Anthropic/OpenAI may be spending more than $1000 for every $100 you pay them

NotGMan

If this is the true cost of AI then the future might be dedicated extension cards for computers that hardcode entire models + weights. Downside: you need to buy a new one for each model. Upside: insanely fast inference and zero subscription cost, only one time purchase cost. Once a certain open source model gets good enough this might become viable. Right now the landscape is still shifting too fast. State of the art models might remain on subscription, expensive and might be used by large companies only. State of the art companies might also create their own hardware with hard-baked weights on chip that they don't release to the public, as it might just make more financial sense long term once they "stabilize" on a certain model.

jqpabc123

Hang on to your wallet, you ain't seen nothing yet. The true cost of AI won't be revealed until after a large portion of the customer base has become "hooked" on it.

trilogic

https://hugston.com/news/the-subscription-to-incompetence-is...

diogenescynic

So we're in the $6 Uber ride era of AI still?

solomatov

Hopefully we will have more information about these companies when Anthropic IPO filing become public. There's too much speculation without them.

janim007

That’s probably because only a handful of companies manufacture GPUs, and they’re still expensive. I think that will change over time as competition increases. LLMs are also still in a relatively early stage. We’re already seeing models become both smaller and more capable—for example, GPT-4 compared to Qwen3-30B, which can outperform GPT-4 in many tasks while using significantly less compute. So if this trend continues, they will be making good profits on your $100

wongarsu

The headline claim assumes that Anthropic is operating the API at cost, and losing massive amounts of money on subscriptions My own impression based on inference prices for deepseek or other "open" models in the 1T range (including providers like DeepInfra with no obvious reason to subsidize their API costs) is that Anthropic is offering subscriptions at cost (on average, power users are a bit more expensive, casual users more profitable) and making good profit on API pricing. Profit that then is spent on model training, marketing and development, for an overall negative bottom line Edit: in case it gets changed: current headine is "Anthropic/OpenAI may be spending more than $1000 for every $100 you pay them"

b3ing

The future of AI is ads, free will have lots of ads and eventually go away. Low paid tier will have a few ads, the $2000 tier no ads. I just hope local llms keep getting better and ways to make them run faster on consumer devices improves

KingOfCoders

I would think it depends on what you count in as cost, how long you can operate a data center, in which intervals you need to train new frontier models etc. There are lots of knobs to dial for your costs.

jabart

I really don't now how these other code bases are structured. Our team ran cc-usage and our cost is right about what we pay as our monthly license. This is only those on the team pro side. Our code base is not small, millions of lines of code. It does not take $65 in tokens to solve an issue. I'm running 3-4 claude code terminals at the same time and i'm still pretty close to what it would cost per a token for usage. I don't know what we are doing right with our code or claude.md to make this happen and I don't want to change it to break it.

graemep

There seem to two doubtful assumptions being made here: 1. That the API pricing is required to make a profit, rather than being effective market segmentation to make a larger profit. 2. That if subscriptions are loss making, it is not worth having loss leaders.

beering

As usual, there’s no factual basis for the claims other than “I made it up” and author doesn’t seem to have technical experience with ML experience. A lot of weasel words doing all the heavy lifting here.

tcp_handshaker

And this is the reason, why the AI companies, are now preparing a bailout by the US government. We will be moving quickly from your 401K is their exit liquidity to US Treasuries are their exit liquidity... Meeting next week at the White House by coincidence just before the SpaceX IPO. Message to investors will be dont worry the US has your back... At which point the corruption is sooo big, that an Empire crumbles under its own stench? "Trump to meet AI leaders to discuss US investment in their companies" - https://www.bbc.com/news/articles/c98r8r7dz5no "Trump Officials Held Millions of Dollars of SpaceX Ahead of IPO" - https://finance.yahoo.com/markets/stocks/articles/trump-offi...

syllogistic

Is he headline strictly about subsidized subscriptions? Anthropic announced their first profitable quarter.

himata4113

Anthropic and openai has the most efficient tokens per unit of compute on the planet and honestly that's their current moat. They're able to serve tokens at half the cost of any opensource provider. Here's the costs to serve opus 4.7 in china on aws according to one of my connections that operates an enterprise account in the region: Input: $0.257 Output: $1.286 Cache read: $0.0257 Cache write: $0.322 And I have zero doubts that using batching and other optimizations that subscription users are being served at an even lower cost. Most of their expenses likely come from training as we're far into the diminishing returns terriority. We will know once anthropic is required by law to report these numbers so there's no point in continued speculation that "anthropic is losing $9 for every $1" because 1: unless there's some subsidies going on it's not true and 2: we will be told directly from anthropic what the numbers are in the near future.

johnbarron

Article flagged by the HN moderators owning pre IPO shares on said companies discussed in this article: Anthropic, OpenAI and SpaceX

whodidntante

I see combined estimated revenue for Q1/2026 to be $15B to $20B, depending on source. I also see combined estimated spend Q1/2026 at $15 to $20B, depending on source. Someone or something is having an hallucination that would make an AI jealous

mannanj

And how much money are they making off our non-training data? Or what is the ROI short and long term of that massive valuable data set? Surely there's at least a valuable subset of ideas that if executed better than the incumbents nets them massive value. I find it disingenuous when people narrow in and focus on the cost of tokens as if thats the only way the companies make money. They are doing a massive data grab and stealing and thieving your IP and data, non-training data sharing cannot be opted out of.

gctwnl

Why was this flagged? The article is a serious attempt at observation and analysis.

herunan

The people pushing the “AI is heavily subsidised” narrative don’t realise it actually flatters Anthropic and OpenAI more than the alternative. If it is subsidised, fine – the incumbents absorb the losses, or lean on hyperscalers like Google or Microsoft who can cross-subsidise across other revenue streams. But if it isn’t, that’s the worse outcome for them: inference is just cheap, competition kicks in, prices crater, end users win. Either way, local models win. If the incumbents are forced to turn a profit, pricing goes up and as local compute gets good enough to handle most use cases, people flock to it. And if inference is just cheap, that means the compute requirements are lower than we thought, and local hardware gets there even faster. Bullish on local either way. We’ll find out once the Anthropic S-1 drops.