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

584 points by pdyc a day ago

https://www.bloomberg.com/news/articles/2026-06-02/uber-caps... (https://archive.ph/ZrwAy)

> 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 models like DeepSeek. I wonder if China's really subsidising the providers, or if inferencing costs are actually much lower, and Anthropic/OpenAI are just making sure no money's left on the table for their eventual IPOs.

vidarh - 21 hours ago

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 (at least Qwen, DeepSeek, Kimi and GLM) are "close enough" that with the right harness they are cost effective alternatives.
They won't necessarily need to close the gap - at least not yet -, because these models won't necessarily compete at the same token counts. E.g. at least some of them need to do far more work to solve the same problems.
But, yeah, the prices will come down one way or the other.
At the same time, even the subscriptions for the cheap Chinese models are probably subsidised, and those subscriptions are likely to get less generous over time.
- White_Wolf - 9 hours ago
  
  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.
  - vidarh - 2 hours ago
    
    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.
  - xyzsparetimexyz - 7 hours ago
    
    And Chinese electricity prices are some of the lowest
    
    dubcanada - 6 hours ago
    
    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.
    
    SR2Z - 2 hours ago
    
    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.
    
    adamgordonbell - an hour ago
    
    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
    
    xyzsparetimexyz - 5 hours ago
    
    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.
    
    hylaride - 2 hours ago
    
    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
  - vablings - 4 hours ago
    
    Yeah, this argument is bullshit. You can head over to Openrouter and look at the token cost for deepseek-v4-flash and deepseek-v4-pro. They are very competitive on the open market
- bel8 - 7 hours ago
  
  Add MiMo 2.5 to the list. Priced like DeepSeek, performs similarly but it also has vision capability.
dgellow - a day ago

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 a depreciating commodity“[0].
So you have on one end the token revenue trending down, on the other end the training cost going up for the next frontier models, and you need to pay back your 10y debt.
0: https://youtu.be/wGZboZcSGDY?is=64GuKyqBh_4aSjTE
- missedthecue - a day ago
  
  "So you have on one end the token revenue trending down, on the other end the training cost going up for the next frontier models, and you need to pay back your 10y debt."
  Not necessarily, the bond holders could simply take a massive hair cut and lose shitloads of money. On the topic of bubbles and exuberance, Jeff Bezos made the salient point that there was a massive over-invested biotech boom in the 1990s and tons of sophisticated investors ended up losing lots of money. But humanity still kept the medical advancements made by the boom. Stocks going down didn't un-research drugs, and it won't un-research new GPUs or un-build datacenters.
  - solatic - 13 hours ago
    
    > Stocks going down didn't un-research drugs
    Drugs cost pennies to manufacture after they are researched and make their way through the approval pipeline. There are many generic drug manufacturers who can work off the existing formulas.
    The more apt comparison is that LLMs won't be un-trained. Opus 4.8 now exists. Even if Anthropic somehow went bankrupt, that particular asset could, at the very least, be sold for proverbial pennies on the dollar to a "generic" inference provider.
    
    saalweachter - 9 hours ago
    
    Research does get lost over time. The whole point of the patent system is keeping that from happening; if the drug company goes bankrupt, even if they lose all their internal documentation in the process, hopefully the patents and other public paperwork provides enough information for an unrelated company -- either having acquired the patent rights, or after the patent period ends -- to reconstruct the processes with less investment then the original research.
    If a bankrupt AI company maintains enough of a skeleton crew to consolidate and archive its intellectual property it could be sold off to another company, but there are also timelines where it all ends up digital dust in the wind.
    
    alfiedotwtf - 4 hours ago
    
    > If a bankrupt AI company maintains enough of a skeleton crew to consolidate and archive its intellectual property it could be sold off to another company, but there are also timelines where it all ends up digital dust in the wind.
    Only if that skeleton crew had deep deep pockets. If Anthropic closed their doors tomorrow because the market collectively saw that AI was not profitable and so open sourced everything, there wouldn't be any money to train Opus 5.0... it would then have to fall on governments to put money into the hat (which I can't see happening unless it was Europe)
    
    eecc - 12 hours ago
    
    Or locked away in litigation for decades… See what became of the Amiga
  - 20k - 12 hours ago
    
    Datacentres aren't the same as infrastructure or research though. All the hardware in them has a finite, useful lifespan. In 10 years time it'll be totally useless
    Hardware fails, and also scales out in terms of efficacy to run it as more power efficient, modern hardware turns up. It requires constant investment to keep it useful, and cost efficient
    When AI pops, we'll temporarily have some extra compute capacity that will be horrendously uneconomical to run due to the high grid load and low consumer demand, before they get shutdown. There's simply no real use for them at this scale
  - dgellow - 10 hours ago
    
