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Brad Gerstner confirmed that tokens aren't being sold at a loss. Whatever the formula, API + Subscription split, the companies are making a profit on net token

• iLoveOncall 5mo ago
  He's an interested party. His investments are worth a lot more if he says that tokens are sold at a profit. I don't understand how anyone would trust him?
  • wqaatwt 5mo ago
    There are plenty of various providers on OpenRouter serving very large Chinese models like GLM for a fraction of what OpenAI/Anthropic. Presumably they are making a profit. It’s unlikely that Claude is proportionally that bigger and more expensive to serve so profit margins on inference must be pretty decent
    • sarchertech 5mo ago
      Do we know they are making a profit though? They could be subsidizing use to build market share the same way. They might not have billions, but at the volumes they are selling maybe they’ve got the cash to do it. Even if they are “profitable” how many Uber drivers are “profitable” because they aren’t correctly calculating asset depreciation. Maybe these guys are doing the same thing. Maybe it’s a lot of people who already had GPUs for crypto mining, and they’ve moved over to this, so that if they need to grow and buy new GPUs the costs would dramatically grow.
      • mvanbaak 5mo ago
        also, it's very much possible that the chinese companies get heavy investments from the state. Since it's very hard to get this info we have no idea wether they really make a profit or not.
        • throwaway-away 5mo ago
          I agree, and find that very plausible. I mean, for the CCP a few billions to subsidize domestic AI companies is a tiny investment with a potential huge payoff. It prevents (or at least make it harder for) US companies to build a monopoly on LLM tech and it could help popping the bubble which would weaken the US economy. In fact, if I remember correctly, the AI infrastructure build-out is what is keeping the US from a technical recession.
        • wqaatwt 5mo ago
          The R&D is of course subsidized but a lot/most(?) of these inference providers are not Chinese
          • sarchertech 5mo ago
            If the Chinese companies are subsidized anyone who wants to compete with them has to match their price.
      • wqaatwt 5mo ago
        > subsidizing use to build market share the same way To an extent maybe, but that market is almost entirely commoditized already. Besides Cerebras and maybe Groq (which already charge a slight premium) all the other providers are more less interchangeable. > Maybe it’s a lot of people who already had GPUs for crypto mining I’m not sure the type of GPUs that were most popular for crypto are at all useful for LLMs?
        • sarchertech 5mo ago
          >interchangeable If there’s a few providers subsidizing, that’s the price ceiling. Everyone who wants to compete has to subsidize. Now if this market had been operating for years, I’d say that it’s likely all these companies are profitable or close to it. But the market is so new and there’s so much hype, I find it very plausible that none of these guys are making a profit and they all hope to just hang in until all the subsidies go away. > I’m not sure the type of GPUs that were most popular for crypto are at all useful for LLMs? There’s some overlap. I’ve definitely read about people repurposing.
• mpalmer 5mo ago
  This is the sort of uncritical thinking that inflates bubbles in the aggregate.
  • wqaatwt 5mo ago
    Compared to the inference prices for open models it’s highly unlikely OpenAI/Anthropic are not making decent amounts of money from inference. How many times bigger could Opus be than GLM or Kimi, it’s certainly not proportional to the price
    • mpalmer 5mo ago
      it’s highly unlikely OpenAI/Anthropic are not making decent amounts of money from inference. Based on what? Why are we all whispering about how profitable all this is? It is the absolute last thing these firms would keep secret.
      • JumpCrisscross 5mo ago
        > Why are we all whispering about how profitable all this is? Nobody is whispering about anything. Everyone is loudly assuming what's convenient for their thesis. Even if you have access to the books, the accounting isn't straightforward–there are yet insufficient data for a meaningful answer. > It is the absolute last thing these firms would keep secret If you find an optimisation strategy that you don't think your competitors have, you absolutely keep your margins secret for as long as possible. Knowing something is possible is the first step to making it so.
        • kddkkdisis 5mo ago
          [dead]
      • wqaatwt 5mo ago
        Based on what I said. If e.g. Sonnet (assuming it’s significantly smaller than Opus) is unprofitable why are there a bunch of inference providers on OpenRouter serving very large models way cheaper? They don’t have a pile of money to burn for no reason.
• m0llusk 5mo ago
  That isn't enough. Over time the need for growth and increasing profits will squeeze existing margins.
  • riddlemethat 5mo ago
    Open source models apply pressures on the low end of the market. The paid models are so much better that they can charge based on value for enterprises.
    • rglullis 5mo ago
      Have you used any of the recent models? My experience with GLM 5.1 does not make me miss Opus at all.
