Comment by fooker
10 hours ago
> Even if the output is like 5-6 tok/s, that might be usable for some purposes.
You'll spend ~100x more on electricity than the API cost to have it run on someone else's GPU at several hundred tokens per second.
I think some sort of extreme data privacy requirement is the only situation that justifies this, but the intersection of {needs absolute data privacy, needs to run SOTA model, cannot afford GPUs} is really really narrow. I wouldn't be surprised if this is an empty set.
There are a number of use cases where sending the contents of your context and prompts (and the resulting output) to a 3rd party service is off the table as an option, and people will compromise speed for data sovereignty. And not everyone's electricity is equally expensive, I pay about $0.075 USD per kWh. It would for example cost me about $48 a month of electricity (not counting cost of cooling) to run a quad socket Dell R940 for a month.
That's an unusually low electric rate for the US - way below the lowest state average which is Idaho at 12.4 cents. It's certainly possible that you are getting 7.5 cents including delivery, but I've had friends say that they're "getting 13 cents per kWh" here in Massachusetts, but that's just the supply rate and the delivery is another ~18 cents.
There are parts of states like Grant County Washington that have cheap hydro power, but it's very rare for power to be that cheap in the US. Even if this applies to you, it won't apply to the vast majority of people on here who will have electric rates 2-4x higher.
Average electric rates by region:
https://www.eia.gov/electricity/monthly/epm_table_grapher.ph...
Not the parent, but here is one location that has rates in that range in the U.S.
https://casscountyelectric.com/rates
> Pacific Contiguous 26.1 cents
This is a bit misleading, because it's combining the 50 cents/kWh from California with 15ish cents/kWh in Oregon and Washington. Seattle City Light, for example, charges 13.38 cents/kWh on flat rate pricing, and far less with time-of-use billing (8 cents/kWh on off-peak).
If you run off solar with battery backup, you can achieve lower than those rates! Look at Time of Use rates. The super off peak rates instantly become the max price point once you pair TOU with Solar + battery.
A lot of people quoting low rates are also just referring to their off-peak rate. This is pretty common in EV discussions. It's not exactly a fair argument there, either, because the flip side of having an off-peak rate is that the on-peak rate is usually quite a lot higher. So the true effective rate is a bit higher, somewhere in the middle depending on usage pattern.
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They are most likely not based in the US, but converting to USD to make comparison easier.
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can send safely context if there’s confidential computing ala my site https://trustedrouter.com/
How do you prove you are running exclusively on Nitro enclave instances or GCP confidential spaces?
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Great, so the other member of the set matters for you more than cost.
Do you actually need to run the state of art model at 5 tokens per second instead of a qwen or whatever 7b or 30b model at 100 tokens per second?
Do I really need to? No, not really. The 27B full density, 35B MoE, 70B and 122B models I have in use get me 95% of the way there on a lot of things. Particularly when dealing with languages and systems where I have at least an intermediate level of knowledge on, to know whether something is going down a dead end, using a wrong method, metaphorically chasing its tail, or is producing valid output.
On the other hand, would it be cool to also have a really big thing as an ancillary tool that I could throw a request into opencode before going to bed, let it crank away and take a look at what it's done 7 hours later? Yeah, particularly if I (very much an unknown quantity at this time) could be confident that it builds high quality, syntax valid, appropriately commented and not absurd code.
>Do you actually need to run the state of art model at 5 tokens per second instead of a qwen or whatever 7b or 30b model at 100 tokens per second?
Some people like doing things they want to do. Do I actually need to buy expensive pigments from europe to make paintings of flowers? My camera produces a much more accurate representation.
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The whole mentality of thinking one knows better than another about what they need causes infinitely more problems than it solves.
It's completely academic. At 5tok/s you can process 13 MTok per month at concurrency 1. I use 5 BILLION tokens per week when coding.
Yeah. At 5 tok/second, you're talking about around $195 worth of output tokens per month. There is no way I can run a usable K3 model for $195 a month of capex, opex, or any-kind-of-ex.
Qwen 3.6 is another matter. Paying provider rates for the amount I run locally would put me in the thousands of dollars. So that's very practical to buy a Macbook instead, plus an RTX card, and so on.
As someone who has worked in two industries that are at the maximal end of data sensitivity and privacy this comes across as a tinfoil hat issue not a real business requirement. In such cases we've always found ways to trade dollars for the privacy we need without having to run our own inference at excruciating slow speeds.
Do you mean by trading dollars for the privacy you need as:
a) Contracting with a third-party independent inference provider who will run your choice of model on fast hardware that they own, with all appropriate data security/privacy/contractual/compliance protection in place
or
b) Contracting with the original creators of the model to run inference via their API and with assurances that all the same data protection is in place
or
c) Spending the money to buy your own inference hardware to run it on something you fully own/control at proper usable speeds?
Edit: Everything I've been writing in this thread is mostly within the context of being able to evaluate K3 and its usefulness to be self-hosted as a preliminary proof of concept or test of feasibility of a new thing, such as on <$20,000 of server hardware, before proceeding to spend 300-400k on GPU-related hardware, or external third party services/ongoing billing.
