Google Puts a Number on a Gemini Query: 0.24 Watt-Hours

For two years, estimates of how much electricity a single AI query uses have ranged widely, because the companies running the models would not say. On August 21 Google became the first major AI developer to publish its own figure. In a technical paper and accompanying blog post, it estimated that the median Gemini Apps text request uses 0.24 watt-hours of energy, emits 0.03 grams of carbon dioxide equivalent, and consumes 0.26 milliliters of water, about five drops.

Google compares the energy to watching television for less than nine seconds. The more useful parts of the disclosure are the method behind it, the rate at which it has fallen, and what it still does not tell us. Google says many published estimates count only the energy used by AI chips during active computation, which gives a theoretical rather than operational picture. Its method includes four additional elements: the actual utilization achieved by chips at production scale, which can be well below theoretical maximums; idle machines kept ready for traffic spikes or failover; the host CPU and memory that support the accelerators; and data center overhead such as cooling and power conversion, captured by power usage effectiveness.

MIT Technology Review, which interviewed Google chief scientist Jeff Dean about the report, gave the breakdown. The paper reports that over a recent 12-month period, the energy of the median Gemini text request fell by a factor of 33 and its total carbon footprint by a factor of 44, while response quality improved. Without that number, the per-query figure can be read in very different ways. Luccioni also said the report is not a substitute for a standardized AI energy score comparable to the Energy Star rating for appliances.

The disclosure lands as utilities and grid operators build forecasts around AI demand. The arithmetic of data center load depends on the product of two numbers: energy per unit of work and the amount of work.