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Cloud, local, or hybrid: run your numbers.

Move the sliders to match your AI spend. The model computes 36-month cumulative cost for staying on cloud APIs, owning the hardware, and hybrid routing, with break-even months and the savings gap, live. Nothing leaves your browser until you decide it should.

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The verdict · updates as you drag

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Your inputs
All metered AI: LLM APIs, copilots, embedded AI vendors.
AI usage compounds. 5–10%/mo is typical for scaling programs.
Share of workload a right-sized local model could handle: extraction, tagging, summarization, internal Q&A.
From a workstation cluster to DGX-class. Hybrid assumes ~40% of this.
Power, colo, and the ops overhead honesty requires.
How much of today's monthly workload the hardware can absorb. Growth beyond it overflows to cloud.
The URL carries your inputs, so paste it into the budget thread.
Cumulative cost · 36 months · hover to inspectIllustrative model
Cloud only Owned / colocation Hybrid routing Your savings wedge
Break-even · owned
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vs cloud-only
Break-even · hybrid
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vs cloud-only
36-month savings
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best alternative vs cloud
Cloud run-rate · month 36
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per month if nothing changes
Where you land at month 36
Cloud only
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Owned / colo
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Hybrid routing
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Illustrative model for directional decisions. It assumes owned capacity absorbs workload up to the multiple you set, with growth overflowing to cloud; hybrid assumes ~40% of the quoted capex, half the opex, and routes your "routable" share locally. A real TCO audit replaces every assumption here with your workload traces, utilization, quotes, and pricing. Read the cloud vs local vs hybrid AI decision guide for the operating tradeoffs behind the model.