The problem with AI is that, this time, nobody was caught off guard. From small startups to tech giants, everyone bet heavily on it. There are very good open-weight Chinese models, and even a French miracle. There is no winner-take-all.
So models are already a commodity, and will remain one for years. Companies must balance capex with very long payback periods against strict austerity everywhere else.
Welp that’s not a good sign for the anthropic IPO. Curious what happens now that both OpenAI and Anthropic will face budgetary pressure. I don’t think they can raise prices, as it’d just open ppl to switch to Open source models.
Sure, but, in absence of money, where are the open models going to come from? They take a lot of effort and resources to train. The current ones have been made in hope the growth will lead to a payoff one way or another. With the two main giants struggling and the market cooling, that payoff becomes quite uncertain.
The work going on to improve things on single card like a 3090 is nuts. HyperQwen, other things. I have my subscriptions, but always good to explore options.
You have to understand that Strata and HyperQwen are giving you good looking tokens per second but are not giving you anything close to the bf16 model’s capability (they quantize, worse they quantize KV caches, they approximate expert routing etc.)
The models are so impressive that getting 70-80% of their capability can be helpful, but beware, you are using a significantly dumber model.
Selling the same product. It doesn't matter who is running the neural network, the utility derived from the neural network has nothing to do with the name of the company.
No, they sell different products in the same category. You are basically saying Google and Bing as the same product when Bing is superior to Google search in some non-critical metrics.
Because they are? Google and Bing are the same product - search engines. Just like Ford and Ferrari both sell cars, whether you think one is "better" or not.
it’s kinda crazy but i do think we’re seeing a turn
my company was easily spending $1m/month on tokens (hit 1.2m september)
sonnet 5.5 drops - we barely cracked $600k this month
it has to go down too, carbon is interesting, china has qwen 4 soon
coding isn’t sustainable growth - RLRVF is really effective for software development - labs are cracking the code, these models will have to get better at other things to be worth it
How does this affect OpenAI's prospects in the next few quarters?
Unlike Anthropic, OAI does not have an S-1 to pore over. Their finances are shrouded in rumor and speculation. I can't assess how much of a death knell a ~15B financing shortfall is.
If this is being announced here, it was probably started at least a few months ago, and at that point funding was likely looking a lot more forthcoming, so it would make sense to try to raise more than is strictly necessary if the price is good. On that basis, it might not be a problematic shortfall.
Nobody on the outside knows for sure, but two key signals to watch are project sunsets and brain drain.
If the rumors of fundraising difficulties are true, OAI will have to prioritize its most profitable projects, potentially slowing down new training runs and optimizing existing models for efficiency at the expense of user experience.
Insiders are also the first to sense internal trouble, so if top talent starts leaving for competitors preparing to go public, it won't bode well for the company.
It's frightening to me that single companies' valuations can vary by that much. The stock exchange is the Adam Smith way of directing the assignation of resources to the most efficient company, and it's supposed to be liquid enough to allow fine-grained decisions.
If an open source model locally does one job correctly, lets say writing the code, then what really do we need OpenAI and Claude for? But I guess there might be some time in that.
That’s why the Mac mini and studio are selling like hotcakes. Massive unified memory with massive cpu performance, with a solid hardware. If I had 3-4K burning a hole in my pocket I know what I’d be getting.
Maybe at first, but server hardware doesn't stay deployed tooo long and ends up liquidated. That was always a looming problem with this rapid buildout. Some hosts like OVH or Hetzner might swipe up some second hand gear, they're not afraid of renting old hardware. But eBay will be flooded once the DCs upgrade / downscale. And it wont be cheap at first either I bet. Everyone will try to cash in on the secondary market hype.
Inference will keep getting cheaper and cheaper though. Perhaps model releases will be fewer and farther between because these groups can't affording paying out a billion or more in training each generation
Yeah, but Wright's law (cost of making the n^th something (like a token) being exponentially less than the cost of making the first) strongly suggests that post-bubble inference will be significantly cheaper the longer the bubble lasts.
Whether that's a good thing considering the other things those dollars could be going towards...
I mean I'm happy for better but it might start grounding the industry where 1.6% better on some benchmarks doesn't justify hundred million investments.
Over last 3 years on HN I have seen such low quality comments : prophesizing the end of times - the bubble will burst and we will all be so happy after that.
Any tiny news article that indicates even a modicum of challenges for OpenAI will be met with slurry of such comments.
Perhaps it’s good to keep a good epistemic hygiene in all this. OpenAI isn’t going away anywhere soon. AI isn’t going away, in fact we haven’t even started yet.
It's a reaction to the constant drum beat of doom marketing:
- "our product is too dangerous to release but we can't be bothered to prove its capabilities working in public hacking competitions"
- "our product is going to kill everyone"
- "our product is going to take all the jobs"
- "we have a $40T addressable market"
- "in a few days AI will be able to improve itself without human intervention and it's capabilities will hocky stick to infinity!!!"