    Those data centers are specifically for AI workloads. Let’s say everything crashes and we now have all the data centers, what do you do with them? GPU are pretty specialized hardware, without AI a data center full of outdated graphics cards isn’t really too valuable.
    It’s really not obvious the infrastructure we are building for AI stuff is something that will benefit humanity over time.
    Without talking about the fact that bubbles are extremely destructive. Bezos is obviously someone who came out ok from the dotcom bubble but we are talking about something that destroys a lot of value globally. That has real, direct consequences, not just investors losing some money. The US economy is currently only growing because of the AI bet
    
    helloplanets - 6 hours ago
    
    AI data centers are being already used at max capacity, aren't they? I have a hard time imagining people would suddenly use AI less than they do as of today, let alone collectively drop it altogether. So the worst case scenario is that they'd need to be auctioned off way under what they'd be worth now, but still for someone to use them for AI.
    Inference is much cheaper than training a new model, so running them just for inference is a completely different thing than having to price in the fact that at the moment all of these companies need to compromise between compute for inference and compute for training new models. If no new models were to be trained, and all the compute was inference only, that would change everything when it comes to the overall compute cost of AI.
    Dotcom infra buildup is a bad comparison, in that it wasn't even close to being all utilized. The infra was completely overproportional to the day to day usage.
    
    cduzz - 3 hours ago
    
    AI data centers that exist and are operational are running at maximum capacity. That's why you see things like the tiny little data center run by xai showing up as a valuable resource to xai (on the sale side) and anthropic (buy side). It is "only" 300 megawatts and there's a 1.25 billion rent on it per month.
    If all these other data centers were anywhere near coming on line, that 300mw data center would be a rounding error not a line item as it is right now.
    So someone's signed contracts for way more and way larger data centers, someone's purchased billions in hardware for these not yet operational data centers. I'm wondering how depreciation's going to work on all these assets...
    Anyhow, I'm not really sure what "max capacity" is here, nor am I really aware when they're going to be delivering the operational assets that are currently levered to their eyeballs and consuming 1/3rd of the memory made on the planet.
    As far as inference vs training, have new gotten radically better than old models or only marginally (at the cost of 10x or more the training costs)?
    Very exciting stuff.
    
    overgard - 2 hours ago
    
    I imagine the trend for AI usage will go up over the very long term (5-10yrs etc.), but short term how much usage is being propped up by employer's forcing their employees to use it? Or by user's being curious about the novelty but ultimately abandoning it if it doesn't do what they want? It'll be interesting to see what changes as tokenmaxxing disappears.
    
    abirch - 3 hours ago
    
    I would day that the dotcom was directionally correct but the timing was wrong. For instance you had pets.com in 1999 but in 2020 you had chewy.com. It's like you had broadcast.com in 2000 but by 2020 you had YouTube that was making more in ad revenue than the next 4 largest competitors.
    With investing timing matters a lot.
    
    inemesitaffia - 10 hours ago
    
    You sell the GPU's to remote gaming companies.
    Replace servers with regular compute.
    
    overgard - 2 hours ago
    
    I imagine that the big incentive for remote gaming would be massive price increases in gaming hardware driven by the AI industry...
    If the AI industry collapses, it would seem like the price of DDR etc. would dramatically decrease and lower demand for remote gaming
    
    GuB-42 - 7 hours ago
    
    AI GPUs have terrible graphical capabilities, if at all. They can run shaders, but they are lacking in texture units, rasterization, etc... huge bottleneck here.
    These AI "GPUs" are worse for gaming than even the crappiest actual GPUs (with a G as in Graphics). Also, the display drivers won't support them, not officially at least.
    
    marcta - 3 hours ago
    
    The G in AI GPU stands for "grift"
    
    __alexs - 9 hours ago
    
    Nvidia would have to ship game ready drivers for H100s but it could work.
    
    xyzsparetimexyz - 7 hours ago
    
    They don't have display-out. You'd have to send back the screen data over pcie to the motherboard for display.
    
    - 5 hours ago
    
    [deleted]
    
    __alexs - 6 hours ago
    
    Not exactly a problem for cloud gaming.
    
    xyzsparetimexyz - 5 hours ago
    
    Has there ever been a market for cloud gaming apart from middle class people with macbooks who casually want to play one particular game but not enough to pay for a whole PC or console?