This reads to me like Anthropic anticipating demand and making a commitment to acquire supply. Not unlike airlines committing to future jet fuel purchases, or Apple committing to future DRAM volume.
At the current price or real price? Anthropic said a $200 subscription can cost them $5000 so the real price could be anywhere from 10-30x the current price.
It's likely Amazon is making a fucking killing though.
> Most likely the subscription inference cost is much lower than you expect.
This is probably not true because they'd be screaming it off every rooftop were that the case.
Same deal with the API inference. Even the "profitable on inference" claim is sourced back to hearsay of informal statements made by OpenAI/Anthropic staff. No formal announcements, nothing remotely of the "You can trust what I'm saying, because if I'm lying the SEC will have my head" sort.
Yet making such statements would be invaluable. If Anthropic can demonstrate profitability before OpenAI, they could poach most of the funding. There's no reason to keep it a company secret.
And API inference is only part of the total costs, not even bringing in training and ongoing fine-tuning. If they're not even profitable on inference, how could they hope to be profitable overall.
50%+ Margin statements have basically been "We are making 50% on delivering it." This does not include ANY of the costs of getting to this point, training, scraping, datacenters, people and so forth.
They are basically saying "Oh yea, the cost of GAS in the car is only X so charging Y per mile is great margin" while ignoring maintenance, cost of acquiring the car and so forth.
Sam Bankman-Fried, Elizabeth Holmes, Kenneth Lay - and hundreds if not thousands more.
The SEC is a regulatory agency, not able to bring criminal charges. The above-named for the most part had to be prosecuted by the Department of Justice or sometimes state attorneys.
A bit of google searching later can get us a specific interview. https://www.dwarkesh.com/p/dario-amodei-2
> Let’s say half of your compute is for training and half of your compute is for inference. The inference has some gross margin that’s more than 50%.
But the context, the very previous sentence is:
> Think about it this way. Again, these are stylized facts. These numbers are not exact. I’m just trying to make a toy model here.
Here, Amodei is in effect using weasel words. He is not giving any actionable claims about Anthropics margins, merely plucking an arbitrary number. Why 50%? Is 50% reasonable? Is 50% accurate to the company? Those are all conclusions the listener draws, not Amodei.
> I don't know about SEC rules
The main premise is that, as a CEO, there are some regulations you are beholden to. You're not allowed to announce you've made a trillion dollar profit, sell all your stock, and then go "teehee just kidding". The SEC prosecute you for securities fraud if you do that stuff.
This makes such weasel words as earlier suspicious. Because the exact statement Amodei gives is not prosecutable. He's not saying anything about the company, just doing a little "toy model".
The degree to which it is intentional that this hearsay travels and is extrapolated from "Well he picked 50% because it's a reasonable figure, and because he's CEO, a reasonable figure would have to be a figure akin to what his company can achieve" into "Anthropic has 50% margin", that's up for debate. Maybe it is intentional, maybe Amodei is exactly the same kind of shitweasel as Altman is. Probably he's just a dumbass who runs his mouth in interviews and for whatever reason cannot issue the true number in an authoritative statement to dismiss this misconception.
Hence my original comment; If the real number were better than the hearsay rumours of the number, Amodei would immediately issue a correction; It'd be great for the company. Hell, even if 50% were about the margin, that'd be great! To promote that from mere hearsay to "we're profitable, go invest all your money" would also be huge. Really, any kind of margin at all would put him ahead of OpenAI.
But he doesn't issue a correction. He doesn't affirm the statement. Perhaps he has other reasons for that, but a rather big reason could be that the margin number is in fact pretty bad.
Now, the observant reader will note I am also using a weasel word there. I do not know whether the number is good or bad, your take away should be "it could be bad." Not "it is bad". Go pressure Amodei into giving us the real number.
Anti-fraud regulators like the SEC give an inherent trustworthiness and credibility to CEOs and other market participants. You can trust that they're not lying to you, because they would be sent to jail if they were.
Another example are general anti-fraud regulations; Consider how one would trust North American or European steel suppliers more than Chinese steel suppliers.
It's not that the Chinese are "evil lying people" and Americans are "saints who never lie", it's that you can trust American, Canadian, and European courts to hold the liars accountable by regulations even if you're not in any of those regions. But the Chinese liars won't be held accountable by regulations.
Thus also the opposite, if someone opts out of this credibility granted to them by anti-fraud regulations, their words may not be quite so truthful.
I think if you're not Anthropic and you don't have access to the actual data, then you can't say for sure. A bunch of anecdotes on terminally-AI people on twitter is not making a convincing case for me, IMO.
On the other hand, if similarly sized models cost much much cheaper than this, why, in the world, would Anthropic have much higher costs than that?
Also, counterpoint, maybe they want you to think that they have higher costs so you're more willing to actually pay for it?
Business buyers are paying API prices, not subscription
Disclosure: Work at Microsoft on AI
If Amazon believes that story they’d be crazy not to invest.
In short: per-token charges currently cover maybe 1% of the total costs in this field. To pay ongoing costs, and pay back investors, everyone will need to pay 100x or 1000x the current rates, likely for decades.
The unit economics for today’s frontier models should be great, and this suggests Anthropic believes they’ll get better.
There are plenty of seemingly informed people saying the exact opposite, so that's a lot of confidence you're talking with. I have a hard time believing it when we know what open weights models cost to run. And sure, there's training costs, but again many say inference costs are already above training costs.
We might see a one time bump in inference when we move off GPUs onto more limited and efficient dedicated hardware, but the sustained fast pace of improvements are far behind us.
But if progress begins to slow down, then the economics work. Maybe Gemma 4 is a good example. It feels really generally useful. Getting it at 1/10th the cost feels like it could be competitive in 2 years.
It’s just that the pace of new stuff is slowing down, and many people are operating under the assumption that this wave will ride on forever.
> inference is indeed profitable
Gemma-4 26B-A4B + M5 MacBook Pro + OpenCode isn't Claude Code _yet_, but it's good enough that if I were forced to use it I would be fine.
Models are likely going to keep getting better, and as costs go down, demand is likely to rise faster.
Huh? Why would that happen? Indications are that costs will likely go up, especially if currently vendors are selling tokens at a loss.
Even if you generously depreciate the GPU and other hardware, it’s hard to believe inference at scale in April 2026 isn’t highly profitable.
I think you meant dollars of electricity.
https://www.theregister.com/2024/03/18/nvidia_turns_up_the_a...
A Blackwell 8X node consumes about 15kw, let’s up that to 50kw to generously account for cooling and everything else.
A US kWh is something like $0.20, so running that node for an hour costs ~$10.
Nvidia got 30,000 parallel TPS out of DeepSeek-R1 on that node:
https://developer.nvidia.com/blog/nvidia-blackwell-delivers-...
So that $10 buys you over 100M tokens or … pennies per million.
I’m sure these numbers are off, but not by an aggregate two orders of magnitude.