4 ms·

We are slowly inching closer to the point where AI and AI products will be billed for what they cost. We are currently living in the heavily discounted world wh

We are slowly inching closer to the point where AI and AI products will be billed for what they cost. We are currently living in the heavily discounted world where everything subsidized to the point where a lot of it is free. It seems like they can't or won't keep that up anymore. My prediction is that whenever one of the big companies raise their prices or move features to higher tiers others will follow soon. They all feel the pressure and non of them want to give away more money than they need to. I wonder if managers will be as excited about AI when the prices go up.

sassymuffinz 6mo ago
It's humorous to me that I can do the work of an AI with nothing but a coffee and an occasional sandwich and yet they talk about AI as if it's some sort of magic hack to productivity. What they don't like is paying money for the work, that's all that matters to them.
- jakobnissen 6mo ago
  You work for sandwiches and coffee, and not for a decent salary?
  - sassymuffinz 6mo ago
    I get paid a decent salary for my expertise and this wild thing called remembering what happened yesterday. My point is my compute is powered by bananas and coffee, not gigawatts of energy and all of the RAM.
    - rescripting 6mo ago
      From the POV of your employer your compute is powered by your decent salary, not bananas and coffee. If that goes away you’d be a fool to keep pointing your brain at your employer’s problems. Thus, your compute is significantly more expensive than AI. Thankfully your taste is also part of your package deal, and is where you deliver real the value over an LLM.
    - JohnHaugeland 6mo ago
      i don’t really care if my salable work product is banana sourced
      - sassymuffinz 6mo ago
        [flagged]
        JohnHaugeland 6mo ago
        insults won’t convince people to agree with you sometimes people just have different belief systems than you, and that’s actually okay
libraryofbabel 6mo ago
This is already happening. For new Anthropic enterprise accounts you are billed at api token prices (maybe with a small volume discount). Anthropic makes a profit on those tokens. (Sure, that profit does not cover the model training costs, but that’s a separate issue.) It’s the subscriptions for individuals (e.g. Claude Max) that are still subsidized below cost. > I wonder if managers will be as excited about AI when the prices go up. Companies are willing to pay the api pricing. Engineering time is very expensive and AI coding agents actually work now since December and are actually showing measurable productivity gains, finally. It’s a good deal to make (obviously, with caveats: you need to make sure your tokens are going on productive tasks that will actually grow revenue) and anyone who penny-pinches is making a strategic mistake.
- BadBadJellyBean 6mo ago
  > Sure, that profit does not cover the model training costs, but that’s a separate issue. I don't think it is. At some point they have to make money and they can't do that if the token cost doesn't include ALL the costs. Someone has to pay for that at some point. And someone has to pay for the subsidized subscribers. So no. API token prices don't reflect the real price. They are still subsidized. Just in a different way.
- CodingJeebus 6mo ago
  They may be for now. Problem is that when foundation model pricing goes up, you're paying not just the increase in tokens you consume directly, but also for all tokens you're consuming via vendors as well. If your company has Figma, Github, and Cursor and they're using the same models you are, your monthly costs with them increase as well. You're exposed N times to the foundation model price increases, where N is the number of times software you directly or indirectly use talks to a frontier model.
- ericmcer 6mo ago
  "Engineering time is very expensive" I always wondered about this statement, like we are generally salaried and there is so many variables that affect how I spend my "time". None of us are machines that can do X work per day and our managers get to slice it as they see fit. Pull a dev off a project they love and throw them onto something they hate and suddenly X is diminished greatly. I would almost predict that reshaping our workflow to be: "prompt, wait, approve changes." results in losses because it is such a mentally tiring workflow and drills into our brains the desire for the LLM to "just fix it". It is the next level of just moving tickets to completed all day.
pphysch 6mo ago
Slowly inching? GitHub Copilot announced 600%+ price increases for many workflows, with others being potentially 100x more expensive due to the change from request to token based billing.
- BadBadJellyBean 6mo ago
  With how intransparent everything in the AI world is I have no idea how far away we are from the "real" prices. Might be a gallop or maybe it's much worse than we think and we are still just inching. We'll see. Exciting times. If you like to see the world burn.
ericmcer 6mo ago
It is already bafflingly expensive. I interviewed at a place recently where they said the average dev was hitting $2k/mo in Claude code costs. That is no longer a helpful tool... it costs like ~15% of an actual dev. Even if it is helping, is it actually... making things better or building anything truly important? The issue seems way too nuanced to spend $2k/mo. Not to mention the entire tech industry floats on hype and imaginary goal posts so now what? Devs can hurdle towards those faster and more mindlessly?
- Aurornis 6mo ago
  > That is no longer a helpful tool... it costs like ~15% of an actual dev. The full cost of each employee is more than their salary. The common estimate is 1.4X their salary due to all of the employer-paid taxes, benefits, and other things. So even $2K/month of token costs would only be around 10% of the cost of a mid-range developer cost. It doesn't have to increase productivity much to justify the cost.
  - legulere 6mo ago
    Don't forget the organisational overhead. You'll need managers and communication overhead between developers grows superlinear (see Brook's law).
    - JohnHaugeland 6mo ago
      brook’s law is probably not true anymore
  - Silhouette 6mo ago
