Comment by soundworlds
17 hours ago
I've been using the $32/month (AUD) subscription, but finally dipped into extra credits to get a task over the line yesterday after I hit my 5-hr limit.
And my god, $15 of extra credits ended up giving me only 30 minutes of Claude Code before running out.
The subscription prices can not be financially sustainable. There is no way that is remotely close to the actual cost of running.
The other way of looking at this is that all the customers paying API rates are giving Anthropic way more than the cost of serving their traffic. They reported an 85% gross margin in their S-1, so this clearly seems to be the case.
Okay but even with a 85% margin the true cost for 30 minutes of usage would be $2.25. At that cost $34 should last only 7.5 hours. I would imagine the average user uses more than that?
I think you would guess wrong.
The median user is using AI as a search engine, meme creator, and/or chatbot… at best.
The additional cost created by the subset of programmers using subscriptions rather than tokens/api can easily be categorized as a marketing expense.
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API is definitely holding things up. But they excluded the training from those profit calculations. There's a ton of wordplay indulged online about how that's capex etc etc. But without the training they don't have the thing to run inference on so it's very fitting with the pattern of being evasive with finances.
You’re confusing two figures. Before their S-1 filing, they reported being “profitable” to their investors when excluding training and stock based comp.
In the S-1 filing Q3 was profitable even with training included, if you exclude stock based compensation.
Q2 was profitable on all operating costs (incl. hardware, employees, training, inference). They were not profitable on non operating costs though. That’s partially interest, but mostly, when their valuation goes up, they’ll have to issue more stock (absolute value) to early investors after IPO. (so, them going up in value is a loss, as the shares they’ll owe will be worth more)
Their profitability will likely crator as they start building their own data centres after the IPO, so that’s the best results they’ll have in a while.
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Deepseek claim they are earning 38 dollars per GPU hour on inference. If you compare Deepseek Flash's off-peak pricing with Sonnet at API rates, Deepseek is 16x cheaper per 1M output tokens, and 13x to 33x cheaper for input, depending on whether or not it's a cache hit. Inference is very profitable.
There are moments where I have a 2 hour , 4 instances in separate Kitty/Ghost windows , Opus 5.5 hammering away on each - and only see a 1% increase on my Max x20. Then there are other days where 10 minutes of a single xH Opus doing 1/10th of the work will kill 2%.
Anthropic is super opaque with what inference costs at any given moment on the subscription and cache is just super inconsistent.
I wouldn't be surprised if they have some implementation of demand-based surge-pricing
A Claude/OpenAI sub is still cheaper than DeepSeek API pricing though. Also, I suspect Claude and OpenAI models to be way larger (probably in the 2-3T range) than that of Deep Seek.
Again, if you ignore training.
That is like saying selling hamburgers is profitable if you exclude the cost of beef.
Not the same. You could, and many will argue we already have, strong enough models that you wouldn’t need an upgrade. Web development is already there. The competition to train better models is about capturing more market share now.
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No. Beef is electricity... you'd have to consider warehousing or indeed staff training, as training
You are probably better off upgrading to Max for one month. I’ve done that a few times.
or a second subscription
How would you sync context between two or more subscriptions?
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> no way that is remotely close to the actual cost
Anthropic is running 85% gross margins on inference.
Yeah, on the API, not subscriptions. Those are a loss leader
No, inference as whole, including all the subscriptions.
The API Gross margin is even higher.
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Less development and operating costs
Yeah and soon we'll discover it's because they calculate the cost of inference as near 0 because they use AWS / NVidia / etc. credits that they got "for free" (aka investments from those companies) instead of paying for them, or some other accounting bullshit.
You wanna know the real price? It's easy, just check what AWS, GCP or Azure charge for tokens.
OpenRouter gives you easier to verify cost analysis of generic inference, as you can know the model weight size and so on, and see how competing providers price that
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No, for a dollar of inference sold, (as an average of all the different inference tiers and plans), it cost them 15c to provide it.
