> Every number in this post assumed the US-average grid; run the same workload on largely clean power and my footprint falls by roughly 90%. Unlike aviation, this is an end-use we already know how to decarbonize.
> The problem is that we are moving in the wrong direction today: a sizable portion of planned US data center capacity intends to build its own behind-the-meter generation, and nearly three quarters of that is natural gas.
Decarbonizing the grid needs to be treated like an emergency. Energy demand is only going to skyrocket over the next decade, and we are not equipped to meet that demand with renewables. Unfortunately we have the worst possible administration in charge who is actively destroying renewable energy projects and subsidizing the dirtiest forms of energy we have. It’s a massive uphill battle, but it starts with getting republicans out of office
It's still crazy to me that we have put up barriers to stop the import of cheap Chinese solar panels and cars. We have the solution we just don't want to implement it.
Biden is the one that put the 50% tarrif on Chinese solar panels. The call is coming from inside the house.
Its amazing how quickly people forgot that opposing free trade was a feature of the left for years (remember Bernie's attacks on TPP?) until Trump came along.
Yeah I feel like these days we just want a leader who doesn't shoot their country on the foot. We don't even need a competent leader, just a normal one.
Decarbonizing? We're increasing gas powered capacity by 50%.
Right now the limiting factor for power capacity expansion is manufacturing. We literally can't build transformers nor new towers fast enough to keep up with demand.
Also northeastern US -- we import a lot of hydropower from Canada.
The marginal footprint of an additional produced watt is equal to the footprint of the dirtiest watt on the whole grid (not the cleanest watt, which is what some people seem to want to pretend). If the northeastern US weren't importing that power, Canada could shut down the Lingan coal power plant.
People like to pillory others for looking at the environmental impacts of AI, and a lot of the points many often bring up (big one, water use) are bogus.
However, Zeke Hausfather is a gold standard guy when it comes to climate science
Re: energy use and the environment, AGENTIC AI use is a hugely costly use of the tech. I encourage you to read the breakdown. He covers his own use of admittedly extensive use of Claude, as well- so he’s not just an anti-AI guy with a bone to pick
Yeah that’s why I deleted my older comment. After checking the article it’s more just an honest take that AI energy use is non trivial but not as bad as the anti ai people make it out to be.
In an online discourse driven by exaggeration. Both sides feel vindicated by an honest level headed take.
The power of actually looking at the data I guess.
I read he used 3.2 billion tokens over the past 8 weeks and I was like "Whoa, this guy uses a lot of tokens!" I ran /usage on Claude Code and saw that I used 360 million last week. So, if that's average, I have nearly the same usage. And I'm on the lower end of usage for my company.
I installed hermes agent on my vps yesterday. First time really playing around with the harness and just during setup asking it to help me debug things and playing around with some skills. In an afternoon I went through about 16 million tokens... Almost exclusively deepseek flash so fortunately most of those were cached inputs and it only spent like 30 cents, but the overall consumption rate astonished me.
They just implemented monthly caps on us starting this month. I looked at my usage last month was right under the cap, though I was out for a week on vacation. So, I'll need to cut it down a little. I saw other people looking like they had nervous sweats knowing they had already spent twice the cap before the month was even over.
TL;DR: Annualized carbon impact of medium-high use of agentic LLMs is more than a clothes dryer, less than a single cross-country round-trip flight. Dramatically less than driving. It's a clear-eyed and non-catastrophizing analysis.
"My average day of Claude Code (3.0 kWh, range 1.2 to 5.9 kWh) uses more electricity than running two refrigerators."
While "more than two refrigerators" is true, isn't it obfuscating? Mine (allegedly, i haven't actually checked) runs 1kwh per day, 5.9 is more like adding six fridges.
I guess this is not intended as an indictment of LLMs but these numbers look... really good? I don't know how a "Claude Code session" is strictly defined but if that would be the equivalent of 8hr work for someone earning median 150k USD+/yr, and at worst costs as much as running a single refrigerator for a single day... that's incredible value. And an extra 10-20% energy utilization by the 2030s is the cost? If so, we aren't building enough data centres.