    The arithmetic is a little different in every country because of local rates of pay and taxation but it's worth remembering that in most of the world except for the richer parts of the US developers do not get paid what those US developers have been making in recent years. There are a few exceptions but the norm is several times less even in major economies in Europe or Asia. Another challenge for US tech companies is that - if you'll forgive the bluntness - their "brand" is now toxic in most of the world. Almost everyone is trying to distance themselves from US tech as fast as they can. Governments and big businesses are starting to invest seriously in alternative solutions and local resources. It will happen over time but I don't see much the US tech companies or the US government can do to stop the train now the wheels are turning. So there's a serious risk for US tech companies now of a double whammy where their already relatively high R&D costs increase even further and yet they're also facing much stronger competition in international markets or maybe even excluded from some of those markets entirely. If we also reach the seemingly inevitable point that "capable enough" LLMs can run locally - or at least as a private resource provided internally by large organisations - there is very little moat left to protect not only US Big Tech whose stocks have been heavily driven by expected returns from AI but the whole US tech industry that is banking on productivity gains from that AI tech. Then they also won't be able to capture most of the entire global supply of components like GPUs/RAM/SSDs because it won't be cost effective any more - and that is one of the few practical moats they have built (however accidentally) that would be a significant barrier to direct competitors setting up shop in places like Europe and Asia. It's going to be interesting to see how US tech companies respond to these effects over the next 5-10 years. The giants are all aboard the AI train and can't back down now so there will probably be some casualties there if - as again seems inevitable - the bubble bursts at some point. But then there's a very long tail of still very successful US tech companies that might be paying US salaries and using AI-based tools but aren't themselves focussed on developing or providing those AI-based tools and they're the ones who are going to need to find new ways to compete effectively within that kind of time frame.
LocalH 6mo ago
That's what the cloud AI industry is banking on. Pushing hard to get AI into workflows at a critical position, then raising the cost to turn the screws, hoping that companies would rather pay than pivot again
Aurornis 6mo ago
> We are slowly inching closer to the point where AI and AI products will be billed for what they cost. I suspect the API prices are already served with profitable unit economics. The SOTA API prices are much higher than the costs for other providers to run very large open weight models. The monthly subscription plans were being offered at a discount to generate interest in these models. We're not entering a period of billing AI at cost. We're entering a period of exploring how how the prices can go before losing too many customers. Products and services aren't sold at cost. They're sold at the price the market will bear. It takes some experimentation to find that equilibrium point where you make more profit per customer but don't lose too many customers.
- malfist 6mo ago
  > I suspect the API prices are already served at prices with profitable unit economics. There is absolutely no evidence to support this.
  - winfredJa 6mo ago
    Mr.Truth-teller Amodei confirmed it that APIs are profitable at Anthropic.
    - Eufrat 6mo ago
      I don’t think any of the AI model providers have produced any evidence to back their claims of profitability. I want to see their S-1s, then we can fight.
    - disgruntledphd2 6mo ago
      He didn't, he talked very carefully in hypotheticals.
  - speedgoose 6mo ago
    We don’t know the models sizes, requirements, and optimisations, but we could take a guess using the infrastructure costs of the largest open weight alternatives that perform slightly worse. In my opinion, it’s a profitable kind of service. They probably don’t pay the public prices for the cloud GPUs though.
XCSme 6mo ago
But with new hardware comping out, and maybe models being smart enough to help with optimizing them and reducing inference costs even more, I think we should still expect the costs to go down.
hacker_homie 6mo ago
run local models
- SchemaLoad 6mo ago
  You need massively expensive hardware to run them, and they aren't as good. It's pretty clear the base price of AI tools is way higher than we are being charged right now.
  - pixelpoet 6mo ago
    I wouldn't call my $2k Strix Halo computer "massively expensive", and it runs e.g. Qwen 3.6 27b brilliantly, with tons of memory to spare and is a full x86 powerhouse pulling 120w at absolute max. IMO the programming world is far too myopic about / insistent on using laptops, especially macbooks. Just because a crappy deal exists doesn't mean everyone is forced to take it. Local AI is a high performance computing problem and laptops are fundamentally a crappy form factor for it; buy an efficient desktop computer and be surprised at what's possible even with today's crazy prices.
- mark_l_watson 6mo ago
  I experiment a lot with local models, great results for engineering tasks, less so for coding agents. I have used the following on a 32G MacMini to help write useful code: ollama launch claude --model qwen3.6:27b-coding-nvfp4 The problem is that running local models (except for engineering tasks like data munging) is slow. With the above setup I set up a task (asking for no user verification) and go for a walk to wait for results that my Gemini Ultra plan would produce in 10 seconds.
bobbiechen 6mo ago
I called this last year: https://digitalseams.com/blog/the-ai-lifestyle-subsidy-is-going-to-end https://digitalseams.com/blog/the-ai-lifestyle-subsidy-is-go... . I see it as no different from the previous generation of consumer startups burning money - as Derek Thompson wrote, > ...if you woke up on a Casper mattress, worked out with a Peloton, Ubered to a WeWork, ordered on DoorDash for lunch, took a Lyft home, and ordered dinner through Postmates only to realize your partner had already started on a Blue Apron meal, your household had, in one day, interacted with eight unprofitable companies that collectively lost about $15 billion in one year.
- unrelat3d 6mo ago
  Everyone called it last year and the year before. The conversation around AI being cheap now started when ChatGPT launched in 2023

