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Uber's $1,500/month AI limit is a useful signal for AI tool pricing

simonwillison.net

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Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#591

Post by oblio »

jujube3 wrote: post #460
dofm wrote: post #313

Earlier quoted context omitted.

I don't think it is unreasonable to say both will happen, is it? In the long term, tokens will fall in price. Obviously. (If "tokens" continues to be the unit) In the short to medium term, for the IPOs to succeed, people have to start actually paying for what they are using, so the price will go up, and is going up, quite a lot. Once their value is set they will slowly fall from that point (or some point maybe halfwa…

I mean, there's an "enormous incentive" for people to run their own data centers rather than using AWS. And yet, cloud is growing and on-premise is shrinking. While I hope local AI continues to exist, I'm skeptical that it will take over, for the same reason running your own servers hasn't taken over. It's just hard, and involves spending huge sums of money up front. It's also not really clear how much tokens are bei…

Infrastructure is massively complex and multi cloud is super hard to do. Switching LLMs is... a drop down.

Now, that doesn't mean running your own LLM will be easy, but this will mean it's a lot more likely that there will be at least regional LLMs, in my opinion. I.e. there will be Google, whichever (if any) is left standing of OpenAI or Anthropic, and then there will be Chinese hosted LLMs, probably Indian hosted LLMs, European hosted LLMs, plus LLMs hosted on managed services (i.e. Bedrock). For sure I see large banks on the like being able to host the best OSS or even licensed LLMs on their own cloud infrastructure accounts (i.e. at AWS, Azure, etc).

And that's on top of the LLMs running on owned server infrastructure plus actual local, on device LLMs.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#592

Post by no-name-here »

bethekidyouwant wrote: post #420
dgellow wrote: post #164

Earlier quoted context omitted.

One aspect Paul Kedrosky mentioned recently is the concept of „duration mismatch“. The price per token goes down over time (either because the AI vendor reduces due to competition pressure, or because customers are now incentivized to use older cheaper models). But datacenters are financed through debt, with the assumption their revenue increases over time. Quoting him: „[AI vendors are] paying for a fixed cost with…

Using a shittier model is just more work for the user, I’m not sure why anyone does it, unless they’re playing with it like a toy.

> more work for the user

Model routers allow this to happen automatically without any more work by the user.

> a shittier model

A ton of tasks don't require the most expensive frontier models, etc.

> I’m not sure why anyone does it

1. Faster solutions from the LLM - also reduces employee costs of having the employee waiting on the LLM

2. Avoiding things like the half-billion dollar per month bill for a single company’s LLM use recently reported in Axios

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#593

Post by consp »

stingraycharles wrote: post #476
thundergolfer wrote: post #373

> That means each employee's AI spending cap is ~11% of that median compensation package. Probably better to use the fully-loaded cost of the engineer, which is much higher than their compensation package. The fully-loaded cost is the total cost paid for the labor power of the engineer, and it includes big ticket items such as office space, food, equipment, insurance, payroll tax, fringe benefits, recruiting costs. I…

I’ve even heard the rule “twice the salary” being used here in EU, but the tax and insurance burden may be higher. All kinds of those are based primarily on total payroll amount.

That number usually includes cost of habitat and others. It's also a stupid number as it is skewed by how much you can squeeze out of your employees. A better number would be to compare it vs revenue per capita.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#594

Post by atwrk »

dzhiurgis wrote: post #506
corpoposter wrote: post #484

Earlier quoted context omitted.

If it’s open weight then anyone can run it for you. Presumably someone you trust just as much as US proprietary models.

I don't think they'll offer open models for long. Since they've actually invested in power, cheap chips, cheap memory and can subsidize tokens - they'll keep undercutting big models to capture data forever. Bonus if they remove ridiculous safeguards and China will be unstoppable.

Pretty sure they'll offer them at least so long as it takes to bring OpenAI and Anthropic into insolvency. Why wouldn't they? The Chinese models are way more nimble to train and run, bring in a ton of goodwill globally, and put immense pressure on the VC furnace that is the US AI sector.

And apparently OpenAI and Anthropic think so, too - why else would they try so hard to ban them instead of outcompeting them?

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#595

Post by oblio »

Der_Einzige wrote: post #464
jujube3 wrote: post #290

Earlier quoted context omitted.

It's cope. People desperately want to believe that AI coding is going away so that they can go back to partying like it's 2020. So there's a huge number of HN posters claiming that the price of tokens will go UP over time rather than down (that's how Moore's Law works, right???) or that code bases that AI contributes to will spontaneously combust, or something.

Token costs do go down over time for sure due to software optimizations (i.e. better attention kernals) but acting like hardware INFLATION isn't happening for at least a few more years is just nonsense. Objectively an A100 is more expensive to rent today than it was in 2024 (a 7 year old GPU - Big short guy is a turbo idiot) and rising. As such, over short time horizons, it's possible to see limited amounts of "price…

It's a mix. If the current wave of LLM businesses crater, demand for LLM specific hardware (and related hardware) will crater. GPUs were propped up by crypto currencies and now by LLMs. They're still great at doing fundamental math operations, but for their value to stay up another massive business opportunity involving matrix multiplication and the like would need to rise as soon as the current business cycle winds down.