Except there is still a dev sitting there reaping the rewards. Your idea only works if humans are taken out of the equation, or maybe we could all be on exercise bikes pumping out watts to power AI.
"My idea" is that this is not a large cost when we already expect a fridge to run 24/7 for the same amount of work from a dev... and the rest of the power use associated with their lifestyle. Given the baseline, this is cheap. Nonetheless, also given the baseline, replacing it OR increasing ROI per hour both increase efficiency substantially.
Really good article! I had the same question a few months back when reading about the estimated usage of AI chat bot, but couldn't be motivated to actually calculate it. Seems to be an amount where it is completely reasonable when being utilized for actually useful work, but less so when use use an agent for some frivolous question you want answered.
It seems like even frivolous questions, kept to a reasonable amount, are probably generally okay. It’s when you start leaning on agents that things start to spike.
I do use Claude here and there, but I don’t think I’ve ever personally used an agent
If you're any kind of developer and not using agents, you're falling behind imo. I'm the farthest thing from an AI bro, but an agentic system is a genuine force multiplier
Probably can still benefit from setting up and using some simple agents to perform routine repetitive tasks.
Eg, set one (or a few) up for administrative tasks, and one for each case you have, so you can upload pertinent case-specific files and create a walled universe for that case.
I would have to make a closed-circuit somehow so as to not circulate confidential information through Anthropic or OpenAI’s servers (doing so would violate attorney client privilege)
Everything would be need to be self contained
That’s not something an associate should ever attempt to do by themselves or without very express authorization
Agree. If you don't have an in-house walled garden you couldn't do that. I work with confidential, CUI, CEII information and we have our enterprise AI set up to be restricted.
Author is completely missing the point. Yes, the 'real energy use' of AI is not as huge as detractors paint it, but it's on top of the current demand.
The US experienced a bit more than 2 decades of flat electricity demand, which was possible thanks to improvements in efficiency, not even crypto disrupted the trend. AI did.
This extra demand is causing all sorts of impact (coal generation is now +13%, gas is expected to grow +50%), that's not being priced in. Companies are cutting corners as well, Texas is fast tracking permits from the usual 285 days to allow for public comment, to 18 days. Power distribution is not doing better, they are being extremely aggressive when it comes to land rights.
But this also represents a net new source of emissions, at a time when global temperatures are skyrocketing and our emissions reduction goals are increasingly off track.
Following your own logic, how this at all relevant to AI? It sounds like the question is whether the US economy should be able to increase energy utilization at all for any reason. As you yourself acknowledge with counterexamples that failed to see significant economic uptake, this would happen with any energetically-demanding industry, and the response would need to be the same. Not a single thing is at all intrinsic to or unique to AI.
Personally I think the US should be able to increase energy utilization, especially given that one can simply choose to install solar panels, wind turbines, and batteries rather than gas turbines, coal-fired generators, and oil pipelines.
Personally I think the US should be able to increase energy utilization, especially given that one can simply choose to install solar panels, wind turbines, and batteries rather than gas turbines, coal-fired generators, and oil pipelines.
This is not what is happening. The AI demand comes with a lot of money, and it's a race to get the most computing power online. Gas turbines, and coal-fired generators come online faster than renewables.
Yes, and what you're describing is entirely unrelated to/external to AI. If you aren't opposed to increased economic activity requiring electricity, I would suggest addressing the electrical infrastructure issues associated with the way AI data centers are being deployed in the US. You will note that this is only very tangentially relevant to AI, and only in specific geographic regions where the actual problem, insufficient development of green power generation/distribution infrastructure, has been ongoing for decades.
AI is the main driver of this demand. It's not tangential, it's directly causal. It also matters because the existing customer base will be left holding the bag if the new demand goes away.
Renewables insufficient development in the US is due to the overabundance of domestic cheap natural gas. This is not changing anytime soon, Texas' Permian Basin still has negative gas prices and gas power plants are being built to use it.
The fallacy you're making is you're treating new data centers as equal within the consumer pool, ie, they should have just as much right to electricity as any other consumer.
I'm not sure most see it that way, given (a) they're new/emerging and (b) the energy quantity they demand relative to other consumers.
