Free Tool

Build vs. Buy: GPU Optimization Layer.

How much does it cost to build a GPU optimization layer internally — vs. using Paralleliq from day one? Model engineering time, maintenance, and 3-year total cost.

Your Cluster

GPU Count128 GPUs

8 GPUs2048 GPUs

GPU cost ($/hr per GPU)$3/hr

$1/hr$15/hr

Expected revenue ($/GPU/month)$100/GPU/mo

$10/GPU/mo$500/GPU/mo

Engineers dedicated to building optimization layer

Loaded engineer cost (annual)$180K

$100K$300K

Paralleliq (illustrative)

Platform fee ($/GPU/month)$8/GPU/mo

$1/GPU/mo$30/GPU/mo

Pricing is illustrative. Actual pricing is based on fleet size and configuration. Get a quote →

3-Year Cost Comparison

Build internally

$360K

$180K/yr 1 · $90K/yr ongoing

Paralleliq

$37K

$12K/yr · available day one

Time to first customer

Month 7

6 mo build + integration

Time to first customer

Day 1

production-ready on arrival

$323K saved over 3 years

3-Year cost breakdown

Build internally

Paralleliq

Engineering time consumed

6 mo

To first MVP

$90K

Spent before v1

Day 1

Paralleliq ready

GPU waste accrued during 6-month build

$498K

Wasted at 30% waste rate

Paralleliq optimizes day one

While your team builds, your GPUs run unoptimized. At 30% average waste, that's $498K in GPU spend with no findings, no recommendations, and no audit trail.

Revenue you couldn't capture during 6-month build

$77K

Left on the table

Paralleliq captures from day one

While your team builds, every GPU you provision runs blind — no waste detection, no cost intelligence, no audit trail for your customers. GPU clouds that pair their control plane with an optimization layer win on efficiency and customer trust. At $100/GPU/month, that's $77Kin differentiation that doesn't wait.

Building internally costs $360K over 3 years; Paralleliq costs $37K. That's $323K your team redirects to your actual product — and you're serving customers on Day 1 while competitors are still in sprint planning.

Get the detailed breakdown. Enter your work email and we'll send a full build vs. buy analysis for your fleet size.

Build cost assumes {engineers} FTE × 6 months to MVP, then 0.5 FTE ongoing maintenance. Paralleliq pricing is illustrative — actual pricing based on fleet size and configuration.

Want this analysis sent to your team?

We'll send you the full build vs. buy breakdown to share with stakeholders.

Ready to see it on your actual cluster?

The calculator models estimates. A 30-minute call shows you exactly what Paralleliq looks like on your build — workspace isolation, per-cluster credentials, and audit trail from day one.

Book a Demo See the Product