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How much energy does GPT-4 Turbo (Nov 2023) use?

OpenAI · released 2024-01-25

GPT-4 Turbo (Nov 2023) uses about 0.995 Wh of electricity to answer a typical question. A long, complex answer costs about 23× more, at 23.2 Wh. That places it 250 of 277 among the models we can measure, and every figure here is calculated the same way as every other model.

A typical question
0.995 Wh
0.46 g CO₂·≈ 2 metres (6 feet) of driving
A long, complex answer
23.2 Wh
11 g CO₂·≈ 43 metres (141 feet) of driving
Capability
126.5
Energy rank
250 of 277
Human votes
1272

How capable is it, really?

The capability figure of 126.46 is a composite over 58 benchmarks, Epoch AI's Capabilities Index, which folds in software engineering, agentic tool use, long-context comprehension and creative writing as well as science reasoning. It is one number standing for a lot of separate tests, so treat a small gap between two models as noise rather than a ranking.

98,114 people have voted on it in blind head-to-head comparisons on LMArena, giving it a rating of 1272. This is the only figure here that measures whether anyone actually prefers the answers, rather than how the model scores on a test. Broken down, people rate it 1268 on coding, 1268 on creative writing, 1249 on following instructions.

What this figure is

Day-one estimate  Calculated from an estimated parameter count, the maker hasn't published one. Every model on this site is calculated the same way, so the comparison holds even where the absolute value carries uncertainty. Our figures are good to roughly a factor of two to three, which is why we only ever state a difference of 5× or more.

Is there a better choice?

A lighter model that does the job
Anthropic · capability 159.0. It scores higher than GPT-4 Turbo (Nov 2023) on Epoch's Capabilities Index (158.98 against 126.46), the composite over 58 benchmarks that the capability figure above comes from, and uses about 45× less energy per answer: 0.515 Wh against 23.2 Wh. It has not faced human head-to-head voting, where GPT-4 Turbo (Nov 2023) carries 98,114 votes, worth weighing. See them side by side →

What OpenAI publishes

Energy cannot be worked out without knowing how big a model is. Of the 39 models from OpenAI that we track, 34 can be assessed at all, the rest publish too little for anyone outside the company to calculate anything.

Where these figures come from

Capability and the roster come from Epoch AI, whose Capabilities Index is the 58-benchmark composite quoted above. Energy is calculated with EcoLogits and calibrated against laboratory measurements from ML.ENERGY. Human preference comes from LMArena. All four are public and free; the full method is here.

These figures are published under CC BY 4.0, use them anywhere, including commercially, with credit to The AI Footprint.

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Figure calculated 2026-10-17 · how these numbers are made · the full comparison of 277 models