sassymuffinz 6mo ago

It's humorous to me that I can do the work of an AI with nothing but a coffee and an occasional sandwich and yet they talk about AI as if it's some sort of magic hack to productivity. What they don't like is paying money for the work, that's all that matters to them.

jakobnissen 6mo ago
You work for sandwiches and coffee, and not for a decent salary?
- sassymuffinz 6mo ago
  I get paid a decent salary for my expertise and this wild thing called remembering what happened yesterday. My point is my compute is powered by bananas and coffee, not gigawatts of energy and all of the RAM.
  - rescripting 6mo ago
    From the POV of your employer your compute is powered by your decent salary, not bananas and coffee. If that goes away you’d be a fool to keep pointing your brain at your employer’s problems. Thus, your compute is significantly more expensive than AI. Thankfully your taste is also part of your package deal, and is where you deliver real the value over an LLM.
  - JohnHaugeland 6mo ago
    i don’t really care if my salable work product is banana sourced
    - sassymuffinz 6mo ago
      [flagged]
      - JohnHaugeland 6mo ago
        insults won’t convince people to agree with you sometimes people just have different belief systems than you, and that’s actually okay

libraryofbabel 6mo ago

This is already happening. For new Anthropic enterprise accounts you are billed at api token prices (maybe with a small volume discount). Anthropic makes a profit on those tokens. (Sure, that profit does not cover the model training costs, but that’s a separate issue.) It’s the subscriptions for individuals (e.g. Claude Max) that are still subsidized below cost. > I wonder if managers will be as excited about AI when the prices go up. Companies are willing to pay the api pricing. Engineering time is very expensive and AI coding agents actually work now since December and are actually showing measurable productivity gains, finally. It’s a good deal to make (obviously, with caveats: you need to make sure your tokens are going on productive tasks that will actually grow revenue) and anyone who penny-pinches is making a strategic mistake.

