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The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

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Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#31

So the choice becomes to either 1) Use the AI tools as much as you can before they increase prices/tighten usage or 2) Stop using them so you won't be compelled to pay more later when the price inevitably goes up/your regular plan gets downgraded? I would think companies would set the usage low and increase it with capacity rather than subsidizing the power users and going into the red. Maybe my strategy wouldn't be…

or 3) start running local models that are competent for most tasks now like Qwen3.6-27B and only use frontier models when the local model gets stuck.

Many of us would love to, and the models are there, but we're constrained by heavily inflated hardware costs.

If big AI does crash out, it would be an absolute gold-mine for local LLM. Cheap, efficient, Nvidia GPUs, and RAM that can run the best local models already available, will be a real boon.

PS - And as great as Qwen3.6-27B is, how large you can scale it (i.e. how big of a context/project) is mostly hardware constrained.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#32

I'm not yet dependent enough on any AI to shell out anything more than $15-$25/month. If I lose it, it will not be the end of the world. I'll probably start digging into local models. I suspect there are many like me. Far more than there are totally dependent users. I also suspect that the AI economy is some sort of "whale economy", where a minority is footing the bill, by paying outrageous amounts to Anthropic/Open…

i just hooked up to local LLMs. feels much slower, more controlable and doesnt change unless i choose.

if i were in business, the idea that my employees would lose skills and be dependent on a third party that controls both price and quality with zero feedback would be insane.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#33

The underlying capitalist problem is that dumping is not just permitted, but expected as a business strategy. Except dumping is usually exporting to another country to kill their industry. Instead, this dumping is exporting "thinking" to destroy humans' innate thoughts, get them hooked, then rugpull for 3x the cost. Cause just over 1 year of LLMs, takes a developer who could reverse engineer a thing, to now needing h…

Generating huge consumer surpluses as a business strategy? Awesome if true.

Err, yes, until the surplus kills off all other competition and allows the supplier to jack prices up sky high, or otherwise bend consumers to their will. There's a reason most countries will stop foreign firms from doing this to them.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#34

This rumor is not demonstrably true. The subscription prices are competitive and for heavy users even cheap compared to API rates, but there is no evidence that they are structurally priced below cost.

> This rumor is not demonstrably true.

OpenAI, Anthropic, and Microsoft/Meta/Google are all at a net negative on AI (i.e. they're "demonstrably" losing money). So it is objectively true. If everyone is losing money, and nobody is profitable, then it is a demonstrable fact.

As far as I know, the only "AI" venture currently in the green is Nvidia, and they're selling shovels to gold miners.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#35
I’m so sick of this scarcity mindset.

We will have better and cheaper intelligence in the future than we have now. This is not Uber. Inference is profitable for these companies. Looking at API pricing and assuming that reflects the cost basis is dumb.

It costs less for OpenAI to serve GPT-5.5 than it did to serve GPT-4. An H100 is more valuable today than it was five years ago because it can serve more intelligence per token.

Jevons paradox and short-term crunches may cause some swings, but the value of a token keeps increasing while the average token price decreases.

Chinese models are already a fraction of the cost, and we will have a mythos/fable-level open-source model by the end of the year. There is no “gotcha” where every AI company rugs you in unison.

Stop trying to figure out how this screws you. Start figuring out what cool shit you can build with it.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#36

This rumor is not demonstrably true. The subscription prices are competitive and for heavy users even cheap compared to API rates, but there is no evidence that they are structurally priced below cost.

> This rumor is not demonstrably true. OpenAI, Anthropic, and Microsoft/Meta/Google are all at a net negative on AI (i.e. they're "demonstrably" losing money). So it is objectively true. If everyone is losing money, and nobody is profitable, then it is a demonstrable fact. As far as I know, the only "AI" venture currently in the green is Nvidia, and they're selling shovels to gold miners.

They are losing money because they are training new models and building new data centers. The claim of the video is that they're losing money just serving current AI models. There's just no evidence of that.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#37
I don't understand why simonw's comment is dead, because he mentions a real counterpoint to the video: API token prices are NOT the raw costs for any provider. I'd even say that inference needs to have quite a juicy margin to cover for all the other costs. It would make no business sense to sell API tokens at a loss: nobody knows yet how to price intelligence, so why start in the red when it's the only source of revenue?

