Running LLMs On-Premise: Hidden Costs Beyond the Power Bill

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A logistics firm's engineering director moved AI inference onto a local GPU after a cloud bill reached $8,000 in one month. Power consumption proved modest, but the true expense lies in setup and maintenance time that is rarely accounted for. By the author's estimate, the setup and debugging consumed about 40 hours over three months, covering driver conflicts, networking breakdowns, and silent output errors. Over three months, the local setup cost roughly $58 to $73 per month including hardware amortization, versus $180 to $240 for a comparable cloud API, with breakeven around month four. The analysis concludes that on-premise hosting pays off mainly for high-volume, repetitive, or privacy-sensitive workloads, while low-volume use is usually cheaper through an API.

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