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There are regulated sectors in countries where data sovereignty is important enough that the sector sticks to air-gapped on-prem hardware and does not use cloud services at all. They have the dollars to pay for more than what it would cost to run on the Cloud.
Interesting. So nobody would have had a problem with you running stuff on Chinese AI providers?
I have some inference I simply don't want to run on OAI, Anthropic, or Google because I don't want to run afoul of their "rules" and end up with a banned account, and this situation is only getting worse when it comes to doing fairly basic tasks like trying to secure your app against security problems.
Having worked in / adjacent several such industries, a lot of the question depends on scale.
A trillion-dollar business can easily trade dollars for the privacy. A business with $1M to spend won't even get a phone call with OpenAI or Anthropic, who were the only* previous players in town for doing this.
Worst-case example: Bootstrapped startup working in military.
It's also the case that an open model enables many more intermediate-cost solutions. E.g. providers certified for specific applications, on-prem rentals, etc.
* Omitting Azure, which gives some privacy for some $$$ on their models, but not at the level of high-security.
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There are a number of use cases where sending the contents of your context and prompts (and the resulting output) to a 3rd party service is off the table as an option, and people will compromise speed for data sovereignty.
Are there? At the highest levels of defense and law, AWS and Azure are used.
Having tried selling some of these entities on doing things in-house, there seems to be little interest.
> Are there? At the highest levels of defense and law, AWS and Azure are used.
This is certainly true if the user is an American company. You could look at the European initiatives to run this stuff on hardware they own in facilities they own and control within the borders of Europe for a counter-example.
Such as: https://www.google.com/search?client=firefox-b-d&q=schwarz+s...
https://www.dutchnews.nl/2026/04/government-turns-to-german-...
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I’ve priced it out: max $135/month to run a dual Xeon 2U server with 3T RAM & 2x 22 core Xeon Gold. It’s the 2x 750W power supplies that ultimately determine opex. My power costs $0.124/kWh, the $135 assumes drawing maximum power continuously, and in that case, I can probably offset my heating bill a little bit in the winter, so maybe effectively a little bit lower.
I don’t know if that’s 100x more than I’d pay (opex-wise) with an nvidia setup, but I can say the one-time capex is a great deal cheaper. Avoiding VRAM and DDR5 (fast DDR4 should be OK) are the biggest cost savers. ECC RAM is worth the extra price. General datacenter-quality hardware has less price sensitivity, and plenty of bang for your buck.
Keep in mind that just because it has dual 750W power supplies that doesn't mean it's what its load will be, for a full CPU loaded wattage figure you'd need basically a pair of kill-a-watts plugged in inline on the feed for each poewr supply and then run stress-ng with artificial cpu stress on all cores for an hour.
Under heavy inference load you will find that the cpu usage is actually less as the bottleneck is the RAM bus speed. An older 2U rack server that is 600W load (typically a 1+1 power supply server when plugged into two kill-a-watt would show 300W on each, equal load balancing) when maxed out with stress-ng might be only 450W total running inference.
If you have 600kWh used in a month by running something 24x7 and your power is $0.15 a kWh, that's more like $90/mo (not counting cooling or any ancillary costs for the environment where it's in).
If you actually were running this thing at 80% or 100% load, then the first thing you'd want to is get a better PDU and then connect your servers to that (48V DC).
One of the problems in buying used/refurb x86-64 rack servers for test and development/proof of concept environment, is that by volume in the market, there's not that many -48VDC power supplies going around, because maybe 5-10% of enterprise customers buy them. Resulting in many fewer units ending up on the resale market.
The options for AC power supplies for servers with 2 or 4 load sharing redundant power supplies are a lot greater. If you were buying all new hardware and starting from a clean sheet of paper design with lots of money to spend, absolutely. At that point also start looking at higher voltage DC distribution stuff related to open compute platform and 800VDC.
But if I were trying to make the absolute most use of $20,000 to put together a 3TB RAM server (48 x 64GB DIMMs), it would likely end up AC powered.
(Context: Parent comment was edited after I wrote this comment)
Where in the world are you finding that much RAM in a racked server for $200/month?
I think he means electrical bill at his estimated wattage load of the server and his known kWh cost, not rented server/hosting cost.
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At my house. I have 5Gbps fiber and could pay for 10 or 25 if I need it.
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One aspect of this is cyberattack proliferation by way of "Hey boss, I saw this TikTok that says if you let me invest [a tiny piece of the neighborhood's profit|our militia's budget] into some RAM, I could get a fully autonomous cyber operation up and running that pays for itself via ransomware etc. within weeks. You like it, we upgrade to something that can work even faster. We don't need the hacker guy from Swordfish with fifty monitors, we just need my cousin who likes building gaming PCs."
That's a world that I don't think we're ready for.
A similar world is already here.
Young men 14-?? already compromise and attempt to extort organizations daily, sometimes cluelessly from western nations, often not. It doesn’t have to be gangs when the home country doesn’t care / isn’t technologically or culturally developed.
Already seeing AI-written payloads and frameworks in the wild. I think it’ll turn out that AI won’t build you a maintainable ERP but it can create C2 networks, exploit POCs or even 0-days potentially, and let kids make their own ransomware tooling. Then we’re dealing not with a handful of cybercrime tool makers but a generational problem.