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The current AI pricing was always going to go away

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Re: The current AI pricing was always going to go away

#31

Post by clhodapp »

PiRho3141 wrote: post #8

This is where open source models are important. The latest deepseek v4 pro model is 2-5x cheaper than Claude Sonnet 4.6. Cursor's Compose 2.5 that was just recently released is 6x cheaper than Sonnet. The state of the art models are going to get better and more expensive and smaller models are going to get cheaper. There will be a point where the intelligence of both the cheap and state of the art models are indistin…

I know it comes off as pedantic to point this out but: Those are open weight models not open source models.

Closed weight models are the equivalent of SaaS. Open weight models are the equivalent of binary driver blobs or Windows software. We don't really have actual open source LLMs, which would need to publicly release their training data and technique so you could train a similar model yourself, or use their work as a baseline for your own model.

This distinction matters because an actual open source LLM would be extremely important from an ecosystem point of view, if someone ever actually released one.

Re: The current AI pricing was always going to go away

#32

Post by rirze »

_fat_santa wrote: post #6

I wonder how much of Uber blowing their AI budget and MSFT pulling their claude code licenses can be attributed to "tokenmaxxing". When Meta announced token leaderboards and other followed, I could see this being the logical conclusion. That whole trend is so dumb because it leads to this. Company announces they will measure developer performance by how many tokens they burn and constantly talks about how the best de…

> I'm convinced that most of those folks and their elaborate workflows aren't really for productivity but for bragging rights about how much they use AI.

This is quite the reductive, charged statement. Can I ask what subscription plan you're using?

My personal experience is unlike this at all-- I work on ever-expanding codebases so I can easily burn tokens. Not to mention, structured agentic coding with adverserial reviews & task organization is not token-efficient. Additionally, for the problems I'm working on, only xhigh or high reasoning gives me worthwhile results while saving time. There are definitely configurations where default consumption doesn't work.

For reference, I used 15 billion tokens (most of it cached) last month on my day job's enterprise plan. That doesn't include my personal plans' usage.

Re: The current AI pricing was always going to go away

#33

Post by alligatorplum »

I seldom use my PC anymore ever since i got a laptop. with the cost per token increasing along with the random "features" where models will just eat through your tokens in one hour. I really have been tempted to turn my PC into a server to run local models on there

Re: The current AI pricing was always going to go away

#34

Post by pydry »

_fat_santa wrote: post #6

I wonder how much of Uber blowing their AI budget and MSFT pulling their claude code licenses can be attributed to "tokenmaxxing". When Meta announced token leaderboards and other followed, I could see this being the logical conclusion. That whole trend is so dumb because it leads to this. Company announces they will measure developer performance by how many tokens they burn and constantly talks about how the best de…

I really wish the management behind these dumb ideas couldnt just quietly pretend they never did it once it goes out of fashion.

The fact that somebody established a leaderboard for tokenmaxxing ought to follow you around like a black cloud for the rest of your career once the collective hallucination lifts and people realize just how monumentally stupid it was.

Alas they do all these stupid things together which makes it seem more defensible and then everybody forgets.

Re: The current AI pricing was always going to go away

#35

Post by alfiedotwtf »

> Memory for 4x expensive

> Did we collectively forget second order thinking?

I bought 2x 16Gb NVIDIA cards this week because I don’t see hardware getting cheaper anytime soon, and because of that I totally don’t see the point of “waiting until prices go lower for graphics cards” because that might not for a long time yet!

In fact, if you include factoring in world events (and the ones that haven’t happened yet but eventually will e.g. China’s 2027 long planned take of Taiwan), then there’s no way graphics prices are going to be accessible to mere mortals until at least 2028.

But my real reasoning is that you’re going to see a flood of OpenAI and Anthropic users leave because of a) increasing pricing plans, and b) impeding business laws on the horizon about protecting sovereign data from AI (i.e data in cloud for training is a no no).

So what happens when people and companies one by one start leaving the SOTA AI cloud for from-good-enough-to-wow models? RAM and graphics cards become the new toilet paper, which is going to double again current prices.

Upgrade now before it’s too late folks!

Re: The current AI pricing was always going to go away

#36

Post by sometimelurker »

PiRho3141 wrote: post #8

This is where open source models are important. The latest deepseek v4 pro model is 2-5x cheaper than Claude Sonnet 4.6. Cursor's Compose 2.5 that was just recently released is 6x cheaper than Sonnet. The state of the art models are going to get better and more expensive and smaller models are going to get cheaper. There will be a point where the intelligence of both the cheap and state of the art models are indistin…

sorry to nitpick (I totally agree with what ur saying btw, I run Ministral-3b on my hardware as my go-to bc I don't usually need the "smartest and most expensive models")

> This is where open source models are important

open-weights, the training data isn't public

Re: The current AI pricing was always going to go away

#38

Post by dragontamer »

kimixa wrote: post #29
adamesque wrote: post #7

It's hard to take this piece seriously if he's citing _Ed Zitron's_ math, and equally hard to make the blanket statement that flat-rate plans = "the current AI pricing". But yes, those pricing models were pretty silly and unsustainable.

Get back to me when there's an AI company that's actually profitable and we can compare their service and pricing. Claiming that there's some small subset of their services (like inference per token) that's "profitable" doesn't mean anything when it relies on everything else that company is still paying for. If you could make money from it at current prices - why aren't they? Otherwise it's just "how much they're wil…

There is probably going to be a quarter or two of profits when the prices dramatically increase. Vibe coding techbros are hooked on the Iron Lung and may not want to get off.

At my work are multiple developers bragging about overnight AI usage to solve problems hands off. Yes they are wasting money and resources but the fad is here. People be vibe coding for now.

In like 6 months when all the costs need to be paid and the prices go up, we will see if these companies stay profitable. But I'm of the opinion that the vibe coding tech bros are more than enough to sustain a short or even medium term profit for these companies. Just on fad-energy alone (see OpenClaw)

The fad probably collapses soon after. I hope anyway, the waste I see is nauseating.

------------

I dunno where this is all going. But I do have faith in human ingenuity still. Things are changing, possibly for the worse, but we need to make the best of it.

The worst of behaviors is wasteful and blatant fraud. There's something useful here though.

Re: The current AI pricing was always going to go away

#40

Post by anthonypasq »

Guys, we are the in the mainframe era of AI. People in the 60's thought computing was expensive too and the idea of having a computer on every desk, nevermind every pocket, nevermind every single piece of electronics in the world basically seemed like a complete pipe dream.

if you told someone in the 70's their toaster would have a supercomputer it in, they would think you were crazy. in 10 years your doorknob is going to have a local AI model it in.

This is computing 2.0 not the dot com bubble. 90% of inference will be at the edge in the future and there will still be super-computers and giant clusters doing cutting edge science and research, but for 90% of use cases youll just need a tiny local model, same reason you dont need a giant GPU in your smart tv.

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