alt Hacker News> they aren’t even profitable
Depends on your definition of profitability, They are not recovering R&D and training costs, but they (and MS) are recouping inference costs from user subscription and API revenue with a healthy operating margin.
Today they will not survive if they stop investing in R&D, but they do have to slow down at some point. It looks like they and other big players are betting on a moat they hope to build with the $100B DCs and ASICs that open weight models or others cannot compete with.
This will be either because training will be too expensive (few entities have the budget for $10B+ on training and no need to monetize it) and even those kind of models where available may be impossible to run inference with off the shelf GPUs, i.e. these models can only run on ASICS, which only large players will have access to[1].
In this scenario corporations will have to pay them the money for the best models, when that happens OpenAI can slow down R&D and become profitable with capex considered.
[1] This is natural progression in a compute bottle-necked sector, we saw a similar evolution from CPU to ASICS and GPU in the crypto few years ago. It is slightly distorted comparison due to the switch from PoW to PoS and intentional design for GPU for some coins, even then you needed DC scale operations in a cheap power location to be profitable.
Replies
> they (and MS) are recouping inference costs from user subscription and API revenue with a healthy operating margin.
I didn't find any reliable sources about OpenAI. All sources that I could find state this is not true -- inference costs are far higher than subscription fees.
I hate to ask this on HN... but, can you provide a source? Or tell us how do you know?
> but they (and MS) are recouping inference costs from user subscription and API revenue with a healthy operating margin.
As far as I am aware the only information from within OpenAI one way or another is from their financial documents circulated to investors:
> The fund-raising material also signaled that OpenAI would need to continue raising money over the next year because its expenses grew in tandem with the number of people using its products.
Subscriptions are the lions share of their revenue (73%). It's possible they are making money on the average Plus or Enterprise subscription but given the above claim they definitely aren't making enough to cover the cost of inference for free users.
https://www.nytimes.com/2024/09/27/technology/openai-chatgpt...
It was my impression that OpenAI was struggling to make money on their $200 pro subscription, because they've underestimate how much people would use it (https://www.theregister.com/2025/01/06/altman_gpt_profits/).
So I do question if OpenAI is able to make a profit, even if you remove training and R&D. The $20 plan may be more profitable, but now it will need to cover the R&D and training, plus whatever they lose on Pro.
Didn’t it just come out they are losing money on the pro subscriptions?
I am paying for o1 Pro but since Deepseek R1 came out I stopped using it. So there goes $200/mo of their revenue ;)
Thanks for the detailed breakdown. This is an important nuance to my short reply.
Are they spending $10B/year on training?
They will have an endless wave of commoditization chasing behind them. NVIDIA will continue to market chips to anyone who will buy... Well anyone who is allowed to buy, considering the recent export restrictions. On that note, if OpenAI is in bed with the US government with this to some degree, I would expect tariffs, expert restrictions, and all of that to continue to conveniently align with their business objectives.
If the frontier models generate huge revenue from big government and intelligence and corporate contracts, then I can see a dynamo kicking off with the business model. The missing link is probably that there need to be continual breakthroughs that massively increase the power of AI rather than it tapering off with diminishing returns for bigger training/inference capital outlay. Obviously, openAI is leveraging against that view as well.
Maybe the most important part is that all of these huge names are involved in the project to some degree. Well, they're all cross-linked in the entire AI enterprise, really, like OpenAI Microsoft, so once all the players give preference to each other, it sort of creates a moat in and of itself, unless foreign sovereign wealth funds start spinning up massive stargate initiatives as well.
We'll see. Europe has been behind the ball in tech developments like this historically, and China, although this might be a bit of a stretch to claim, does seem to be held back by their need for control and censorship when it comes to what these models can do. They want them to be focused tools that help society, but the American companies want much more, and they want power in their own hands and power in their user's hands. So much like the first round where American big tech took over the world, maybe it's prime to happen again as the AI industry continues to scale.