Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

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

simonwillison.net

Post reply on HN
Print view View original

241–250 of 819 posts

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

#241

Post by siliconc0w »

I use the $100/mo sub but my 30 day API cost is about $1700/mo.

It really depends how you use it, if you're using prompts to generate detailed designs, breaking those into lists of tasks, and then feeding those to multiple agents - it's really easy to burn through many thousands.

If you're being more deliberate and using a few agents at a time interactively, having it review PRs/resolve issues, automated clean-ups and performance optimization, etc it could be more like $1500.

If you're just throwing it one-off questions like a better stack-overflow that is well under a $100.

I've really gotten into /goal, if you can find something verifiable and leave it overnight - it's kinda like christmas morning to see where it landed.

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

#242

Post by malfist »

bijowo1676 wrote: post #171
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…

do GPU chips really depreciate physically? There are no moving parts, I dont think memory chips or GPU chips deteriorate naturally. I think its only accounting depreciation. I have been using my laptop for a decade, what is stopping datacenters from using the purchased GPU chips for a decade?

They do degrade physically, but the bigger thing is they stop being competitive quickly. Each year or so we see doubling of GPU speeds for the same amount of power.

If you build a 100MW data center with GPU compute and three years laster a new data center opens with the same cost for GPUs and same electricity cost you do, but can do twice as much compute, you quickly lose business unless the market is just so constrained customers can't afford to be picky. But the moment there's slack in the market you'll see major migrations off of providers that have the same cost but half, or quarter of the same performance.

So when you see someone talking about GPUs fully deprecating in value in 1-3 years this is what they're talking about. Right now it's not a big deal because there's no slack in the market. But once there is, the bottom will drop out.

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

#243

Post by threetonesun »

dghlsakjg wrote: post #210
anthonypasq wrote: post #152

Earlier quoted context omitted.

perhaps the personal computer? Companies were spending 3-5k (10-15k inflation adjusted) on every employee for just hardware. everyone making comparisons to the dotcom bubble seems misguided. this is clearly computing 2.0 imo

The Dotcom bubble is an interesting comparison. The general thrust that everything would be online was correct, it was just that the market mistimed and misallocated of capital by a decade or more. There was massive spending on infrastructure capacity that we wouldn't end up needing until the 2010s. There were hype driven valuations completely disconnected from business fundamentals just because a company was an 'int…

The question you always have to ask is what problems does it directly solve. I personally think most of the current problems in software development and really the world at large are not time-bound problems but alignment issues, and all an LLM can really do there is be some 3rd party oracle that gives you an answer without needing other humans to agree with you.

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

#244

Post by jmalicki »

Aurornis wrote: post #205
bijowo1676 wrote: post #171

Earlier quoted context omitted.

do GPU chips really depreciate physically? There are no moving parts, I dont think memory chips or GPU chips deteriorate naturally. I think its only accounting depreciation. I have been using my laptop for a decade, what is stopping datacenters from using the purchased GPU chips for a decade?

There are data centers that use and rent out 10 year old server GPUs. They can't run larger modern models. They can't run smaller models as fast as newer servers. So their remaining market is applications where customers are okay with older, smaller models and slower performance. They have to price the service lower than competitors due to the lower performance. The older GPUs are less efficient so it costs them more…

As long as the demand for GPUs keeps increasing, there are more data centers being built to house them.

When you have waitlists for many many months for Blackwell GPUs, keeping the old ones around as long as customers are willing to pay for them is great.

If I as a customer have a use case for a machine learning model I developed awhile ago, so an insect identification model, I had an ML researcher/eng develop it back in 2019, and it runs fine on a 2018-era T4 GPU (NVidia 2080 era), why mess with it?

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

#245

Post by tardedmeme »

bijowo1676 wrote: post #171
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…

do GPU chips really depreciate physically? There are no moving parts, I dont think memory chips or GPU chips deteriorate naturally. I think its only accounting depreciation. I have been using my laptop for a decade, what is stopping datacenters from using the purchased GPU chips for a decade?

Gradually, and especially when hot. Modern chips are pretty close to the physical limits of how small they can be made, and that means atomic/chemical effects like electromigration are accounted for and determine the lifetime. Every extra 10 degrees Celsius of temperature doubles the speed of chemical reactions.

