Would that be the most expensive single thing ever built? The ISS cost around $150B and is commonly said to be the most expensive single item, but that does include running costs.
cmiles8 1 hours ago [-]
Nvidia is turning into a savings and loan company that happens to design computer chips on the side. What could possibly go wrong.
HDBaseT 1 hours ago [-]
The loans will just take longer to repay. There is a market for Anthropic & OpenAI, it just likely doesn't have the 200B profit each year required for the maths to make sense.
If shit hits the fan, the companies collapse, then Nvidia gets their money from the investors anyways.
jacquesm 52 minutes ago [-]
NV might end up owning them.
47 minutes ago [-]
u1hcw9nx 4 hours ago [-]
I would like to see the numbers.
If Nvidia sells hardware for $100B with 75% cross margin, and provides $50 billion in backstop for that same hardware, it would be still be nicely profitable deal ($25B) if the backstop capacity would be a total write-off recovering $0. Reselling that capacity in some large discount below already low backstop price would increase the profits.
It's all those pension funds, sovereign wealth funds and Softbank getting into that $500 billion deal that will be hurt.
ColdStream 2 hours ago [-]
Pretty much, I have said it for a while now, Softbank and Oracle are the ones I would be worried about. Both of them have put their companies wealth behind this, if it goes down so will they.
Others have played it fairly smart in terms of insulating potential issues.
throwaway27448 2 hours ago [-]
A better world is just a few steps away
pjjpo 2 hours ago [-]
SoftBank has always managed to squeeze by after every mistake selling some early huge wins Alibaba, Nvidia, arm. Wonder if they still have any of those left in the back pocket.
jgalt212 1 hours ago [-]
Indeed, Masa has more lives than a cat.
NewJazz 4 hours ago [-]
Businesses aim to make the most profit possible with their resources. If they can make a 25% margin that is good, but if they can turn around sell thr same thing for a 50% margin, that is much better.
Basically what i am saying is maybe there is a better buyer than openai.
senor_digimon 2 hours ago [-]
This is probably a lot more related to the fact they want to make GPUs an asset class. Nvidia is banking on the fact there will be an entire market that will guarantee whatever anyone needs.
Taikhoom10 42 minutes ago [-]
This is meaningless in the long run; the broader problem is the constant circular financing and "Fake profits".
It is not the first time, either; the capital cycle will prevail.
All economics is circular financing, that's how it works.
You pay Apple for a MacBook, Apple uses it to develop a better MacBook.
What goes wrong is leverage. We haven't seen much hint of the 10x leverage kind of deals that brought down the house in 2008.
Taikhoom10 18 minutes ago [-]
Uh no, NVDIA helping startups get financing so they can buy NVDIA chips is inherently damaging because eventually the debtors will not help with the financing and startups will not be able to buy chips.
fooker 14 minutes ago [-]
Again, this is how all of economics works.
A Toyota dealership arranges a loan for you. Through a bank for a used vehicle, sometimes through Toyota itself for new cars.
A house builder will routinely take on part of the loan providing burden to get some of the interest.
Even someone selling you their thirty year old house will often provide seller financing.
You may have ideological options against this, which is fine. There are billions of people, for example that are fundamentally opposed to the idea of interest. But like it or not, this is how it has worked for a last ~500ish years.
13 minutes ago [-]
behnamoh 3 hours ago [-]
In other words: the investments that were never going to happen are not going to happen.
ColdStream 2 hours ago [-]
While it is true they haven't lost anything, it does signal to shareholders, potential share holders and current VC's the direction of things.
4 hours ago [-]
Noaidi 4 hours ago [-]
The Möbius strip of AI financing continues…
sidewndr46 3 hours ago [-]
it seems much more like Relativity by M. C. Escher where no one is quite sure how to exit without bringing everything down with them?
gymbeaux 3 hours ago [-]
What would happen to Nvidia, Anthropic, OpenAI, if tomorrow someone released an open weights model on HuggingFace that matched performance and accuracy of Opus 5 running locally on an RTX 5070? That won’t happen tomorrow, but it will likely happen someday… what’s the plan beyond “don’t be the one holding the bags?”
jimbo808 55 minutes ago [-]
There’s no reason to assume frontier-level intelligence eventually collapses all the way onto a midrange consumer GPU. In fact, there are quite a few reasons not to assume that (information-theoretic constraints, etc).
fooker 17 minutes ago [-]
There's no information theoretic constraint we know of that prevents this. You will almost surely win a Turing award if you can prove this.
It's almost a given that whatever is frontier intelligence today will run on a potato in a few years.
jimbo808 11 minutes ago [-]
Kinda silly to follow your “prove it” challenge with an absurd claim you most certainly cannot prove, much less support with evidence.
christophilus 31 minutes ago [-]
But, it could happen for a coding-focused model, or an accounting-focused model, etc. most tasks only need a subset of the total model to be done effectively.
fooker 19 minutes ago [-]
> on an RTX 5070
RTX 5070 prices go up ~N times. Nvidia makes more money because it's easier to make these things than it's to make a GB300.