Followed by absurd financials that spin massive losses as "getting in on the ground floor" before historic profits arrive based on the doom marketing above.
No one is saying AI is going away soon). But OpenAI and Anthro will go the way of Netscape when the market finally stops blindly accepting the doom marketing. Anyone with eyes can see LLMs will create historic increase in productivity among knowledge workers AND it will be a commodity. The massive profits frontier labs need to justify valuations are not coming.
There are AI bears and AI bulls. It's easy to cherry pick extreme and clearly wrong statements from each. But if you actually believe the bears are the more extreme/wrong overall you just aren't paying attention to what the bulls are saying.
You have conflated two completely unrelated concepts. LLMs aren't going anywhere, but what good does that do a company burning hundreds of billions to do 20% better than Chinese models trained with millions? The economics don't economic.
It's far too late for a prescription now because they're already committed to hundreds of billions in spending they don't have, but the reason Chinese companies will win the long game is because they are serious and the Americans are deeply unserious. From the beginning, Chinese labs have viewed LLMs as software tools and developed efficiently. Conversely, Americans are selling a fantasy about creating the machine god if they just throw another hundred billion at it every few months. Altman, Amodei, and Musk are all pathological liars who have oriented their entire companies around deceiving investors and marketing hype rather than engineering principles. They are unbelievably successful at what they set out to do, but what they set out to do was not to build a long-lasting foundation for success.
There's no should, only what economics incentivize. Right now we're not paying for the upfront training costs-it's great, the Millennial subsidy continues. But if, and big if right now, the infinite money font dries up and they have to recoup training investment direct from customers then that looks to be a huge price increase on the ground which makes cheap to train and good enough even more attractive than it already is.
Can also be read as observation, as I have observed that many colleagues haven't started yet using AI on a daily basis and I myself is still using methods from months ago (no agent orchestration).
At this point AI company valuations only make sense if each of them captures most of the value of the entire IT sector. Soon. If that doesn’t happen, it’s a matter of time before reality catches up, but how much time? Who knows. It could be years still.
Or AI could in the next few years generate more value than the whole IT sector a few times over. That would be cool.
The problem with AI is that, this time, nobody was caught off guard. From small startups to tech giants, everyone bet heavily on it. There are very good open-weight Chinese models, and even a French miracle. There is no winner-take-all.
So models are already a commodity, and will remain one for years. Companies must balance capex with very long payback periods against strict austerity everywhere else.
Good news for customers, BTW.
Welp that’s not a good sign for the anthropic IPO. Curious what happens now that both OpenAI and Anthropic will face budgetary pressure. I don’t think they can raise prices, as it’d just open ppl to switch to Open source models.
Sure, but, in absence of money, where are the open models going to come from? They take a lot of effort and resources to train. The current ones have been made in hope the growth will lead to a payoff one way or another. With the two main giants struggling and the market cooling, that payoff becomes quite uncertain.
The work going on to improve things on single card like a 3090 is nuts. HyperQwen, other things. I have my subscriptions, but always good to explore options.
You have to understand that Strata and HyperQwen are giving you good looking tokens per second but are not giving you anything close to the bf16 model’s capability (they quantize, worse they quantize KV caches, they approximate expert routing etc.)
The models are so impressive that getting 70-80% of their capability can be helpful, but beware, you are using a significantly dumber model.
open weight, "how we trained it" is the open source of LLMs
They are two different companies
Selling the same product. It doesn't matter who is running the neural network, the utility derived from the neural network has nothing to do with the name of the company.
No, they sell different products in the same category. You are basically saying Google and Bing as the same product when Bing is superior to Google search in some non-critical metrics.
Folks certainly have their preferences, but I think most consider each company's roughly equivalent models to be of the same quality.
It's more like a duopoly where the top two leaders have meaningful market share. Airbus and Boeing is more apt than Bing and Google.
I would also say that Google and Bing are roughly the same thing fwiw.
Because they are? Google and Bing are the same product - search engines. Just like Ford and Ferrari both sell cars, whether you think one is "better" or not.
Stupid post. Microslop dedicated little resource to bing.
Both OAI and Anthropic are rivals throwing immense resources in direct competition in producing the best product in the SAME CLASS.
Better comparison is Pepsi vs coke or Home Depot vs Lowe’s.
Like, no name of a company must or has to have anything to do with the product itself.
Thanks for the insight, Sherlock
it’s kinda crazy but i do think we’re seeing a turn
my company was easily spending $1m/month on tokens (hit 1.2m september)
sonnet 5.5 drops - we barely cracked $600k this month
it has to go down too, carbon is interesting, china has qwen 4 soon
coding isn’t sustainable growth - RLRVF is really effective for software development - labs are cracking the code, these models will have to get better at other things to be worth it
The end state is OpenAI as a division of Microsoft.
