⚡ An AI query uses as little energy as a microwave for one-tenth of a second

• A simple text query to AI uses only 114 joules - equivalent to running a microwave for one-tenth of a second.
• Generating a high-quality image requires 2,282 joules, which corresponds to five and a half seconds in the microwave.
• Even the largest text model uses only 6,706 joules per response, less than what is required to run a microwave for eight seconds.

Text generation requires minimal energy

A new comprehensive analysis from MIT Technology Review shows that individual AI queries consume surprisingly little energy. Researchers at the University of Michigan have measured energy consumption for different types of AI tasks and found that most everyday uses require very small amounts of electricity.

The smallest model in the study, Meta's Llama 3.1 8B, uses only 57 joules from the processor to answer questions. When researchers included cooling and other systems, the total consumption became 114 joules per response. This corresponds to the energy to run a microwave for one-tenth of a second.

Even complex tasks like writing travel plans for Istanbul or explaining quantum computing require the same low energy amount. Simple questions like asking for jokes often use nine times less energy than more complicated tasks.

The largest text model in the study, Llama 3.1 405B with 405 billion parameters, consumes 6,706 joules per response. This is enough to run a microwave for eight seconds.

Image generation more efficient than expected

Creating images with AI requires surprisingly little energy compared to the largest text models. Stable Diffusion 3 Medium uses 2,282 joules to generate a standard image with 1024 x 1024 pixel resolution. This corresponds to five and a half seconds in the microwave.

Image-generating models often work with fewer parameters than large text models, which explains the lower energy consumption. The energy requirement does not depend on what the image depicts - creating an image of a skier on sand dunes requires the same energy as an astronaut farming on Mars.

Open models enable precise measurement

Researchers used specialized tools to measure energy consumption of H100 GPU chips, which are used in most AI data centers. They found that doubling the GPU's energy consumption provides a good estimate of the entire system's energy needs, including processors, fans, and cooling.

The study focused on so-called open source models that can be downloaded and tested by researchers. Meta announced in April that its Llama models have been downloaded more than 1.2 billion times, showing that these efficient models are used on a large scale.

Unlike closed systems like ChatGPT, Google Gemini, and Anthropic Claude, researchers can measure the energy consumption of open models exactly. This gives users the opportunity to make informed choices based on actual energy data.

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