BadBadJellyBean 6mo ago
> Sure, that profit does not cover the model training costs, but that’s a separate issue. I don't think it is. At some point they have to make money and they can't do that if the token cost doesn't include ALL the costs. Someone has to pay for that at some point. And someone has to pay for the subsidized subscribers. So no. API token prices don't reflect the real price. They are still subsidized. Just in a different way.
CodingJeebus 6mo ago
They may be for now. Problem is that when foundation model pricing goes up, you're paying not just the increase in tokens you consume directly, but also for all tokens you're consuming via vendors as well. If your company has Figma, Github, and Cursor and they're using the same models you are, your monthly costs with them increase as well. You're exposed N times to the foundation model price increases, where N is the number of times software you directly or indirectly use talks to a frontier model.
ericmcer 6mo ago
"Engineering time is very expensive" I always wondered about this statement, like we are generally salaried and there is so many variables that affect how I spend my "time". None of us are machines that can do X work per day and our managers get to slice it as they see fit. Pull a dev off a project they love and throw them onto something they hate and suddenly X is diminished greatly. I would almost predict that reshaping our workflow to be: "prompt, wait, approve changes." results in losses because it is such a mentally tiring workflow and drills into our brains the desire for the LLM to "just fix it". It is the next level of just moving tickets to completed all day.

pphysch 6mo ago

Slowly inching? GitHub Copilot announced 600%+ price increases for many workflows, with others being potentially 100x more expensive due to the change from request to token based billing.

BadBadJellyBean 6mo ago
With how intransparent everything in the AI world is I have no idea how far away we are from the "real" prices. Might be a gallop or maybe it's much worse than we think and we are still just inching. We'll see. Exciting times. If you like to see the world burn.

ericmcer 6mo ago

It is already bafflingly expensive. I interviewed at a place recently where they said the average dev was hitting $2k/mo in Claude code costs. That is no longer a helpful tool... it costs like ~15% of an actual dev. Even if it is helping, is it actually... making things better or building anything truly important? The issue seems way too nuanced to spend $2k/mo. Not to mention the entire tech industry floats on hype and imaginary goal posts so now what? Devs can hurdle towards those faster and more mindlessly?

Aurornis 6mo ago
> That is no longer a helpful tool... it costs like ~15% of an actual dev. The full cost of each employee is more than their salary. The common estimate is 1.4X their salary due to all of the employer-paid taxes, benefits, and other things. So even $2K/month of token costs would only be around 10% of the cost of a mid-range developer cost. It doesn't have to increase productivity much to justify the cost.
- legulere 6mo ago
  Don't forget the organisational overhead. You'll need managers and communication overhead between developers grows superlinear (see Brook's law).
  - JohnHaugeland 6mo ago
    brook’s law is probably not true anymore
- Silhouette 6mo ago
  The arithmetic is a little different in every country because of local rates of pay and taxation but it's worth remembering that in most of the world except for the richer parts of the US developers do not get paid what those US developers have been making in recent years. There are a few exceptions but the norm is several times less even in major economies in Europe or Asia. Another challenge for US tech companies is that - if you'll forgive the bluntness - their "brand" is now toxic in most of the world. Almost everyone is trying to distance themselves from US tech as fast as they can. Governments and big businesses are starting to invest seriously in alternative solutions and local resources. It will happen over time but I don't see much the US tech companies or the US government can do to stop the train now the wheels are turning. So there's a serious risk for US tech companies now of a double whammy where their already relatively high R&D costs increase even further and yet they're also facing much stronger competition in international markets or maybe even excluded from some of those markets entirely. If we also reach the seemingly inevitable point that "capable enough" LLMs can run locally - or at least as a private resource provided internally by large organisations - there is very little moat left to protect not only US Big Tech whose stocks have been heavily driven by expected returns from AI but the whole US tech industry that is banking on productivity gains from that AI tech. Then they also won't be able to capture most of the entire global supply of components like GPUs/RAM/SSDs because it won't be cost effective any more - and that is one of the few practical moats they have built (however accidentally) that would be a significant barrier to direct competitors setting up shop in places like Europe and Asia. It's going to be interesting to see how US tech companies respond to these effects over the next 5-10 years. The giants are all aboard the AI train and can't back down now so there will probably be some casualties there if - as again seems inevitable - the bubble bursts at some point. But then there's a very long tail of still very successful US tech companies that might be paying US salaries and using AI-based tools but aren't themselves focussed on developing or providing those AI-based tools and they're the ones who are going to need to find new ways to compete effectively within that kind of time frame.

