What could Paralleliq save your fleet?
Estimate the annual value across margin recovery, incident prevention, and operational efficiency — based on your fleet size and current spend.
For hosted model API providers, inference deployment platforms, and enterprise AI teams.
Industry average: 30–40%. Most teams don't know their real number until they scan.
OOM triage, tier changes, customer escalations, utilization reviews.
Assumes 65% of estimated waste recovered and 70% of manual ops hours automated. Based on 64 GPUs at $3.5/hr and an ML infra engineer cost of $150/hr. Actual results depend on your workload mix and current tooling.
Want the full breakdown for your actual cluster — not estimates?
Ready to see your real number?
These are estimates. A 30-minute call with a piqc scan of your cluster shows you the actual waste, misplacement, and dark capacity — before you spend anything.
More Calculators
View all →$/Token vs. GPU Utilization
See how utilization rate drives cost per token — and what recovering waste saves.
Procurement Deferral Calculator
How many months does fleet optimization delay your next hardware order?
Capacity Risk Calculator
Find your GPU ordering deadline before traffic growth outpaces your cluster.
GPU Waste Calculator
Estimate how much your inference fleet could recover through rightsizing.
GPU Inference TCO Calculator
Compare total cost of ownership across cloud providers.
Build vs. Buy: GPU Control Plane
Model engineering time, maintenance cost, and 3-year total cost.
GPU Sizing Calculator
Get a GPU type, node count, and scaling strategy recommendation.
Inference Capacity Planner
Plan GPU capacity based on your model, traffic, and latency targets.
GPU Fleet Cost Optimizer
Find the lowest-cost configuration for your throughput requirements.
KV Cache & Context Window Cost
See how KV cache memory scales with context length and batch size.
CPU:GPU Ratio Calculator
Find the gap as AI shifts from batch inference to multi-agent orchestration.