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The GPU's used for AI have significantly higher utilization rates than gaming GPU's...

Here's some napkin math:

H100: 61% utilization / 700W ~ 3.7MW/year

RTX 3080: 10% utilization / 320W ~ 0.27MW/year



How many AI users are served using a single H100 per time, and how many gamers are served using a single 3080 per time? How many gamers are simultaneously running a 3080 or equivalent for their entertainment?


You can't compare those things very easily.

If you're only talking about the GPU's used for inference, then that's a different story. Not nearly as much hardware is required for inference.

But the number of GPU's needed to train models is in the tens of thousands, and there are rumors that some shops (Meta) are already using 100k+ GPU's, just for training.

Those are likely all/mostly H100s, running at least 60% of the time. Consider that OpenAI, Anthropic, Google, Meta, Tesla, X.com, etc. are all within an order of magnitude of each other in terms of compute.

For arguments sake, that's 6 companies approaching 100K H100's worth of compute for their next gen models.

Now consider that GPT4 used roughly 100x more compute to train, compared to GPT3. And GPT5 is rumored to follow this trend, using 100x more compute than GPT4. Extrapolating, GPT6 might also use 100x more compute than GPT5.

Even if the next generation of AI GPU's are 10x as powerful as the H100 for the same amount of electricity, the next generation of models would need 10x as many GPU's (and thus, 10x as much electric demand).

Extrapolate that to GPT7, 8, 9 etc. And you can see why people are worried about the power usage.

This isn't even theoretical. As mentioned in this thread already, these companies are signing deals to buy all the capacity of power plants in some areas.


>100k+ GPU's, just for training.

That's a tiny drop in the sea of the almost 2 billion PC gamers [0], and hundreds of millions of gaming consoles [1] in the world. Not to mention the energy required to manufacture all that hardware. Plus the datacenters required for online gaming, which must also be considerable.

It's weird to be concerned about power usage of AI, but turning a blind eye to the massive amounts of power required by the gaming industry.

[0] https://www.statista.com/statistics/420621/number-of-pc-game...

[1] https://en.wikipedia.org/wiki/List_of_best-selling_game_cons...


I think it's weird to ignore that every GPU used for AI equates to 10-50 gaming GPUs (10 if you assume every gamer has a 3080, which they don't), and that the number of GPUs used for AI is 10x every 18-24 months.

It's not that AI uses too much power today, it's that at the current trend, it'll be using somewhere between 100x and 1000x as much power by 2030/2035. Which would place it between 2-20% of total power consumption.


Where does this "10-50" figure come from? A quick google search says a H100 draws 700 W, while a 3080 draws 320 W.

AI provides tangible value to businesses and private users beyond mere entertainment. We'll see how much power it consumes in the future, and where that power comes from.


I did the math in previous comment that you already replied too..

"The GPU's used for AI have significantly higher utilization rates than gaming GPU's... Here's some napkin math:

H100: 61% utilization / 700W ~ 3.7MW/year

RTX 3080: 10% utilization / 320W ~ 0.27MW/year"

H100 uses at least 10x as much power as a 3080 over it's life time. And most gamers aren't playing on 3080's.


The difference here is between potential energy use and actual energy use. AI chips as well as other server chips are in use most of the time. But if I sell 1 billion gaming chips, these chips will be in use a small fraction of the time.


Yes, AI users are being served by much more than one GPU at a time.

Which is why the power used is so much higher than a single gaming pc


Thousands of users are being served by those GPUs. A gaming PC has one user.

I can't believe I have to point this out on HN of all places.


Indeed. But how many gaming GPUs are out there in the world?




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