At this rate ANT will end up as a division of Amazon
I mean the super groups are going to break up and make their own bands.
My only request is to keep Opus 5.5 alive
How does this affect OpenAI's prospects in the next few quarters?
Unlike Anthropic, OAI does not have an S-1 to pore over. Their finances are shrouded in rumor and speculation. I can't assess how much of a death knell a ~15B financing shortfall is.
If this is being announced here, it was probably started at least a few months ago, and at that point funding was likely looking a lot more forthcoming, so it would make sense to try to raise more than is strictly necessary if the price is good. On that basis, it might not be a problematic shortfall.
Nobody on the outside knows for sure, but two key signals to watch are project sunsets and brain drain.
If the rumors of fundraising difficulties are true, OAI will have to prioritize its most profitable projects, potentially slowing down new training runs and optimizing existing models for efficiency at the expense of user experience.
Insiders are also the first to sense internal trouble, so if top talent starts leaving for competitors preparing to go public, it won't bode well for the company.
oh but that's nothing... consider all previous financing episodes and the companies involved
this is more about the supply and demand of capital in any given moment than it is about the outlook of the company.
as a litmus test: would you turn down the opportunity to buy OpenAI shares at this current valuation?
Wow! Its bursting...
The subheading in the article is telling, and doesn't appear to demonstrate anything I would describe as "bursting"
> The ChatGPT maker’s latest funding round values it at $1.25 trillion, less than its $1.4 trillion target
The investments these companies are making depends entirely on the confidence that number go up, a lot, very quickly and soon.
Number go down, or even not go up as much as expected, is not good. These valuations are entirely matters of confidence. When that goes away…
Fear is central which eventually will find its way in the public market.
It's frightening to me that single companies' valuations can vary by that much. The stock exchange is the Adam Smith way of directing the assignation of resources to the most efficient company, and it's supposed to be liquid enough to allow fine-grained decisions.
That's 150B shaved off like it's nothing lol
Is there even a way to professionally decide if a company's value is 1.25 or 1.4 Trillion?
I always kind of suspected that those are somehow derived numbers, but arbitrary for the most part.
If an open source model locally does one job correctly, lets say writing the code, then what really do we need OpenAI and Claude for? But I guess there might be some time in that.
That’s why the Mac mini and studio are selling like hotcakes. Massive unified memory with massive cpu performance, with a solid hardware. If I had 3-4K burning a hole in my pocket I know what I’d be getting.
You won't. It will become something you install like a browser.
Not looking very good fellas, Bot Swarm breaches, microslop laying off 27% of their workforce.
If you have a billion users and 90% + are freeloaders, you need social media style ads to support growth, which no one likes.
Plus they are all out of data training sets, they are buying zombie companies for their data.
There are dozens of distillated clones, which are getting better every release.
The only moat is expensive data centre builds with on-loan Nvidia inference and the Chinese embargo fears.
Good luck out there.
What else can you expect? Look the markets right now. Its bleeding. Started with China and now US.
No no no, don’t burst that AI bubble just yet. I haven’t finished all my side-projects.
Once the bubble bursts we can finally sweep up the datacenter GPUs and jerry rig them to our home servers!
I literally can't wait.
They will probably go to other data centers or company premises.
Maybe at first, but server hardware doesn't stay deployed tooo long and ends up liquidated. That was always a looming problem with this rapid buildout. Some hosts like OVH or Hetzner might swipe up some second hand gear, they're not afraid of renting old hardware. But eBay will be flooded once the DCs upgrade / downscale. And it wont be cheap at first either I bet. Everyone will try to cash in on the secondary market hype.
After you upgrade your electric panel and cooling.
Winter is coming.
The government will just nationalize them and use all the compute for poorly defined military tasks
Or to further build out total domestic surveillance, like they've been telegraphing.
Use Ultra mode.
The consumer-level services you've gotten used to will still exist no matter how hard the bubble bursts, if it ever does. Way too many players now.
Sure, but you'll have to pay for what it really costs
If the capital cost gets written off, because it can never be recouped, then there’s only the operating cost left.
Suppose OpenAI goes bust tomorrow and all those data centres get sold for pennies on the dollar. Whoever buys them can operate them at cost.
I thought the incremental supply cost per token wasn’t that high, and the main expense for these companies was the training they do on top of that?
Inference will keep getting cheaper and cheaper though. Perhaps model releases will be fewer and farther between because these groups can't affording paying out a billion or more in training each generation
Yeah, but Wright's law (cost of making the n^th something (like a token) being exponentially less than the cost of making the first) strongly suggests that post-bubble inference will be significantly cheaper the longer the bubble lasts.
Whether that's a good thing considering the other things those dollars could be going towards...