This excludes the R&D costs, including training, where most of their costs lie.
The basic truth of LLM economics is that inference is cheap. The NRE cost to get where you can get premium prices for inference is sky-high. This is part of why the AI companies want to drive the scale up so much.
We recently switched from paying API prices via Cursor to a Claude subscription. Before we'd be averaging $100-$300 per day, now we have the €90/mo subscription and I haven't even reached the 5h limit yet.
My guess is a mixture of both... There's a reason why enterprise customers have to use API based billing.
(We also had a stint of using Grok 4.7 and that was the same price for our usage. Opus 5.5 seemed smarter though. After taking into account caching both average around $0.60 per 1M tokens)
Because, like with other subscriptions, most people don’t use even half of it.
You might not be representative of the average user. Usually with subscription-based services, you have a minority of hyperusers that the company loses money on and a large majority who only use their subscription occasionally.
OTOH less than $10 gets me more DS4.1 than I can use in a month.
> And my god, $15 of extra credits ended up giving me only 30 minutes of Claude Code before running out.
I've been running into the same thing, and adding separate OpenAI seats for employees rather than paying obscene overages to Anthropic. Thankfully Opus has decreased usage quite a bit, and made this less of an issue as well.
Opus 5.5 is incredibly verbose compared to GPT 6.1. I mean substantially. They are both great generating the code I need. But I wonder how much more this extra vebosity costs me with Opus.
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> The subscription prices can not be financially sustainable. There is no way that is remotely close to the actual cost of running.
It's completely unclear to me why this is the conclusion everyone jumps to instead of "holy cow they are milking it on API pricing."
I mean, have you ever run a local model? How much electricity did it cost you to get 1,000 tokens out of it? Like a fairy-dust of a cent?
The AI labs' cost is CapEx. Marginal cost of tokens is zero.
How much electricity do you think a few DGX Sparks consume?
I found this to be a shocking experience as well. Compare the 20x (now ultra 10x or whatever) plan running with 90% cache hit vs some extra credits you put on top. It's pissing in the wind.
Be careful!
They lure you in to do "automatic top up", which gets quite expensive if you dont watch it :-)
> The subscription prices can not be financially sustainable. There is no way that is remotely close to the actual cost of running.
Welcome to... any subscription system ever? If every person with a gym subscription actually went there say three times a week, or every person living in a dorm paying flat rate for electricity started mining bitcoin 24/7, these systems would collapse. That doesn't mean it's not sustainable, it just is how subscription pricing works, by having some people use its offers a ton and others barely at all
This metaphor gets repeated a lot for some reason but using a gym subscription has an upper bound. If one subscription could be using 10000 different machines at the same time their model would be entirely different.
CC has an upper bound too, and one that is much more reasonably reached in regular usage (as opposed to gym visits)
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Claude also has higher bound. Once it proposed running 16 concurrent subagents and it went through 5h limit (and substantial part of weekly) in minutes.
Overall it would go through weekly usage within 40 minutes, if not for 5h session limit.
Running on 10000 computers will just hit all the limits at once.
because "building things with claude-code" isn't the product they're selling, not really.
they're setting a precedent that artificial intelligence should be free, or at least at-cost (free from profit), but robot labor (API usage) should not. I am all in favor of this dynamic. They built / maintain the robots, so they profit from their labors.
I think every comment is talking about their 20 dollar plan. Enterprise pricing is 20/seat+ api use prices. That pricing is all that matters, the personal use tier is probably tiny
Don't worry, I've probably sent Claude 5 messages on my personal sub the past month, so I got you covered.
>> The subscription prices can not be financially sustainable.
Even if they are a loss leader, they serve a valuable purpose: people who get used to using AI a lot via the subscription then lobby their companies to start using it. IMHO this is one of the reasons Anthropic was able to make major headway into enterprise.