OpenAI · released 2024-01-25
GPT-3.5 Turbo uses about 0.067 Wh of electricity to answer a typical question. A long, complex answer costs about 23× more, at 1.56 Wh. That places it 136 of 277 among the models we can measure, and every figure here is calculated the same way as every other model.
The capability figure of 113.42 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.
No human head-to-head votes exist for this model. It has been benchmarked but not, as far as we can tell, put in front of people to compare against anything else, worth knowing before treating its scores as a verdict on its answers.
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.
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.
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.
Compare GPT-3.5 Turbo with another model
Or work out what a year of using it adds up to, for you or for a whole organisation.