AI Data Center Colocation: Choosing Providers for High-Density GPU Clusters

Traditional colocation data centers were designed for 5-15 kW per rack - enough for a chassis of CPU servers with 1-2 RU switches. The cooling architecture uses raised-floor airflow with perforated tiles, the electrical distribution uses 60 A or 100 A PDUs, and the floor loading assumes 3,000-5,000 pounds per rack. AI GPU clusters require 40-140 kW per rack, floor loading of 8,000-12,000 pounds for liquid-cooled racks with CDU equipment, and cooling capacity that can reject 10x the heat density. A colo provider whose maximum committed density is 25 kW per rack cannot support even a single GPU row without major infrastructure upgrades.

The density mismatch creates a cascade of facility constraints. At 100 kW per rack, a 20-rack GPU pod draws 2 MW of critical load. If the colo suite has 2N redundant power from two 1.5 MW UPS modules, that pod consumes two-thirds of the entire suite capacity. The floor tile layout must deliver 100 kW of chilled water per rack position for rear-door heat exchangers or liquid cooling manifolds. The floor grating must be rated for 12,000 pounds per rack to support the combined weight of servers, cooling manifolds, and cable ladder. Most colocation facilities built before 2023 cannot meet these requirements without a fully deprecated capital upgrade, which few are willing to fund for a single tenant.

AI colocation requires dedicated power delivery paths that bypass the shared busway infrastructure typical in multi-tenant colo. The standard solution is a dedicated electrical room per colo suite with a 2.5 MVA transformer, main switchboard with 4,000 A bus rating, and dedicated PDUs feeding overhead busway at 415 V or 480 V. For a 5 MW GPU deployment, the colo provider must provision 20 percent spare capacity in the electrical room, meaning the room must be sized and wired for at least 6 MW. The power path is: utility feed to colo substation, dedicated transformer, main switchboard, overhead busway, rack PDU, and server PSU - each hop audited for losses and voltage drop at full load.

The power pricing model for high-density colo differs from traditional per-rack or per-circuit pricing. Most GPU colo contracts use a pass-through model where the tenant pays the actual utility cost (typically $0.06-0.14/kWh depending on location) plus a facilities markup of 15-25 percent to cover transmission, transformation, UPS losses, and generator maintenance. Some providers offer blended all-in rates of $0.10-0.20/kWh including power and cooling. The key negotiation lever is utilization: GPU clusters idle at 100-300 W per GPU but draw 700-1,000 W under training load, meaning a 3-5x power draw swing. Contracts should specify whether billing is based on committed capacity (kW reserved) or actual consumption (kWh metered).

The colocation market segments into three tiers for GPU deployments. Tier 1 REITs (Equinix, Digital Realty, CyrusOne, QTS/CyrusOne) operate the largest footprint with the deepest interconnection ecosystems but charge the highest premiums, typically 20-40 percent above Tier 2. Their existing facilities, however, were mostly designed for 10-20 kW per rack, and retrofitting for GPU density requires premium-priced custom suites. Digital Realty's PDx (Powered Data eXchange) platform and Equinix's xScale program specifically address high-density with pre-configured 40-100 kW per rack zones, available at a 15-30 percent premium over standard colocation.

Tier 2 regional providers (Flexential, CoreSite, TierPoint, DataBank, Aligned) are often more responsive to GPU-specific requirements and can deploy high-density zones faster than the REITs due to simpler organizational approval chains. Aligned's Delta technology platform was designed specifically for high-density and delivers up to 50 kW per rack with rear-door heat exchangers as standard. CoreSite's Reston and LA facilities have deployed 40-60 kW per rack GPU zones for AI customers. The emerging Tier 3 category includes GPU-specific colo providers like Applied Digital and Nscale that build exclusively for AI workloads with 80-150 kW per rack liquid cooling, no raised floors, and electrical rooms embedded in each GPU suite. These specialized providers are capturing 15-25 percent of the GPU colo market and growing.

GPU clusters require dense network interconnectivity far beyond traditional colo tenants. A 256-GPU H100 pod with 16 nodes requires 128 NDR400 InfiniBand ports for compute fabric plus 16-32 ports for storage fabric. Cross-connects to cloud on-ramps (AWS Direct Connect, Azure ExpressRoute, Google Cloud Interconnect) need 100 Gbps or 400 Gbps each for hybrid AI training patterns where datasets reside in cloud storage. The interconnect cost for a 256-GPU deployment can easily reach $15,000-30,000 per month in cross-connect fees alone, before bandwidth charges from cloud providers.

The colo provider's fiber infrastructure and Meeting Room ecosystem are critical. Providers with a robust Internet Exchange (IX) presence - Equinix Fabric, Megaport, PacketFabric - enable dynamic bandwidth provisioning across 50-200 Gbps links that can be scaled up on demand. GPU tenants should verify: physical fiber diversity (at least two diverse conduit paths into the building), available cross-connect types (SMF single-mode fiber, single-mode OS2), provisioning lead time (digital cross-connects via SDN portals can be live in minutes; physical cross-connects require 5-15 business days), and whether the provider supports dark fiber delivery for direct customer-lit waves between colo suites or from colo to the tenant's fiber meet.

GPU colocation contracts differ materially from standard colo agreements. The term structure typically ranges from 1-3 years for GPU deployments versus 3-5 years for traditional colo, reflecting the rapid hardware refresh cycle. GPU GPU tenants should negotiate early termination rights tied to technology obsolescence (e.g., if the colo cannot support the next-generation GPU power density or cooling requirements). The security deposit for a 5 MW GPU suite can reach $500,000-1,500,000 - five to ten times a comparable CPU colo deposit - due to the concentration of asset value.

Force majeure and SLA provisions deserve particular attention. A 1 MW training job interrupted by a power event loses $5,000-10,000 per hour in GPU time value (at $3-5 per GPU-hour). The colo SLA should guarantee 100 percent power availability (not 99.99 percent) with defined financial credits: typically 5 percent monthly credit for the first hour, 10 percent for 2-4 hours, and 25 percent for more than 4 hours of cumulative downtime. Cooling SLAs should specify maximum GPU inlet temperature (28-30 degrees C) and humidity range (20-80 percent RH non-condensing per ASHRAE A2) with temperature excursion credits. Most colo providers resist 100 percent uptime SLAs - the negotiation outcome is typically 99.99 percent availability with a defined response time to power events (10-minute generator start, 30-second automatic UPS transfer).