The table doesn't say 29kW, it says 29Wh for 1500 output tokens with 10k input tokens, i.e. energy per token, not power. On Wed, Jul 29, 2026 at 12:12 PM Jaro Reinders via ghc-devs <ghc-devs@haskell.org> wrote:
I've done a bit of research now, mainly based on Jegham et al. "How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference"
They list the energy consumption of DeepSeek-R1 (671B params) to be ~29 kW at 10k input token and 1.5k output token scales (Table 4). I think it is reasonable to expect current frontier models to at least match that since the models seem to have gotten larger and I think contexts are generally also larger in the use case we're considering (large chunks of GHC would have to get loaded into the context presumably).
From the same study, most datacenters use around 0.3 kg of CO2 equivalent per kWh (Table 1), so DeepSeek R1 uses about 8.7 kgCO2e/h.
That means using a single agent for ~400 hours is equivalent to a return flight from Austin Texas to Zurich (3500 kg CO2e; source: online tool), which I find an unjustifiable amount of emissions, but I guess some members of the community do already make such a trip once a year.
I think this shows that it is likely that heavy use of LLMs causes significant emissions exceeding that of yearly transatlantic flights.
Cheers,
Jaro
On 27 Jul 2026, at 15:46, Tom Ellis via ghc-devs <tom-lists-ghc-devs-2026@jaguarpaw.co.uk> wrote:
On Mon, Jul 27, 2026 at 03:32:45PM +0200, Magnus Viernickel via ghc-devs wrote:
Technological improvements increasing the efficiency of a resource do not lead to a fall but to a rise in total consumption of that resources.
That's a well-known effect. See e.g. https://en.wikipedia.org/wiki/Jevons_paradox.
Yes indeed. I do not dispute that the amount of energy going into AI usages is increasing both in relative and absolute terms.
But how much?
There are countless projections and surveys like the one shared by Andrei. We fortunately do not have to rely on bloggers with no considerable qualification in that area.
That's good to hear, and I would welcome someone making a numeric claim and backing it up with citations. I think that would be a valuable contribution to the discussion here.
To be clear: *I* am not trying to make a claim, nor refute someone else's claim. I am pointing out that no such claim has been made precise nor substantiated in this discussion! If someone believes strongly that AI energy use should be factored into GHC's LLM policy then the responsibility is theirs to make a precise and substantiated claim. If claims about AI energy usage are not precise and substantiated then I don't see why they should factor into the policy decision.
Tom _______________________________________________ ghc-devs mailing list -- ghc-devs@haskell.org To unsubscribe send an email to ghc-devs-leave@haskell.org
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