Free Tool

GPU Inference TCO Calculator.

Model the full 3-year cost of your GPU inference fleet — compute, operations, idle waste, and networking — and see where ParallelIQ recovers margin.

Infrastructure

GPU Type

GPU Count

Cloud Provider

Pricing Commitment

Utilization %

Model Size

Traffic

Requests / day

Avg output tokens

API price ($/M tokens)

Operations

ML Ops FTEs

Avg annual salary ($)

One-time setup cost ($)

Platform fee ($/GPU/mo)

3-Year TCO

$2.21M

8× H100 · AWS

$735,974

Annual spend

$197,345

Idle waste/yr

$1.61M

3yr with Paralleliq

$596,013

3yr savings

3-Year cost comparison

Without Paralleliq

With Paralleliq

API only (0.88/M tokens)

Annual cost breakdown

Item	Baseline	w/ PIQ
Compute (GPU hours)	$358,810	$289,739
Wasted capacity (idle)	$197,345	$128,274
Operations (people)	$360,000	$216,000
Networking & storage	$17,164	$17,164
Paralleliq platform	$0	$14,400

4 months

Payback period

Net monthly saving: $16,556/mo after platform fee. 3-yr net ROI: $596,013.

99.4M req/mo

API break-even

You need 66.3× more traffic to justify self-hosting over the API.

Operations is a significant cost center. 49% of your TCO is people managing GPU infrastructure. Automating utilization management reduces this by up to 40%.

Get your full TCO report. Enter your work email and we'll send a detailed breakdown.

Estimates use public on-demand cloud pricing. Committed use discounts are applied as multipliers. Waste reduction and ops savings are modeled at 35% and 40% respectively based on ParallelIQ customer data.

Want actual numbers from your running fleet?

The TCO calculator models estimates. piqc scans your live Kubernetes cluster and shows you the actual idle waste and cost — no agents, no instrumentation required.

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