Not impossible, not unlikely, probably 50-50.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#596

Post by iLoveOncall »

simonw wrote: post #467
emp17344 wrote: post #402

Earlier quoted context omitted.

The issue is he’s not actually balanced at all. I’ve never seen him say anything negative about an AI product.

Here's my AI misuse tag: https://simonwillison.net/tags/ai-misuse/ - 54 posts My ongoing coverage of AI ethical issues: https://simonwillison.net/tags/ai-ethics/ - 308 posts I've been the loudest voice about the fundamental insecurity of LLMs for several years: https://simonwillison.net/tags/prompt-injection/ - 150 posts In https://simonwillison.net/2025/Aug/25/agentic-browser-securi... I said "I strongly expect that…

Literally none of those articles are critizing LLMs, only use made of them by 3rd party actors outside of the providers. It really has nothing to do with LLMs themselves.

The fact that you had to dig to August 2025 to find a single article that's actually a critic of something produced by the AI labs is just further proof.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#597

Post by vinzenzu »

ValentineC wrote: post #104

> I noted that my own token usage comes to about $1,000/month against each of Anthropic and OpenAI - which currently costs me just $100 per provider thanks to their generous subsidized plans for individual subscribers. Do we know that AI providers are going to keep these per-token prices, or eventually lower them because of competition from China? Many lower-budget individuals are now moving to China open weight mode…

API prices of Anthropic, OpenAI, and Google are massively inflated.

https://martinalderson.com/posts/no-it-doesnt-cost-anthropic...

There's no way that all AI inference providers are colluding and/or all running at a massive loss, meaning the cheap Chinese model prices must be the real cost it takes to run frontier-class models PLUS their margin.

Look at Deepseek 4 Pro. https://openrouter.ai/deepseek/deepseek-v4-pro/providers Deepseek and Baidu are subsidising prices but they probably train on inputs. I have no model training and ZDR in OpenRouter enabled, and the first provider that shows up there is Deepinfra, significantly more expensive than Deepseek. BUT much cheaper than Sonnet 4.6 and ChatGPT GPT-5.4.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#598

Post by overfeed »

tmp10423288442 wrote: post #260
lbrito wrote: post #237

Earlier quoted context omitted.

That's just a non sequitur. "companies are already paying thousands per seat" has zero correlation with something being a fad or not. There are much more reasonable rationales explaining why companies are acting the way they are than "because AI coding is not a fad"

Can you name a service that charged companies thousands/seat/month that turned out to be almost or completely useless? There's lots of random services sold to corporates that are not very useful (all the random benefits besides health care, life insurance, and other big-ticket items), but the per-seat charge of those is much smaller.

> Can you name a service that charged companies thousands/seat/month that turned out to be almost or completely useless?

The Concorde turned out to be fad (not "useless" - which was your reframing.) Touted as the future of travel, each seat cost about $20,000 of today's dollars, but it turned out even at those high prices people and companies were willing to pay per-passenger, supersonic trans-Atlantic air travel is not economically viable, and was discontinued.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#599

Post by no-name-here »

kristianp wrote: post #439
Animats wrote: post #169

Earlier quoted context omitted.

Raise them, more likely. NVidia says that GPU hardware prices won't decrease until at least 2030. The world is out of fab capacity.

> The world is out of fab capacity. Can anyone expand on this point? I read an article saying that the big AI co's datacentre spend was a bunch of lies because they can't build datacentres at anywhere near the rate they want to.

> they can't build datacenters at anywhere near the rate they want to

That was because the supplies the datacentre needed were constrained - supply-constrained, not end-user demand constrained, so would be in agreement with the GP comment (and the article I read didn't imply anything about lying).

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#600

Post by sfn42 »

sevenzero wrote: post #539
sfn42 wrote: post #472

Earlier quoted context omitted.

Have you tried adding this information to claude.md so it knows? I also think your excuse is bad. "The code is legacy fucked so I'll just legacy fuck it some more because I can't be bothered to make an effort"

Are you some kind of entitled corporate dev that barely has any influence on the codebase? If I fuck up a whole business goes down as I am the only dev there currently. We cant afford that happening. Also why would I mess with anything claude.md related? I just use the CLI tool. LLM enthusiasts always claim how smart these things are so they should figure it out on their own, you know?

I have full control of my codebase. I'm not afraid to make changes to it because I know what I'm doing.

You would edit Claude.md to say things like what tech the project is using, because that's the entire point of claude.md. It's literally the solution to the exact problem you're complaining about. Any information you want it to know, you put in there and then it knows it. And you can tell Claude to make or update the file for you.

I'm not one of the people telling you how smart LLMs are. I'm telling you how to use it efficiently, by not expecting it to know everything but rather provide the information that it needs in order to be a more useful tool.

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