    • InsideOutSanta 5mo ago
      I wouldn't call Kimi K2.6, GLM5.1, DS4 or newer Qwen models "low end". I prefer GPT5.5, but if it disappeared tomorrow, I'd be perfectly fine with any of these chinese models.
  • hypercube33 5mo ago
    I think for a while this is possible - the models definitely aren't as efficient as they can be as we've seen a lot of promising papers over the last year about how people are changing pieces and parts to do more with less. None of it has come to market yet that I'm aware of so for now it's just a hope I suppose but things like Opus definitely burn a ton of compute to be the leader in benchmarks but the gaps are closing.
• ainch 5mo ago
  Tokens can be sold at profit, but 70% of compute expenditure goes to R&D and model training[0]. Inference needs to cover all of that as well as being profitable in a vacuum. [0] https://epoch.ai/data-insights/openai-compute-spend https://epoch.ai/data-insights/openai-compute-spend
  • benjiro3000 5mo ago
    [dead]
  • ml_basics 5mo ago
    this will change as inference demand increases (which is happening right now faster than many people expected)
    • vb-8448 5mo ago
      do you have some ref?
    • ainch 5mo ago
      At the same time, the training paradigm being scaled, Reinforcement Learning, is significantly less data-efficient than next-token prediction. You basically need to run an agent for minutes (or longer if you want good long-horizon performance), only to give it a binary pass/fail - one bit of information. Inference compute is definitely scaling fast, but to scale RL, training and R&D compute also needs to scale hard. I don't think it's obvious that inference will overtake R&D/training, unless there's a reputable source that states that.
• utopiah 5mo ago
  It's like witnessing a rocket using the most powerful engine on Earth then once it escaped orbit turn off the engine and said "It is flying without power!". Yes, sure, right now it is ... but that's NOT how it got here. There are trillions invested to recoup and at most billions in sales. It doesn't add up to tokens making a profit any time soon.
  • StevenWaterman 5mo ago
    The problem is, people see "they're not profitable once you account for training" and equate that to "AI will go away soon" But if all the AI companies stopped training new models, they would all instantly become profitable (and stick around) The thing that makes them unprofitable, is having to compete (which means training models). If / when enough companies exit the market, the cost to compete goes down and you end up in an equilibrium
    • notahacker 5mo ago
      Sure, but if companies don't exit the market and FOSS alternatives don't end up being unable to get near them in quality, they have to keep spending on training. And conversely, if the market becomes uncompetitive and FOSS sucks, the winners of the AI arms race are very strongly incentivised to stick their prices up anyway...
      • JumpCrisscross 5mo ago
        > if companies don't exit the market and FOSS alternatives don't end up being unable to get near them in quality, they have to keep spending on training Eh, the AI companies still have lots of datacentres. For the guys who funded with equity, they could collapse down to just running those as utilities. (For the guys who funded with debt, they'd have to restructure.) From the customer's perspective, this situation shouldn't result in a cost spike. (Consolidation, on the other hand, would. But that's a separate argument from the one the article attemptes to make.)
        • 5mo ago
• cryo32 5mo ago
  They aren't being sold at a loss but they aren't being sold at enough to cover the current losses and the costs. The losses are being passed around in some fucked up circular funding mess which will inevitably collapse into a debt crisis at some point.
• gobdovan 5mo ago
  Do you think it will be the case for the Claude Code/Codex tokens as well? I think those are heavily subsidized, but they're the only ones I find real value in.
• malshe 5mo ago
  In other words, AI companies have positive earnings before expenses
  • mrweasel 5mo ago
    "We'd be making money if we didn't have to manufacture the product", something like that?
• jknoepfler 5mo ago
  Brad Gerstner might need a primer in asset depreciation.
• parliament32 5mo ago
  If tokens weren't being sold at a loss, Anthropic would be screaming about it from the rooftops. They've been desparately trying to make themselves not look like a money furnace lately, but it's not really working. They might be sold at-compute-cost, but that of course ignores training, salaries, and everything else.
• vb-8448 5mo ago
  Is sounds very much like "trust me bro" ... Obviously I, like basically everyone else here, don't have access to Open AI or Anthropic books so it's just guessing based on public available evidences, but "tokens aren't being sold at a loss" does not imply there is any profit. And, even if there is some profit, it needs to be big enough to at least pay back the capex spendings and finance the next model iteration.
• runtime_terror 5mo ago
  Ignoring the hundreds of billions of investments and debt and the astronomical costs of training and building data centers, sure. This is delusional thinking.
• dzonga 5mo ago
  so because some1 said something it becomes true ? /o\