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

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

#741

Post by vidarh » Thu, Jun 04, 2026, 4:58 PM UTC

White_Wolf wrote: post #638

vidarh wrote: post #331

Earlier quoted context omitted.

We can tell that the inferencing costs for many of these models are low enough that these models are being sold close to real costs on the basis that many of them are open weight and available from third party providers who have no incentive to subsidize them. I think the frontier labs will need to drop their high per-token prices at least for their low and mid-level models for the reason that several Chinese models…

I really doubt Deepseek is subsidised. It's roughly the same price everywhere you look. Deepseek is using the Huawei hardware (as far as I managed to understand from various articles) and hence the savings.

I didn't suggest it was. I pointed out that some of the subscriptions offered by the Chinese labs probably are. Not the per token API prices.

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

#742

Post by hylaride » Thu, Jun 04, 2026, 4:59 PM UTC

xyzsparetimexyz wrote: post #694

dubcanada wrote: post #686

Earlier quoted context omitted.

Don't know why people keep parroting this, this is incorrect. Chinese electricity prices are equal or slightly cheaper then most of North America. But significant pockets such as those around the Quebec or other hydro plants are significantly cheaper then Chinese power pricing. Not only that, China may subsidize AI, but so does the US.

Okay interesting. I presume that China also has low cost areas too no? Their grid at least seems more stable. Datacenter construction is more likely to raise prices in the US than there.

China's grid has had some serious issues over the past decade that didn't get widely reported for all the reasons you can think of. Some of them were exasperated by poor planning and censorship making it hard to hold anybody accountable. Not to say that they don't/didn't eventually work on it, but there was a widely held belief that the people at the top weren't even aware of the issue until foreign firms were directly impacted. This is not to say they can't or won't expand come hell or high water, though.

https://www.bbc.com/news/business-58733193 https://www.cbc.ca/news/business/china-power-cuts-1.6193281

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

#743

Post by jon_adler » Thu, Jun 04, 2026, 5:03 PM UTC

reddec wrote: post #660

c7b wrote: post #652

1,5k. For two months of that spend you could buy a machine that can self-host decent models, plus a year's worth of electricity. It's not up there in terms of quality, but with a bit more effort it works pretty decently. I'm completely baffled that that's not way more common, is it really just the quality?

Second here. From recent Alibaba Qwen conference: the all-in-one box (DC in a box - I think I was called Apsara, 0.6x0.6x1.5m) plug and play, 1.5TB GPU RAM, capability to run in a fully air gapped environment, any open models... All of that is roughly $300k one time. And this box can do non LLM tasks as well. Performance (throughput) around 20k t/s. Delivery time - around 2 months. For any medium sized company its pe…

Where can I find more information on this? A web search didn’t reveal much for me.

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

#744

Post by aiisjustanif » Thu, Jun 04, 2026, 5:04 PM UTC

lavezzi wrote: post #228

_jab wrote: post #186

Earlier quoted context omitted.

It's pretty simple; organizations are willing to tolerate paying $1500/month/engineer, which seems to be roughly inline with "normal" consumption for most full-time engineers. If that number grows significantly, then I bet companies will start exploring flash models more, as you propose.

They are willing to tolerate it now, which is quite a switch up from the free for all we had a few weeks ago, and if they aren’t able to tie in this new ~$1500p/m cap to demonstrable productivity and revenue increases then that will be kneecapped even faster

I mean we saw this with cloud spending and especially with logging and database read write cost across numerous companies.

It’s a clear pattern in service delivery for software for a while now. Hell for many goods and services in general, like Uber rides themselves.

Start cheap, get some vendor lock in, service provider reduces discounts, consumer notices and then reacts to the price by reducing consumption.

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

#745

Post by simplyluke » Thu, Jun 04, 2026, 5:15 PM UTC

newsoftheday wrote: post #736

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…

> $330k/year For a traditional software engineer? I retired last year after 3 decades and my salary was about the same as it was in the early 2000's at the last company I was at. Maybe I should have negotiated more but I thought only FAANG paid traditional pre-AI engineers more than $250K.

Uber's comp packages are probably right in line with that. Tech salaries are trimodal, and uber's right in line with the big public tech companies.

https://newsletter.pragmaticengineer.com/p/trimodal

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

#746

Post by hylaride » Thu, Jun 04, 2026, 5:43 PM UTC

simonw wrote: post #700

_fizz_buzz_ wrote: post #681

Earlier quoted context omitted.

My understanding is that a lot of AI data centers are still heavily relying on spinning HDDs, which is why seagate, western digital are selling more HDDs than ever before.

Huh, TIL. Here's the Seagate financials for Q3FY26: https://s24.q4cdn.com/101481333/files/doc_financials/2026/q3... "Hard Drive exabyte shipments of 199EB, up 39% YoY, with ~90% shipped to data center customers" "Data center revenue of $2.5B, up 55% YoY, driven by strengthening cloud and enterprise demand" And an article: https://www.seagate.com/stories/articles/the-ai-era-doesnt-r...