When they stray too close to the line ... you get Intel's 13/14th gen chips that wear out after 1-2 years instead of 10-20 years. Intel calls it "Vmin drift" because that doesn't sound scary, but the actual point is that various wear-out mechanisms push the chip outside of its design envelope - increasing the voltage or lowering the clock speed may get it to run for a while longer, but you're living on borrowed time as the various circuits just stop working right and you get unpredictable instruction mis-execution: https://fgiesen.wordpress.com/2025/05/21/oodle-2-9-14-and-in...

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

#246

Post by pmontra »

hrpnk wrote: post #127
pmontra wrote: post #125

I wonder what they are doing with $1500 per month. I'm on Claude Pro $20 plan and I'm doing well. That's 3 days per week. On the other 2 days I'm using a customer's Claude Max, I don't know if it's the $100 or the $200 plan, but I'm sharing it with some of its other developers.

$1500/mth is token pricing. Your other plans are fixed price with rate limits where you get more tokens than the dollar equivalent you pay monthly. These plans are economical only if majority of users spend less tokens in $ than the plan's costs. This subsidizes the gap vs. power users who spend multiple k$ monthly in API tokens.

> Your other plans are fixed price with rate limits where you get more tokens than the dollar equivalent you pay monthly.

Or the fixed cost plans reflect the real cost and the people paying API prices give them the profit.

Anyway, none of my customers will let me bill them $1500 more (about $75 per day) because I'm using AI. And what for? I'm not working to move money from the pockets of my customers to the pockets of AI companies.

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

#247

Post by geodel »

> A $1,500 monthly limit per tool strikes me as a rational policy response to over-spending,...

> 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.

This whole article seems to me like Multi level marketing "businesses" where 'Diamonds' have made their money by promoting MLM in seminars and telling hopefuls at bottom that "Buying AI subscription now is their one shot to be a winner in life"

Perhaps there is something to MLM vs LLM to create a FOMO effect.

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

#248

Post by datsci_est_2015 »

saulpw wrote: post #239
OptionOfT wrote: post #206

Earlier quoted context omitted.

Because companies are betting that this spending will allow them to reduce cost by firing people. Right now the AI LLM PRs we're seeing are just introducing more work for other people, while these so-called builders are looking good with their new dashboards and functionality they're demoing. But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are. It'…

> But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are. You can absolutely do this. It's even right most of the time.

I believe the “them” the OP was talking about was referring to the people opening the PRs, not the LLMs.

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

#249

Post by soleveloper »

john01dav wrote: post #236

Why isn't self hosting (even just renting a GPU server, not necessarily on premise) at large companies or hosting via something like together AI to run the open weight models not more common? I've tried the open weight models and the premium models like Opus and Gemini Pro, and I find that the latter are a little better, but not nearly to the degree to justify the extreme price difference, since the differences large…

If the premium models are just about 10% better - that could justify the price vs. self hosting a ~0.5-1T open weights model.

Remember that utilization of these huge racks will not be 24h/7, and these are usually not GPU intensive shops that would train models on the spare compute. With prices of 100-200k USD and north with ~2 years lifetime, that would be hard to justify financially.

Self hosting could easily amount to ~1000 USD a month amortized across many developers. In rush hours - there will be hard rate limits.

Would that 1500-1000=500$ monthly USD justify the 10% decrease in "AI Productivity" ? I guess not. In most cases.

For everyone that asks me around, I'd say that in short term, unless there's a really good reason to self host these coding assistant models, then the big 2/3 coding assistants providers are the better choice.

No one got fired from licensing claude code.

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

#250

Post by datsci_est_2015 »

john01dav wrote: post #236

Why isn't self hosting (even just renting a GPU server, not necessarily on premise) at large companies or hosting via something like together AI to run the open weight models not more common? I've tried the open weight models and the premium models like Opus and Gemini Pro, and I find that the latter are a little better, but not nearly to the degree to justify the extreme price difference, since the differences large…

There’s probably plenty of money to be made in LLMs as a service - but not enough time has passed for the commodification to occur. I’m with you in that when the dust settles I don’t think any of the frontier model providers will have a moat. Just like during the dotcom boom a catchy URL and a webpage that could accept payments wasn’t a moat, either.
Post reply on HN