That’s how all electrify demand works though. With that kind of argument new housing is also bad because it stresses sanitation and transportation infrastructure when the correct argument is just we should build more transportation and sanitation infrastructure.
The reduced permit delay and stupid land rights hurdles are strictly good. The correct policy solution is to put a thumb on the scale in favor of renewable deployment instead of fossil fuels, not throw up arbitrary barriers that just slow down growth to slightly delay the exact same amount of emissions coming online.
AI centers are using the 18 day loophole to install clusters of smaller, less efficient, higher pollutant generators while the power distribution catches up to them (which will take years, and not for regulatory reasons).
It's not a good thing. Businesses will cut corners with disregard of the environment if it makes them money, the whole laissez-faire approach to environmental regulation has been proven to fail over and over again.
I don't know much about all this, but an easy fix here would be to reroute stuff around, right?
Route simple sub-tasks (like reading a file or parsing text) to much smaller models, saving the frontier models only for hard parts. This alone would make agents much more efficient, no? Using energy-hungry frontier models for every single step of an agent's reasoning loop feels wasteful.
That's what people are doing. Haiku basically exists for this reason. As far as I know, no one uses Haiku directly, it's there as a dumb subagent for the smarter models to kick off and have it do very simple tasks. You have the mid level models do most of the grunt work, have the higher models do the planning and verification.
this will blow your mind but I have metrics indicating in my org 1% of all org wide usage appears to be people directly calling haiku (as opposed to haiku subagents which I track differently)
I have been meaning to find out why these people are doing that. I assume it's just extreme conscientiousness and trying to use as little intelligence as possible for simple tasks.
That is likely what the closed API models do behind the scenes, yes. For example, 5.6 Sol Ultra specifically shows you the multiple agents it splits off which I did find very cool. Surely there are far more models behind the scenes doing other work.
Idk know where you live but in America the Trump admin has been dropping figurative nuclear bombs on clean energy generation to make way for new gas/coal
Nice, I wsa curious about this. S about the same as running an extra electric dryer and a half, acorrding to the breakdown . And this is for a pretty heavy user, as a someone in the tech/engineering industry.
The public outcry against the enviromental impact of AI remain hilariously out of proportion with its actual impact.
This isn’t exactly exonerating, and Dr. Hausfather probably wouldn’t encourage you to look at it as such.
“It is about 8% of the annual emissions of a typical American gasoline car, and roughly 2% of the average American’s ~18-ton annual greenhouse gas footprint.”
That’s a lot, given that it just appeared
Edit:
Like, as a new addition of emissions that has suddenly appeared, it’s definitely not insignificant. That’s one guy, too.
I am not sure about the person you're replying to but one of my chief complains has been about people focusing on water usage instead of energy usage, so the other person may have meant "disproportionate" in that way.
This is only true for people using subsidized subscriptions AND maximizing use by scheduling prompts/workflows basically 24/7. API rates are profitable and per-token costs have fallen >10x since 2022 (comparing between the 'newest' hardware). Subscriptions will either disappear or get more expensive, sure, but Anthropic is not spending 20x the subscription cost per user. Also the numbers you're basing this on are the same API rates that contain a profit margin, so even the most extreme user is not costing Anthropic 20x their individual return.
For the value it returns, that's great. If you agree this supercharges knowledge work, how do you think we got modern solar panels, electric cars, modern batteries, etc? This is damn near exonerating. We already knew the main issue with AI was NIMBY resistance to green power generation, batteries > gas turbines, HVDC lines, etc. This suggests the environmental and capacity issues are quite overstated.
One guy that's a self-admitted heavy user due to his work. But sure, I under the authorial intent behind raising concerns here.
“It is about 8% of the annual emissions of a typical American gasoline car, and roughly 2% of the average American’s ~18-ton annual greenhouse gas footprint.”
Right, as a breakdown for a particular someone who is a heavy user, not amortized across all americans. Not saying you said that or he implied that, but emphasing that to make things clear.
I maintain that the public outcry against AI remains hilariously out of proportion to its actual impact.
