GPU colocation requirements differ from those of a conventional server deployment because GPU systems concentrate substantial power draw, heat output, and network traffic into a relatively small footprint. Before selecting a facility, you need to confirm that it can support your hardware at the rack level, cool the expected load, provide the right network architecture, and leave room for the cluster to grow.
At ColoCapacity, we connect organizations with colocation facilities around the world and help them compare infrastructure based on their actual deployment needs. For GPU environments, that comparison needs to go much deeper than available rack space.
Why GPU Colocation Requirements Are Different
A traditional colocation request may begin with the number of cabinets, total power, bandwidth, and preferred market. A GPU deployment needs a more detailed technical profile.
AI training, inference, rendering, scientific computing, and other accelerated workloads often use dense clusters of high-powered systems. The facility must support the electrical load without forcing equipment across more cabinets than expected. It also needs enough cooling capacity to remove the resulting heat continuously.
Connectivity matters at two levels. The servers need fast links within the cluster, while the deployment needs reliable external access to users, storage platforms, cloud environments, and other facilities.
These requirements affect one another. Spreading hardware across extra cabinets may solve a rack power limitation, but it increases cabling distances, consumes more floor space, and could complicate cluster networking. A facility should be evaluated as one complete operating environment.
Start With an Accurate Power Profile
Power capacity is usually the first constraint to investigate. Do not base the request only on the number of racks or the stated wattage of individual GPUs.
Build the estimate from the complete system configuration, including:
- GPU servers
- CPUs and memory
- Local storage
- Network switches
- Management appliances
- Supporting storage systems
- Power conversion losses
- Expected growth
Use manufacturer specifications for each system rather than applying one estimate across every server. For example, NVIDIA’s data center deployment documentation lists a maximum system power consumption of 10.2 kW for a DGX H100 system. Other platforms will have different electrical and thermal specifications.
The maximum rating does not necessarily equal normal operating consumption, but the facility still needs a defensible design target. Ask your hardware vendor or engineering team for maximum power, expected sustained draw, input voltage, plug type, and power supply configuration.
Look Beyond Total Building Capacity
A data center may have significant power available across the property while limiting how much it delivers to one cabinet, cage, or section of the floor. Confirm:
- Maximum usable power per cabinet
- Available circuit sizes and voltage
- Single-phase or three-phase service
- A and B power-feed availability
- Power distribution unit compatibility
- Breaker and circuit utilization limits
- Metering at the cabinet or circuit level
- Capacity available for future expansion
Redundant feeds also need attention. Dual-corded equipment should connect to independent power paths where the design supports it. If a server has several power supplies, review how those supplies distribute load and how the system behaves after losing one feed.
Ask whether the quoted power reflects provisioned capacity, usable capacity, metered consumption, or a combination of these. That distinction affects both deployment planning and cost comparisons.
Match Cooling to the Actual Heat Load
Nearly all electrical power consumed by IT equipment eventually becomes heat. A dense GPU rack therefore creates a concentrated thermal load that the cooling system must remove around the clock.
Start by confirming whether the proposed configuration uses air cooling, direct-to-chip liquid cooling, rear-door heat exchangers, or another method. The answer will narrow the list of suitable facilities.
Air-cooled GPU systems require adequate airflow through each chassis and careful hot-aisle and cold-aisle management. Cabinet doors, containment, floor layout, fan direction, and neighboring equipment all influence cooling performance. High room-level capacity does not guarantee that enough cool air will reach a particular rack.
Liquid-cooled equipment introduces another set of questions:
- Does the facility support the required liquid-cooling method?
- Are coolant distribution units available?
- Who owns and maintains that equipment?
- What supply temperatures and flow rates are supported?
- How does the facility monitor leaks?
- Is heat rejection capacity available at the planned scale?
- Can the same cooling design support the next hardware generation?
Environmental limits should match the hardware manufacturer’s specifications. ASHRAE’s AI data center site-planning guidance also points infrastructure planners toward recommended and allowable environmental envelopes for IT equipment.
Request documentation for both the cooling design and the available capacity. If the deployment will grow in stages, verify that cooling can expand alongside rack power rather than becoming a separate bottleneck.
