Comment by mrweasel
20 hours ago
I can't read the original Chinese text, but if it's revenue, then you still can't say anything about profitability. Housing and powering one GPU should be way less than $38 per hour, so there should be a profit on inference. If that profit can cover training new models we don't know, but it would appear to not be the case.
For the past year or two I think it has generally been agreed that inference is profitable, but the LLM business as a whole is not.
I seem to recall the leaked Liang Wenfeng speech gave a figure of 8-12(?) months of inference recouping the training costs of the model.
I think what he said was that 10 months of inference paid for the hardware it runs on (which may have a lifetime of a few years). I don't think he mentioned training/development cost.
You are correct, sorry. I should verify stuff like this before posting.
I assume they need these models to stop being replaced in 1-2 months though.
It's really hard to unpick, for example, energy prices might be heavily subsidized for the Chinese models.
But it's clear that it's not the money burning pit I think it was just a year ago.
China has a two tier energy system.
Consumer get the cheaper energy, while industry normally get the twice as expensive energy.
But for AI/Datacenters, there is a exception and they get the cheaper consumer level energy.
You need to take in account that the way China taxes is not the same as here in the West. And a lot more is put on the local governments regarding generating their own revenue (why there was so much building in China because those projects funded local government). A bit of a side topic lol. Its not so simple as they are making a loss on something because how its structured.
AI gets the cheaper tariffs then the rest of the industry, that is a fact. They simply have less energy profits on the AI energy. Now if you consider that subsidized or not, ... in both cases China is still making a profit.
What is overlooked is the massive amount of energy generation that China has and still keeps expanding. And that is a direct reflection upon why the prices for industry and consumers are so cheap. This buildout ironically had nothing to do with AI but was more about lower energy = cheaper industry production ... and a lot of buildout was also to build more independence from energy imports. They are not just throwing solar and wind turbines around like candy, the amount of reactors constructed and still under construction, ...
> China currently has 36 to 38 nuclear reactors under construction, maintaining the largest nuclear buildout in the world and accounting for roughly half of all global nuclear plant construction
So yea ... The AI in the west have a issue because it really does not matter if you cut China from Nvidia GPUs or advanced nodes, they compensate on the power level.
Edit: And a little extra, the irony is here in the West building nuclear is expensive as hell because we barely do one or two at the time. With a lot of lost expertise. China doing tons of them non-stop cuts down on the costs a lot.
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as if electricity for openai & anthropic isn't heavily subsidised
as if electricity for spacex wasn't literally illegally installed gas turbines polluting the air
Would that be due to the size of the models from DeepSeek or perhaps only for their distilled models? If it's for general purpose models that would crash the valuation of Anthropic and OpenAI, both who are struggling with profitabilitet to say the least.
Who said they need to distill anything? Deepseek is the most popular chinese model getting trillions of input tokens a day that have no ZDR availability. They specifically tell you that part of the deal is that they get your data to use however they want (atleast they're honest).
This idea that Deepseek needed to distil their way to success is nonsense. Its a great narrative for OpenAI and Anthropic to spread because Americans have been brainwashed for two decades into dealing with their own inadequacies by blaming things on scary asians stealing things.
In reality China is outworking and lapping most American companies. They produce 10 EEs to every 1 America produces. They are simply harder workers.
The West is cooked because we're too lazy to work hard and we'd rather make up stories about boogeyman who are stealing from us. The only thing we're good at now is killing people who economically challenge us.
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kind of on track with gemini's releases
google is a company that tries to make a point of having profitable subdivisions
What about sourcing the asset itself? It's like a factory is it not?
You pay for the asset (tenancy in a data center) and then you pay for housing, powering, cooling, etc.
I think it’s pretty clear from the cherry picked numbers at Anthropic.
Demand is the issue. Demand only spikes with a sota model release then in drops back down to unprofitable levels when factoring in training a new model and build out.
So your stuck in an unprofitable cycle of losing revenue when your not releasing sotas but losing profit when you are.
This goes back to googles original memo “there is no moat”.
Where in you can’t stop training sotas because you’ll lose customers to the next inference model above you instantly.
Google has seemingly defeated this by finding models cheap and good enough for their existing platforms resulting in a moat of distribution. Something OpenAI and Anthropic seems to lack.
Unless the money of the investors is going somewhere else...