Silicon Analysts

GPU Cluster TCO Calculator

Model total cost of ownership for AI GPU clusters from 8 to 16,384 GPUs over 1–5 years. Includes hardware, networking, power, cooling, datacenter space, staff, and software costs. Compare against equivalent cloud costs.

Cluster TCO Calculator

Model total cost of ownership for GPU clusters. Select a preset or configure hardware, power, and operations to see a complete cost breakdown.

Hardware

816,384

Power & Cooling

Datacenter & Operations

$78.5M
3-Year TCO
$2.1K
Cost/GPU/month
2.1 MW
Total Power
55%
vs Cloud Savings

TCO Breakdown

Cost Breakdown Detail

Component3-Year CostAnnual% of Total
GPU Hardware$47.1M$15.7M60.0%
DC Space / Colo$15.4M$5.1M19.6%
Staff / Operations$5.0M$1.6M6.3%
Replacement / Refresh$3.7M$1.2M4.7%
Power (Electricity)$3.3M$1.1M4.1%
Networking$2.6M$853.3K3.3%
Software Licensing$1.5M$512.0K2.0%
Cooling$66.4K$22.1K0.1%
Total TCO$78.5M$26.2M100%

Cloud Comparison

On-prem TCO
$78.5M
Equiv. cloud cost
$176.3M
Savings
$97.8M (55%)

Cloud estimate uses published on-demand rates with 30% reserved discount. Actual cloud costs vary by commitment, region, and availability.

Operational Details

GPU systems: 128
Total power: 2.06 MW
FTEs needed: 11
Cost/TFLOP/mo: $0.47

Frequently Asked Questions

How much does a GPU cluster cost?
A DGX H100 system (8 GPUs) costs $200K–$500K. A 256-GPU SuperPOD costs $7–10M. Total 3-year TCO including power, cooling, networking, and operations typically adds 50–70% on top of hardware cost. Our calculator models all components.
What percentage of cluster TCO is hardware vs operations?
GPU hardware typically represents 35–50% of 3-year TCO. Power (electricity) is 10–20%, networking 10–15%, datacenter space 10–15%, staff 5–10%, and software/licensing 2–5%. The exact split depends on electricity rates, GPU generation, and deployment model.
How much power does a GPU cluster use?
An H100 SXM5 uses approximately 1,400W total system power per GPU (including CPU, networking, and cooling overhead). A 1,024-GPU B200 cluster draws approximately 1.8MW. GB200 NVL72 racks draw 120–130kW each and require liquid cooling.
What is the best deployment model for GPU clusters?
Colocation is most common for clusters under 10MW — it offers fastest time-to-deployment with typical rates of $200–215/kW/month in Northern Virginia. Owned facilities make sense above 50MW where the $15–20M/MW construction cost is amortized over scale and time.