LocalH 6mo ago

That's what the cloud AI industry is banking on. Pushing hard to get AI into workflows at a critical position, then raising the cost to turn the screws, hoping that companies would rather pay than pivot again

Aurornis 6mo ago

> We are slowly inching closer to the point where AI and AI products will be billed for what they cost. I suspect the API prices are already served with profitable unit economics. The SOTA API prices are much higher than the costs for other providers to run very large open weight models. The monthly subscription plans were being offered at a discount to generate interest in these models. We're not entering a period of billing AI at cost. We're entering a period of exploring how how the prices can go before losing too many customers. Products and services aren't sold at cost. They're sold at the price the market will bear. It takes some experimentation to find that equilibrium point where you make more profit per customer but don't lose too many customers.

malfist 6mo ago
> I suspect the API prices are already served at prices with profitable unit economics. There is absolutely no evidence to support this.
- winfredJa 6mo ago
  Mr.Truth-teller Amodei confirmed it that APIs are profitable at Anthropic.
  - Eufrat 6mo ago
    I don’t think any of the AI model providers have produced any evidence to back their claims of profitability. I want to see their S-1s, then we can fight.
  - disgruntledphd2 6mo ago
    He didn't, he talked very carefully in hypotheticals.
- speedgoose 6mo ago
  We don’t know the models sizes, requirements, and optimisations, but we could take a guess using the infrastructure costs of the largest open weight alternatives that perform slightly worse. In my opinion, it’s a profitable kind of service. They probably don’t pay the public prices for the cloud GPUs though.

XCSme 6mo ago

But with new hardware comping out, and maybe models being smart enough to help with optimizing them and reducing inference costs even more, I think we should still expect the costs to go down.

hacker_homie 6mo ago

run local models

SchemaLoad 6mo ago
You need massively expensive hardware to run them, and they aren't as good. It's pretty clear the base price of AI tools is way higher than we are being charged right now.
- pixelpoet 6mo ago
  I wouldn't call my $2k Strix Halo computer "massively expensive", and it runs e.g. Qwen 3.6 27b brilliantly, with tons of memory to spare and is a full x86 powerhouse pulling 120w at absolute max. IMO the programming world is far too myopic about / insistent on using laptops, especially macbooks. Just because a crappy deal exists doesn't mean everyone is forced to take it. Local AI is a high performance computing problem and laptops are fundamentally a crappy form factor for it; buy an efficient desktop computer and be surprised at what's possible even with today's crazy prices.
mark_l_watson 6mo ago
I experiment a lot with local models, great results for engineering tasks, less so for coding agents. I have used the following on a 32G MacMini to help write useful code: ollama launch claude --model qwen3.6:27b-coding-nvfp4 The problem is that running local models (except for engineering tasks like data munging) is slow. With the above setup I set up a task (asking for no user verification) and go for a walk to wait for results that my Gemini Ultra plan would produce in 10 seconds.

bobbiechen 6mo ago

I called this last year: https://digitalseams.com/blog/the-ai-lifestyle-subsidy-is-going-to-end https://digitalseams.com/blog/the-ai-lifestyle-subsidy-is-go... . I see it as no different from the previous generation of consumer startups burning money - as Derek Thompson wrote, > ...if you woke up on a Casper mattress, worked out with a Peloton, Ubered to a WeWork, ordered on DoorDash for lunch, took a Lyft home, and ordered dinner through Postmates only to realize your partner had already started on a Blue Apron meal, your household had, in one day, interacted with eight unprofitable companies that collectively lost about $15 billion in one year.

unrelat3d 6mo ago
Everyone called it last year and the year before. The conversation around AI being cheap now started when ChatGPT launched in 2023