Spinning drives are still the "best" for data density and if the IO is sequential (which wouldn't surprise me with AI training workloads), the performance delta may not be that bad vs SSDs. As always, it depends on use case.

I know that a lot of cloud storage has tiered models, where the "expensive, but faster" tiers are SSDs, but then the slower cheaper tiers are HDDs, and the "cold storage" can be HDDs that are turned off all the way to tiers like AWS's S3 "deep archive glacier" tier being tape drives.

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

#747

Post by adamgordonbell » Thu, Jun 04, 2026, 5:43 PM UTC

SR2Z wrote: post #739

dubcanada wrote: post #686

Earlier quoted context omitted.

Don't know why people keep parroting this, this is incorrect. Chinese electricity prices are equal or slightly cheaper then most of North America. But significant pockets such as those around the Quebec or other hydro plants are significantly cheaper then Chinese power pricing. Not only that, China may subsidize AI, but so does the US.

China averages 7¢/kWh, almost 1/3 of the US average at 19¢/kWh. My rates (before PG&E were forced to concede) were as high as 49¢/kWh, a 7x factor. These are residential rates and not industrial ones, but I hope my point is clear. China has very cheap power compared to the US, there's a reason why they had to ban bitcoin to get rid of miners.

Quebec has lower rates then 7¢/kWh at data center / wholesale level. Quebec spot market runs negative sometimes, apparently. And Oklahoma has cheap power, and probably other places. Not sure your utility bill is the place to get accurate numbers.

    "Mean wholesale electricity prices in 2024 were lowest in SPP ($27.87/MWh), the Southeast ($29.72/MWh), and Southern California ($29.95/MWh), and highest in the Northwest ($59.98/MWh)."

https://www.ferc.gov/sites/default/files/2025-03/25_State-of...

If my math is right, divide those by 10 for cents per kWh

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

#748

Post by camdenreslink » Thu, Jun 04, 2026, 5:44 PM UTC

sfn42 wrote: post #142

sevenzero wrote: post #124

Earlier quoted context omitted.

I wish I could disable most of these. I already hate all the "oh you're actually right, let me fix that" nonsense. Then it proceeds to burn 50k tokens on the git history instead of copying logic A from a different part of the codebase to logic B, where I want that exact logic without having to write the boilerplate myself...

A lot of the time if you're copying code from one place to another what you actually want to do is abstract it so you can reuse it in both places. The LLM can easily do this type of stuff, just tell it and it'll happily do it. This is exactly what I mean when I tell people they need to work closer with the AI, tell it how to do things. Don't just tell it what to do and get frustrated when it does it differently than…

There are a lot of instances where you don't want to create an abstraction that will tie two disparate areas of the code together even if they happen to be using a similar pattern you want to copy. For example, when you expect their implementations to diverge in the future.

I have experienced enterprise codebases that have been DRY'd to the point they become ossified.

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

#749

Post by sfn42 » Thu, Jun 04, 2026, 5:51 PM UTC

camdenreslink wrote: post #748

sfn42 wrote: post #142

Earlier quoted context omitted.

A lot of the time if you're copying code from one place to another what you actually want to do is abstract it so you can reuse it in both places. The LLM can easily do this type of stuff, just tell it and it'll happily do it. This is exactly what I mean when I tell people they need to work closer with the AI, tell it how to do things. Don't just tell it what to do and get frustrated when it does it differently than…

There are a lot of instances where you don't want to create an abstraction that will tie two disparate areas of the code together even if they happen to be using a similar pattern you want to copy. For example, when you expect their implementations to diverge in the future. I have experienced enterprise codebases that have been DRY'd to the point they become ossified.

That's why I said "a lot of the time". Not always. And it's not really a problem to de-DRY things, literally just copy/paste and make the change you want. The bigger problem in my eyes is when the requirements start to diverge people just add an if branch and soon you have a function/component that does 7 different things depending on how it's used and it's a big buggy mess.

It's also possible in many of these cases to identify sub-patterns you could abstract, to create a set of tools you can compose in different ways in order to satisfy the different use cases. Instead of one function/component you make multiple, and use them together.

All this stuff is just basic programming but I've mostly given up trying to preach about it. Most people don't care, and even if they did care they just don't have the talent to write really good code. It's rare to find a dev who does really solid work. In my experience you either do it because that's who you are, or nothing I say will make any difference.

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

#750

Post by closeparen » Thu, Jun 04, 2026, 5:52 PM UTC

newsoftheday wrote: post #736

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…

> $330k/year For a traditional software engineer? I retired last year after 3 decades and my salary was about the same as it was in the early 2000's at the last company I was at. Maybe I should have negotiated more but I thought only FAANG paid traditional pre-AI engineers more than $250K.

There is a tier just outside of FAANG that pays similarly or better, prominent examples being Uber, Airbnb, Stripe, Block, Databricks, Datadog, Pinterest, Snowflake, etc.