Get back to me when there's an AI company that's actually profitable and we can compare their service and pricing.
Claiming that there's some small subset of their services (like inference per token) that's "profitable" doesn't mean anything when it relies on everything else that company is still paying for. If you could make money from it at current prices - why aren't they?
Otherwise it's just "how much they're willing to subsidize".
The problem with fixating on earnings as you're doing is that it's a bad metric for a growth company. COGS is much more important. What you're doing is setting it up so every growth company is terrible until they've matured into a 20 year old company. That's obviously dumb.
There is probably going to be a quarter or two of profits when the prices dramatically increase. Vibe coding techbros are hooked on the Iron Lung and may not want to get off.
At my work are multiple developers bragging about overnight AI usage to solve problems hands off. Yes they are wasting money and resources but the fad is here. People be vibe coding for now.
In like 6 months when all the costs need to be paid and the prices go up, we will see if these companies stay profitable. But I'm of the opinion that the vibe coding tech bros are more than enough to sustain a short or even medium term profit for these companies. Just on fad-energy alone (see OpenClaw)
The fad probably collapses soon after. I hope anyway, the waste I see is nauseating.
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I dunno where this is all going. But I do have faith in human ingenuity still. Things are changing, possibly for the worse, but we need to make the best of it.
The worst of behaviors is wasteful and blatant fraud. There's something useful here though.
On OpenRouter there are 11 third-party inference providers hosting DeepSeek V4 Pro right now, of which 8 are US-based and 7 of those have zero data-retention policies (which I mention to rule out any claims of "oh they're making up the money by logging all your data"). This is a 1.6T-A49B model, so a bit bigger than Sonnet (~2/3rds the size) and a bit smaller than Opus (~3x as large). These third parties are almost perfectly interchangeable via OpenRouter as a marketplace, so they have no incentive to offer any sort of "growth pricing" below costs, and they serve it at $3.48/Mtok out.
Kimi K2.6 is 1T-A32B with a slightly less computationally efficient architecture, and is served at around $3.50/Mtok out by 9 US ZDR providers.
Unless you think that either the generally accepted size estimates for Anthropic/OpenAI models are wildly off or those companies are a lot worse at serving models efficiently, Anthropic and OpenAI are probably making around 5-8x margins on their API costs.
The cost of training new models is of course a major factor not counted here. Depending on how you want to think about that this may or may not make them net profitable. I remember one of those CEOs gave an interview a while back where they described it as a series of independent investments, where each model they train is net-positive in revenue by EOL just from its own inference, but I don't know whether that's still true or not.
Regardless, the point is that if they stopped training new models today, both Anthropic and OpenAI are making incredibly generous profits on their API inference.