What does it cost to build an AI GPU cluster? Pick a GPU, set the count and your energy price, and get an equipment capex range, the power/cooling infrastructure estimate, annual energy cost, and cost per rack and per usable kW — for H100, H200, B200 and GB200 clusters.
The cost to build an AI cluster splits into three parts, and this estimator produces a planning range for each from a single input — your GPU count.
It reuses the same sizing engine as the BOM generator and the power calculator, so the equipment list, the load and the cost all agree.
The GPUs themselves are the headline, but a cluster's real cost is the system around them. Dense AI needs liquid cooling (CDUs), redundant power (UPS and transformers), high-density distribution, and an 800G network — and then the building has to deliver it: electrical and mechanical install commonly runs several dollars per watt of facility power. On top of capex, energy dominates operating cost: a multi-megawatt cluster running continuously spends millions a year, and a better PUE turns straight into savings.
Comparing builds on cost per usable kW cuts through the noise — it normalises for size and GPU type and is how operators actually reason about AI data center economics. Estimate it here, then turn the numbers into a firm quote so market pricing, redundancy and lead times are confirmed against your specific project.
Equipment cost scales with GPU count — a 512× H100 cluster is roughly the servers, racks, power, cooling and network in the millions of dollars, plus a power/cooling infrastructure install typically estimated at $3–6 per watt of facility power, plus ongoing energy. This estimator produces a planning range from your GPU count and energy price; our engineers confirm firm pricing at quote.
It splits into equipment capex (GPUs, servers, racks, UPS, transformers, cooling, network, monitoring), facility infrastructure (electrical and mechanical install, containment, construction), and operating cost (mostly energy). This tool estimates the equipment and infrastructure ranges and the annual energy bill so you can budget the whole build.
Cost per usable kW divides the mid-point capex by the IT (usable) power the cluster draws — a useful way to compare builds of different sizes and GPU types on an apples-to-apples basis, and a common metric for AI data center economics.
GB200 NVL72 racks are priced and quoted as integrated systems (72 GPUs, ~120 kW, direct-liquid), so a GB200 cluster concentrates cost into fewer, denser, more expensive racks with correspondingly higher cooling and power infrastructure per rack. The estimator prices the integrated racks and sizes the surrounding infrastructure.
It is a fast planning range using the catalog’s indicative unit prices, standard install $/W factors and your energy price — good for budgeting and comparing options. Final cost depends on configuration, redundancy, site, market pricing and lead times. Request a quote and our engineers confirm the firm number.
Our solutions engineers confirm the exact equipment, infrastructure and lead times and return firm pricing — no payment, no commitment, back in about one business day.
Our engineers scope power, cooling and compute together. No payment, and quotes come back in about a business day.