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Microsoft Puts AI Query Power Use at 0.16 to 0.60 Wh, Far Below Prior Estimates

The revised figures challenge widely cited claims that a single AI query uses several watt-hours, with implications for data center planning and public perception of AI energy costs.

Reporting from 1 sources: GIGAZINE.

Microsoft Puts AI Query Power Use at 0.16 to 0.60 Wh, Far Below Prior Estimates

Microsoft published an analysis estimating that a typical query to a large language model consumes 0.16 to 0.60 Wh of power, roughly equivalent to running a microwave for a few seconds. The figure is 1/20th to 1/4th of earlier estimates, which Microsoft says failed to account for batch processing and production GPU utilization rates.

Microsoft's research team based the estimate on a model with over 200 billion parameters running on a server with eight NVIDIA H100 GPUs. They combined metrics including tokens processed per second, per-server power consumption, and facility-level Power Usage Effectiveness (PUE). For a median query of about 300 tokens, median power consumption was 0.31 Wh, with the central 50% of the range falling between 0.16 and 0.60 Wh. Water consumption for cooling was estimated at 0 to 0.067 mL per query.

Microsoft argues that earlier estimates-some suggesting a ChatGPT query uses roughly 10 times the power of a Google search-overstated consumption by 4 to 20 times because they did not reflect batch processing or efficient GPU operation in high-user environments. However, the company notes that queries requiring multi-step reasoning or long code generation, with a median response of 5000 tokens, consume about 3.91 Wh, roughly 13 times a typical query.

Synthesized by Yomimono from the 1 cited source below, including Japanese-language reporting where cited, then editorially reviewed before publishing.

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