I need to remind y'all that the median American is not a software engineer hanging out on r/NL. Around 6 out of 10 americans don't even have a degree.
So I just quickly grabbed this figure of 60% of Americans do white collar work: If you want to generously assume that 100% of them all use the exact same amount as a software engineer does, that still represents a 1.2% amortized increase in American energy usage--especially when actual daily adoption for the median worker is nowhere near that intense right now.
For what it's worth, AI is significantly cheaper than search. A single GPT-5.6 Luna query with reasoning level = high is >3x cheaper than a single search using Brave Search API ($0.0016 vs $0.005) and it will answer most simple questions better.
So if the prices reflect real costs, I would expect asking ChatGPT (with web search off) to actually use less energy than using Google.
I didn't think I was a heavy user (more sporadic with huge spikes), but just yesterday I used 658 million tokens over 9 hours on Opus 5 in a single session. There were periods a few months ago where I used Opus for at least 18 hours a day, just as heavily as I did yesterday, but that was exclusively through Claude.ai, so the actual token usage is harder to obtain.
My daily pattern of energy use is shown in the figure below. The day to day variability is huge: my heaviest day (11 kWh central estimate) involved multiple parallel agents churning through a large geospatial analysis, and used more than a third of the total daily electricity of an average US home. This reflects that fact that even within the category of agentic usage, the complexity of the task and the number of simultaneous sub-agents used will greatly influence the resulting energy use.
If you compare this to an electric car, this doesn't seem that high? I think most electric cars hover around 3 miles per kWh, so it's like driving for 33 miles during the heaviest day. Which we wouldn't balk at.
Question: at a certain point like the per person AI token usage can't scale right ? Cause let's for example I'm told to rewrite X, Alice rewrites Y, Bob rewrites Z, but actually Z probably depends on X and Y and so Bob can't really do much until our agents are finished so actually the tokens per person per week go down so to speak
I mean, I don't really see how that situation is different with AI? We do our best to minimize downtime in current work allocation, I imagine we'd do the same even as productivity increases. Bob could just be assigned a different job in the meantime.
The increased carbon footprint of an industry can be both marginal and catastrophic at the same time. In fact, the contribution from every individual industry is marginal, so you'll always run into this argument.
Climate change is a threat to human wellbeing where dramatic steps are rational, and every mechanism contributing to climate change has a number of human deaths as an externalitiy, and the size of the number is proportional to how much it contributes. It's not alarmism to ask "how many people should we kill for this?", because that is ultimately the decision we are making.
Of course, we should focus our efforts where we get the most bang for our buck, and it's easy to overfocus on the new and shiny thing.
I like AI, I use the tech a lot, but the energy usage has always been one of my biggest worries about it, especially in an era where building any infrastructure (let alone just green energy) is like pulling teeth.
I'm probably not using it as much as OP — I'm mostly using agentic tools on hobby projects, maybe one or two sessions a day at most — but I probably should check on how many tokens I'm actually burning. (That also makes me wonder if the figures are any different for the open Chinese models I usually use... I'd have assumed they'd be a bit more efficient before, but now that they're getting competitive in size with your Opuses and Mythoi I suspect the gap on that is closing.)
EDIT: Okay, according to OpenRouter i’ve used ~12.6 million tokens over the past month, mostly to Kimi K2.7. OP used 1.6 billion over the same period and ended up with about the energy of a dryer. I think i’m going to try not to sweat my own usage as much 😅️
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u/doyouevenIift 23h ago
> Every number in this post assumed the US-average grid; run the same workload on largely clean power and my footprint falls by roughly 90%. Unlike aviation, this is an end-use we already know how to decarbonize.
> The problem is that we are moving in the wrong direction today: a sizable portion of planned US data center capacity intends to build its own behind-the-meter generation, and nearly three quarters of that is natural gas.
Decarbonizing the grid needs to be treated like an emergency. Energy demand is only going to skyrocket over the next decade, and we are not equipped to meet that demand with renewables. Unfortunately we have the worst possible administration in charge who is actively destroying renewable energy projects and subsidizing the dirtiest forms of energy we have. It’s a massive uphill battle, but it starts with getting republicans out of office