How long does it take for a local GPU to pay off vs LLM APIs?

At moderate utilization, an RTX 4090 or Mac Studio M4 Max typically breaks even in 6-18 months compared to GPT-4o-class APIs. Higher utilization and cheaper electricity shorten payback.

What is the biggest hidden cost of local LLMs?

Electricity, cooling, maintenance, and downtime are the main hidden costs. Model upgrades can also require more VRAM, forcing hardware refreshes.

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Local LLM ROI Calculator

Should you buy a GPU workstation or keep paying per token? Find your break-even point.

Local Hardware

Hardware cost ($)

Power draw (W)

Electricity ($/kWh)

Hardware utilization (%)

Replacement / upgrade reserve ($/yr)

Cloud API Alternative

Input tokens / mo (millions)

Output tokens / mo (millions)

API input price ($/1M)

API output price ($/1M)

Forecast years

3-Year TCO Comparison

Local TCO

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Cloud TCO

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Savings (local)

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Break-even

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Why local wins or loses

Low volume: Cloud is cheaper until you hit steady, predictable token usage.
High utilization: Local hardware pays off faster when GPUs run most of the day.
Cheap electricity: At $0.06/kWh, local TCO drops significantly.
Privacy / latency: Local may win even at higher cost if you cannot send data to APIs or need sub-100ms responses.
Compare hardware options in our GPU comparison table.

Local LLM ROI Calculator

Local Hardware

Cloud API Alternative

3-Year TCO Comparison

Why local wins or loses

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