This is most definitely not widely understood. We still don't know yet. There's tons of discussions about people disagreeing on whether it really is profitable. Unless you have proof, don't say "this is widely understood".
Even at $200 monthly subscription that kind of stuff burns through tokens at a rate where it's very difficult to believe that they are even breaking even, never mind profit.
We need to see the cash flows.
I don't think it suggests a profit, but rather a _hope_ for a _future_ profit, and a commitment to a strategy that may or may not pan out. Capitalism rewards those who are early to the party and commit to their bit.
Also while datacenter-based scaleout of a model over multiple GPUs running large batches is more energy efficient, it ultimately creates a single point of failure you may wish to avoid.
If you add in the cost of training, it’s not profitable.
Not including the cost of training is a bit like saying the only cost of a cup of coffee is the paper cup it’s in. The only way OpenAI gets to charge for inference is by selling a product people can’t get elsewhere for much cheaper, which means billions in R&D costs. But because of competition, each model effectively has a “shelf life”.
Obviously that doesn’t help them turn a profit, until they can stop growing training costs exponentially.
So it’s really a race to see whether growth in revenue or training costs decelerates first.
Vast amounts of capital have been poured in, but they continue to raise more. Presumably because they need more.
Is the capital being invested without any expectation of ROI?
I love the whole “they are making money if you ignore training costs” bit. It is always great to see somebody say something like “if you look at the amount of money that they’re spending it looks bad, but if you look away it looks pretty good” like it’s the money version of a solar eclipse
But if they're losing money on inference, they will lose more money when people use their services more. There's no way to turn that around at that price.
Are they? Or are they just saying that to make their offerings more attractive to investors?
Plus I think most people using agents for coding are using subscriptions which they are definitely not profitable in.
Locally running models that are snappy and mostly as capable as current sota models would be a dream. No internet connection required, no payment plans or relying on a third party provider to do your job. No privacy concerns. Etc etc.
Where on earth do people get this idea? Subscriptions that are based around obscure, vendor defined "credits" are the perfect business model for vendors. They can change the amount you can use whenever they want.
It's likely they occasionally make a loss on some users but in general they are highly profitable for AI companies:
> Anthropic last month projected it would generate a 40% gross profit margin from selling AI to businesses and application developers in 2025
and
> OpenAI projected a gross margin of around 46% in 2025, including inference costs of both paying and nonpaying ChatGPT users.
This assessment might change if local AI frameworks start working seriously on support for tensor-parallel distributed inference, then you might get away with cheaper homelab-class hardware and only mildly unreasonable amounts of money.