It's a different story for subscriptions. According to my rough computation (N=1), a Claude Max 20x at $200 gives you access to around $8k worth of tokens per month – but they don't cost Anthropic $8k! – and there I think they'd make a loss on every token maxxer which may or may not be compensated by subscriptions that are not used. But that's not the end of the subscription story.

Once you are "enterprise" you pay for token use and there is no way around it: Anthropic does it and so does OpenAI. The subscription is the gateway drug to token maxxing. When people are hired in an Enterprise job, they'll come with their habit of using AI for all and any task.

All to say that: yes, AI labs are bleeding money but on everything else – datacenters, training models, talent,...

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#38

Earlier quoted context omitted.

Okay then provide a link to a Dropbox PDF or official documentation “demonstrating” the premise is “untrue” please. Or admit you’re blinded by faith. Or financially interested in the public believing in a hypothetical like your second sentence. In short, citation needed or shens bruh.

If you're claiming "AI inference is sold at a loss", it's on you to prove it. All we have actual evidence of is: some users use enough AI that the subscription is sold at a loss to them (up to degenerate cases: usage maxed out at all times), if billed by API metrics, while some other users are, by the same metrics, profitable (down to degenerate cases: a forgotten subscription with $20 a month and 0 usage). We don't…

Very well said. People are making a lot of claims when very little knowledge of the financials is public. If you actually look at the numbers, there are plenty of ways in which API revenue and forgotten subs could more than make the difference for power users. Even if power users are getting 10-20x their sub fee in tokens, the math could still work out. Personally, I doubt more than 5% of Claude subs even approach max usage, because it requires having so many agents running all of the time.

I imagine we'll know in a few months when these companies go public.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#39

This rumor is not demonstrably true. The subscription prices are competitive and for heavy users even cheap compared to API rates, but there is no evidence that they are structurally priced below cost.

It is demonstrably true. Grab gpt-oss-120b, run it continuously and see how far 20 dollars worth of that gets you. People definitely use much more than that in a month, not just power users but regular ones, and they're using models that are more expensive to run (plus the "cloud" markup).

i mean this is difficult to calculate because of prompt cacheing, the ratio of input/output token etc, but if you just do some napkin math, i find it hard to believe people are getting this many tokens on a $20 plan.

heres some napkin math

gpt oss 120b is in/out price at 0.039/ 0.18 per million on open router. heres some assumptions.

1. the ratio of input/ouput is about 25/1. (coding is mostly grep and fairly low outpu)

2. you are getting 75% prompt cache reads

Case B: 50% Prompt Caching Discount (Standard Provider Rate)At 75% Prompt Caching:Total Tokens Obtained: 658,749,010 (approx. 659 Million tokens)

Input: ~633mil

~475 mil cached at 50% input pricing = ~$9.25

~158 mil uncached = ~$6.15

tokensOutput: 25mil tokens ($4.5)

This doesnt even account for profit margins on inference providers, or the fact that openAI probably has a much more efficient inference stack.

its really hard to know what these companies are actually paying, but from everything im hearing, people are reporting API inference pricing is 50% margin.

Re: The $15,000 AI Bill. Your $20 Subscription is a DELUSION [video]

#40

So the choice becomes to either 1) Use the AI tools as much as you can before they increase prices/tighten usage or 2) Stop using them so you won't be compelled to pay more later when the price inevitably goes up/your regular plan gets downgraded? I would think companies would set the usage low and increase it with capacity rather than subsidizing the power users and going into the red. Maybe my strategy wouldn't be…

There's another option too:

In the short term, resource management can affect prices and allocation, especially when it's being figured out on the go.

A permanent position that technology is fixed assumes the technology will not improve.

This means, the software won't get more efficient with it's use of hardware, or the hardware won't become more power efficient, etc. Open/self-hosted models are a real world example where efficiency is happening.

Thinking technology won't become more efficient is like imagining that cell phones will still run with the poor battery life of the 1990's.

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