set of large providers and buyers.
Fragmented supply
Regional operators hold real capacity that is difficult for buyers to discover and compare.
Cost pressure
Compute can become one of the largest variable costs for AI-native companies.
Sovereignty
Governments and enterprises increasingly care where workloads and data are placed.
Underused capacity
Installed capacity can sit underused while buyers struggle to find the right infrastructure elsewhere.