GPU Calculators for AI teams.
Eight free tools to help you size, cost, and optimize your GPU infrastructure — before and after deployment.
GPU Waste Calculator
AI teams waste up to 50% of GPU spend. Estimate how much your inference fleet could recover through rightsizing in 30 seconds.
GPU Inference TCO Calculator
Compare total cost of ownership across cloud providers for your GPU inference workload — H100, A100, L4, and more.
Build vs. Buy: GPU Control Plane
Should you build a GPU fleet control plane internally or use Paralleliq? Model engineering time, maintenance cost, and 3-year total cost side by side.
GPU Sizing Calculator
Get a GPU type, node count, and scaling strategy recommendation based on your model size, quantization, and traffic pattern — before you deploy.
Inference Capacity Planner
Plan GPU capacity for inference at scale. Input your model, traffic, and latency targets and get a fleet size recommendation.
GPU Fleet Cost Optimizer
Model a mixed GPU fleet across providers and workload types to find the lowest-cost configuration for your throughput requirements.
KV Cache & Context Window Cost
See how KV cache memory scales with context length, batch size, and model architecture — and what it costs at production scale.
CPU:GPU Ratio Calculator
Is your cluster balanced for your workload? As AI shifts from batch inference to multi-agent orchestration, the GPU:CPU ratio keeps falling. Find your gap.
Want a real number from your actual cluster?
These calculators give you estimates based on inputs you provide. piqc scans your running Kubernetes cluster in seconds and shows you the actual waste, misplacement, and dark capacity — no agents, no instrumentation.