Start by questioning the need (the most frugal query is the one you never run), then match the model to the task: a smaller model is enough for most uses and needs 10 to 50 times less energy than a large one. Add concise prompts, volume monitoring with a budget for each use case, and requests to your suppliers for data and for low-carbon regions. This is the logic of the general framework for frugal AI (AFNOR SPEC 2314).
Read the source article: AI Scope 3 emissions: how to count AI in your carbon footprint