Plan for High-Performance Connectivity
GPU clusters move large datasets between compute nodes, storage systems, and external platforms. A facility with basic internet access may still fall short of the workload’s network requirements.
Begin with the cluster architecture. Training environments may need high-bandwidth, low-latency connections between servers. The number of nodes, switch design, oversubscription ratio, cable type, and physical distance between cabinets can all affect performance.
Then evaluate external connectivity. Depending on the workload, you may need:
- Multiple network carriers
- Diverse fiber entrances
- Dedicated internet access
- Private transport between facilities
- Direct cloud connectivity
- High-capacity cross-connects
- Access to an internet exchange
- Protection against carrier or path failures
Ask which carriers are already on-site and how long a new circuit normally takes to provision. A promising facility may become impractical if the required provider must build into the building or if cross-connect delivery will delay the launch.
Port speed alone does not define network performance. Review committed bandwidth, burst terms, latency to critical destinations, routing control, redundancy, and data-transfer charges. Storage traffic and model checkpoint transfers can make throughput and cost just as important as user-facing latency.
ColoCapacity’s global provider directory lets teams research infrastructure providers and compare their coverage before requesting detailed proposals.
Check Space, Weight, and Physical Installation Requirements
GPU hardware may create physical constraints that do not appear in a standard cabinet request. Document the rack-unit count, chassis depth, cabinet dimensions, equipment weight, and cable volume.
Confirm that the proposed cabinets can hold the equipment and that the floor can support the concentrated load. Heavy systems may also require server lifts or other installation equipment. Wider cabinets can simplify high-density network cabling, while deeper cabinets may be necessary for specific chassis designs.
Airflow direction deserves a separate check. Mixing front-to-back equipment with systems that use another airflow pattern can disrupt aisle containment and create recirculation.
Installation planning should cover delivery access, loading areas, staging space, packaging removal, rack-and-stack services, and any advance notice required for large shipments.
Review Operations and Remote Support
GPU infrastructure still needs hands-on attention after installation. Before signing an agreement, clarify what the facility’s remote-hands service includes.
Useful questions include:
- Is technical support available at all hours?
- What response times apply to urgent requests?
- Can technicians replace drives, cables, power supplies, or network components?
- Are support hours included or billed separately?
- Can replacement equipment be stored on-site?
- What access procedures apply to your employees and vendors?
- How are incidents documented and escalated?
The facility team may handle basic physical tasks, while your organization remains responsible for operating systems, orchestration, security, and workload management. Define those boundaries before deployment so expectations remain clear during an outage.
Account for Growth Before Choosing a Facility
A GPU deployment that fits today may exceed its original power, cooling, or network allocation after the next expansion. Ask whether adjacent cabinets are available and whether the facility can reserve or forecast capacity for later phases.
Future hardware may also draw more power per rack or require a different cooling method. A site that supports the first cluster should have a credible path for the next one.
Geography matters here as well. Power availability, network ecosystems, data-residency needs, and regional expansion options vary by market. You can use ColoCapacity to explore data center regions before narrowing the search to individual facilities.
Information to Include in a GPU Colocation Request
A detailed request produces more useful proposals and reduces follow-up questions. Include:
- Preferred countries, regions, or metro areas
- Hardware manufacturer and model
- Number of systems and cabinets
- Expected and maximum power draw
- Voltage, circuit, and receptacle requirements
- Cooling method and thermal specifications
- Required carriers and port speeds
- Inter-cabinet networking requirements
- Cloud or private-network connections
- Redundancy expectations
- Target installation date
- Growth forecast
- Remote-hands and storage needs
Avoid describing the project only as an AI or GPU deployment. Those labels do not tell a provider how much power, cooling, space, or bandwidth the equipment requires.
Compare GPU Colocation Facilities Against the Full Deployment
The right GPU colocation site must support the complete technical design, not simply have open cabinets. Confirm usable rack power, cooling at the expected density, network options, equipment fit, operational support, and an expansion path before comparing final pricing.
ColoCapacity lets teams research global markets, facilities, and providers through one platform. If you already know your hardware specifications, submit a custom infrastructure quote request with the expected power, cooling, connectivity, and location requirements. A detailed request makes it easier to identify facilities that can support the workload from installation through future growth.