ColdStream 2 hours ago [-]
Those companies will be quick to copy the tech, inference cost would plummet and there is a greater chance that these companies could make it to solvency. At least in the short term. Long term it might not be so great as consume hardware catches up.
lisplist 1 hours ago [-]
If you could run Opus 5 on a 5070 then the labs must have achieved RSI at that point
martinald 2 hours ago [-]
Nothing would really change IMO? 99% of users don't have anything like a RTX5070 (mobile especially).
Even if it did, it still doesn't make much economic sense running a model locally vs on a datacentre.
For example, I managed to just about squeeze a Q2 quant of Qwen 3.7 27b on my 9070XT. I get around 60tps decode (slightly faster prefill). _but_ it uses 300W of power to do so. At UK electricity rates of 30c/kWh this works out at something like 42c/MTok. I can get far far better models on openrouter cheaper than that, plus I'm not horrendously constrained on context length.
protocolture 2 hours ago [-]
I dunno a lot of things said about AI economics sound like an IBM executive making reassuring statements about their terminal/mainframe business before the personal computer took off.
Like even if you run it in a datacenter in this scenario, you could do it on a cheap GPU instance in Azure, you still wouldnt need OpenAI or Anthropic specific clouds.
>uses 300W of power to do so.
There are plenty of people with phat electricity pipes in their on prem server rooms that have been vacated for cloud. Companies who want the benefits of AI but dont want the risk of sending their data to foreign API endpoints.
nl 2 hours ago [-]
It seems very very unlikely that an Opus 5 matching local model that runs on a 5070 will be released within the next 5 years (I don't want to say "ever").
If it does happen then NVidia will sell a lot of 5070s though!
milkshakes 2 hours ago [-]
inference is the cheap part; training is expensive. what compute infrastructure would train this mythical magic model?
ElProlactin 1 hours ago [-]
Exactly. If OpenAI and Anthropic didn't have to train new models, they'd (probably) be instantly profitable and with good margins.
drivebyhooting 2 hours ago [-]
Inference time scaling means whoever had the most compute has the highest intelligence model.
d_sem 2 hours ago [-]
I guess I'd like to understand the technical reasoning on how you think an how an Opus 5 could over time fit on an RTX 5070.
formvoltron 3 hours ago [-]
wobble wobble
nian2326076 4 hours ago [-]
[flagged]
2773738384 4 hours ago [-]
[flagged]
Rendered at 02:13:10 GMT+0000 (Coordinated Universal Time) with Vercel.
There's a release from DoE about it: https://www.energy.gov/articles/fact-sheet-department-energy...
That's a horrible amount of gas energy generation.
https://www.datacenterdynamics.com/en/news/openai-in-talks-t... has more details. The whole campus build could be as much as $500B.
Would that be the most expensive single thing ever built? The ISS cost around $150B and is commonly said to be the most expensive single item, but that does include running costs.
If shit hits the fan, the companies collapse, then Nvidia gets their money from the investors anyways.
If Nvidia sells hardware for $100B with 75% cross margin, and provides $50 billion in backstop for that same hardware, it would be still be nicely profitable deal ($25B) if the backstop capacity would be a total write-off recovering $0. Reselling that capacity in some large discount below already low backstop price would increase the profits.
It's all those pension funds, sovereign wealth funds and Softbank getting into that $500 billion deal that will be hurt.
Others have played it fairly smart in terms of insulating potential issues.
Basically what i am saying is maybe there is a better buyer than openai.
It is not the first time, either; the capital cycle will prevail.
https://s-1.vercel.app/posts/the-capital-cycle-theory/
You pay Apple for a MacBook, Apple uses it to develop a better MacBook.
What goes wrong is leverage. We haven't seen much hint of the 10x leverage kind of deals that brought down the house in 2008.
A Toyota dealership arranges a loan for you. Through a bank for a used vehicle, sometimes through Toyota itself for new cars.
A house builder will routinely take on part of the loan providing burden to get some of the interest.
Even someone selling you their thirty year old house will often provide seller financing.
You may have ideological options against this, which is fine. There are billions of people, for example that are fundamentally opposed to the idea of interest. But like it or not, this is how it has worked for a last ~500ish years.
It's almost a given that whatever is frontier intelligence today will run on a potato in a few years.
RTX 5070 prices go up ~N times. Nvidia makes more money because it's easier to make these things than it's to make a GB300.
Even if it did, it still doesn't make much economic sense running a model locally vs on a datacentre.
For example, I managed to just about squeeze a Q2 quant of Qwen 3.7 27b on my 9070XT. I get around 60tps decode (slightly faster prefill). _but_ it uses 300W of power to do so. At UK electricity rates of 30c/kWh this works out at something like 42c/MTok. I can get far far better models on openrouter cheaper than that, plus I'm not horrendously constrained on context length.
Like even if you run it in a datacenter in this scenario, you could do it on a cheap GPU instance in Azure, you still wouldnt need OpenAI or Anthropic specific clouds.
>uses 300W of power to do so.
There are plenty of people with phat electricity pipes in their on prem server rooms that have been vacated for cloud. Companies who want the benefits of AI but dont want the risk of sending their data to foreign API endpoints.
If it does happen then NVidia will sell a lot of 5070s though!