AI Training vs. Inference Infrastructure Requirements

Training and inference share hardware families but differ sharply in how they use a facility. Treating them as one requirement leads to over-built edge sites or under-built training halls.

Training: power and contiguity

Training clusters run near peak power for long periods and benefit from large, contiguous footprints with dense east-west fabrics. Proximity to end users is rarely a constraint; power availability and growth pathway usually are.

Inference: latency and distribution

Inference serves users. Interactive applications benefit from regional placement, multi-site resilience, and local peering. Power density per site is often lower, but the number of sites is higher.

Planning both together

• Place training where power and contiguous growth are available.
• Place latency-sensitive inference regionally.
• Connect the two with diverse, sized network paths.
• Use the same operating model across both tiers.