“ChatGPT uses 10 times more energy than a Google search.”

“ChatGPT uses 10 times more energy than a Google search.”

That sentence has been in slides, headlines, and comment sections for three years.

It was never a measurement of ChatGPT.

Here is the actual chain.

In 2009, Google published a number. A search used about 0.3 watt-hours. They have not published a replacement in seventeen years.

In 2023, an Alphabet chairman said talking to a large language model would “likely cost 10 times more than a keyword search.” That was an expectation. Not a meter reading.

A paper in Joule took the 10× and multiplied it by the 2009 search figure. That produced about 3 watt-hours per interaction. Another early model landed at 2.9, assuming answers the length of a short essay.

The International Energy Agency put 2.9 next to 0.3 in a chart.

The internet did the rest.

Ten times became the fact.
The 2009 baseline stayed frozen.
The essay-length assumption stayed invisible.

Then OpenAI published its own number. An average ChatGPT question uses about 0.34 watt-hours.

That is not 10× a 2009 Google search.
That is about the same as a 2009 Google search.

Epoch AI independently landed in the same neighborhood for a typical text answer.

The 10× was an input to an old estimate. It got quoted as the output.

I’m not saying a reasoning run, an agent loop, or a generated video is a search.

Those can be many times a normal answer.

I’m not saying Google Search in 2026 is still the 2009 machine. It isn’t. They added a lot of AI to the results page and never updated the 0.3.

I am saying we have been repeating a ratio that was guessed from a sixteen-year-old search number and a sentence in an interview.

If you want to compare AI to search, compare this year’s machines. Stop hanging the argument on a multiplier nobody measured.