What is the carbon footprint of training a large frontier model — and of running it at scale?

The provided sources do not contain specific quantitative data on the carbon footprint of training a large frontier model or running it at scale. They focus primarily on compute costs, efficiency improvements, and operational expenses rather than environmental impacts like emissions [6][10][11]. One source highlights the broader "unseen carbon cost" of AI growth, noting that unbridled expansion risks exacerbating resource depletion and emissions through a behavioral theory lens, but it offers no model-specific figures [9]. Another emphasizes power as AI's key infrastructure bottleneck, with inferencing potentially 15 times more costly than training over a model's lifecycle and comprising 75% of AI compute by 2030, implying significant energy demands that could contribute to carbon footprints indirectly [10].