The honest math
Owned beats rented. Here is the math.
Cloud AI inference is a large, variable, recurring cost. Continuous workloads break even against a self-hosted build in months, then keep saving for years. We do not hide the premium. We show it.
~18.0 months to break even
Break-even
3-yr delta $11,057 owned vs cloud
Workload
Usage
Recommended build
RTX 5090 node
$11,000
Estimated volume
~1,980M tokens / month
@ $0/1M blended cloud
Cloud / mo
$693
Owned / mo (power)
$80
3-yr saving
$11,057
At heavy 24/7 usage, this workload breaks even in ~18.0 months, then keeps saving. Owning turns a variable cloud bill into a fixed cost plus cheap Ontario power. You pay a premium once; you stop renting forever.
Estimate. Cloud rates: AWS Bedrock on-demand, US regions (DeepSeek v3.2 $0.62/$1.85 per 1M; frontier proxied to Claude Sonnet 5 standard $3/$15). Build costs in CAD include Aurora Nyxus margin over ~$6K GB10 retail. Power at Ontario ~$0.10/kWh. Real numbers depend on your exact model, context length, throughput, and duty cycle. We quote from your actual workload.
The rented trap
Pay-as-you-go inference scales with use. Nightly agentic workflows can run about $5,000 a month on a hyperscaler. Every user consumes credits. You rent forever, and the meter never stops.
The owned advantage
A self-hosted node's main operating cost is electricity. Ontario power is among the cheapest in North America. Run a node at steady load and a typical workload breaks even in about a year, then it is yours.
01
Fixed, not variable
Owned capacity turns AI cost into a fixed line.
02
Cheap Ontario power
Among the lowest electricity rates in North America.
03
Route intelligently
Local, subscription, and pay-as-you-go via one router.