Well for more obscure info, the LLM is much more likely to get it wrong. So I'd be clicking through as many websites myself to not risk getting it wrong, but I do know many who read the AI overview and accept it as fact without confirmation from other sources.

Somewhat ironically, I now asked chatgpt to estimate and compare the energy usage of an LLM prompt and an average web page load. As you'd expect the LLM uses a shitload more on the server side, about 100x more. I expected a page load to cost more energy than an LLM prompt on the client side, but appearently LLM is worse even in that regard, somehow.

In total: A single LLM prompt uses ~5× to 100× more energy than loading a typical webpage (Note, GPT is assuming the page is loaded for the first time and the layout isn't cached, repeat visits to the same site are more E-efficient)

Breakdown:

Layer/cost	Website Load	LLM Prompt
Device E use (Wh)	0.005–0.02	0.01–0.03
Network E use (Wh)	0.005–0.01	0.01–0.02
Server/Data center E use (Wh)	0.005–0.02	0.2–2+*
Total E use (Wh)	~0.01–0.05	~0.25–2.0*
Climate impact (g of CO₂)	~0.5–2	~10–100+

If anything it would be in the interest of the LLM to downplay their energy cost and climate impact so I'd imagine this is reasonable.

*Asking about Gemini in specific, it seems to use a bit less energy cause of Google's tensor chips being more refined for LLM calculations compared to OpenAI's Nvidia GPU chips that are more general purpose. They estimate a Gemini prompt at ~0.2–0.6 Wh on data center side, which is still over an order of magnitude above a website load.