What are Prometheus and Hyperion? Meta AI campus capacity explained

• They are designed for AI workloads at far larger scale than conventional enterprise computing.
• They require multiple data-center buildings and highly coordinated infrastructure.
• They show why power delivery, thermal management, and networking become system-level concerns.
• They are useful examples of how frontier AI demand changes the physical form of compute.
• It shows that leading AI operators are planning capacity at industrial scale.
• It connects compute growth directly to grid, land, construction, and regional infrastructure.
• It raises the importance of deployment timing, not just headline chip counts.
• It helps readers understand why future compute supply may increasingly be measured in campuses and gigawatts.

Prometheus and Hyperion help explain what happens when compute becomes campus-scale infrastructure. Any figures shown are illustrative calculations, not current quoted market prices.

• Buildout timing and when each phase becomes operational.
• Power sourcing, grid upgrades, and long-term energy strategy.
• Whether capacity is concentrated in one campus or distributed across several facilities.
• Chip deployment, networking design, and cooling readiness.
• Whether other operators move toward similar campus-scale projects.

Market read: multi-gigawatt projects reveal expected demand for compute and power; commissioning progress indicates when supply may materialize. Figures here are illustrative unless explicitly sourced and dated — see our methodology.

• Investors and analysts: distinguish prospective electricity demand from operating compute output.
• Buyers: monitor whether new capacity becomes accessible or is committed internally.

Decision check: translate a campus announcement into market supply only at the stage supported by evidence.