The chinese models are being trained for less than a million a pop.
I mean I'm happy for better but it might start grounding the industry where 1.6% better on some benchmarks doesn't justify hundred million investments.
I have only ever paid per token for this reason: if I can’t generate sufficient value to cover the real cost I don’t want to invest in using it
.. which will be the same you are paying today. Token prices are already above their operating costs.
If you're talking about free tiers, yes, that might change as marketing budgets will shrivel up.
Over last 3 years on HN I have seen such low quality comments : prophesizing the end of times - the bubble will burst and we will all be so happy after that.
Any tiny news article that indicates even a modicum of challenges for OpenAI will be met with slurry of such comments.
Perhaps it’s good to keep a good epistemic hygiene in all this. OpenAI isn’t going away anywhere soon. AI isn’t going away, in fact we haven’t even started yet.
It's a reaction to the constant drum beat of doom marketing:
- "our product is too dangerous to release but we can't be bothered to prove its capabilities working in public hacking competitions" - "our product is going to kill everyone" - "our product is going to take all the jobs" - "we have a $40T addressable market" - "in a few days AI will be able to improve itself without human intervention and it's capabilities will hocky stick to infinity!!!"
Followed by absurd financials that spin massive losses as "getting in on the ground floor" before historic profits arrive based on the doom marketing above.
No one is saying AI is going away soon). But OpenAI and Anthro will go the way of Netscape when the market finally stops blindly accepting the doom marketing. Anyone with eyes can see LLMs will create historic increase in productivity among knowledge workers AND it will be a commodity. The massive profits frontier labs need to justify valuations are not coming.
There are AI bears and AI bulls. It's easy to cherry pick extreme and clearly wrong statements from each. But if you actually believe the bears are the more extreme/wrong overall you just aren't paying attention to what the bulls are saying.
> OpenAI isn’t going away anywhere soon. AI isn’t going away
You have conflated two completely unrelated concepts. LLMs aren't going anywhere, but what good does that do a company burning hundreds of billions to do 20% better than Chinese models trained with millions? The economics don't economic.
According to your argument, OpenAI should simply stop R and D which can result in massive jumps in performance because China may catch up?
What is your prescription if I may ask? Don’t invest in research? Let China do it?
It's far too late for a prescription now because they're already committed to hundreds of billions in spending they don't have, but the reason Chinese companies will win the long game is because they are serious and the Americans are deeply unserious. From the beginning, Chinese labs have viewed LLMs as software tools and developed efficiently. Conversely, Americans are selling a fantasy about creating the machine god if they just throw another hundred billion at it every few months. Altman, Amodei, and Musk are all pathological liars who have oriented their entire companies around deceiving investors and marketing hype rather than engineering principles. They are unbelievably successful at what they set out to do, but what they set out to do was not to build a long-lasting foundation for success.
There's no should, only what economics incentivize. Right now we're not paying for the upfront training costs-it's great, the Millennial subsidy continues. But if, and big if right now, the infinite money font dries up and they have to recoup training investment direct from customers then that looks to be a huge price increase on the ground which makes cheap to train and good enough even more attractive than it already is.
Can you read?
You know "we haven't even started yet" is also prophesying, right?
Can also be read as observation, as I have observed that many colleagues haven't started yet using AI on a daily basis and I myself is still using methods from months ago (no agent orchestration).
Sometines it truly feels like titles of YouTube videos.
It is the α's and Z's brigading in with their over-emotional shortsighted groupthink.
1. GPT-4.5 launch. "AI crash is gonna lead to decade long winter." https://news.ycombinator.com/item?id=43206226
2. Claude Code limits tightened. A commenter expects the bubble to pop, while arguing AI will succeed long term. https://news.ycombinator.com/item?id=44599297
3. GPT-5 disappoints. "Teetering on the edge of a huge bubble pop." https://news.ycombinator.com/item?id=44966583
4. DeepSeek releases a cheaper model. A commenter expects excess data-centre capacity when the bubble bursts. https://news.ycombinator.com/item?id=45413548
5. AMD signs an OpenAI chip deal. A commenter predicts a bubble pop and a flood of cheap GPUs. https://news.ycombinator.com/item?id=45491514
6. Discussion of AI-assisted open-source contributions. A commenter says models must improve soon or the bubble will pop. https://news.ycombinator.com/item?id=45745326
7. Discussion of Opus 4.5 coding. A commenter advises using cheap AI tools before the bubble bursts. https://news.ycombinator.com/item?id=46521192
8. GitHub Copilot moves to usage-based billing. "The bubble has burst." https://news.ycombinator.com/item?id=47929404
9. DeepSeek runs on one AMD accelerator. A commenter predicts a bubble pop will flood the hardware market. https://news.ycombinator.com/item?id=49166790
10. Same DeepSeek thread. "AI is overvalued, so it WILL pop." https://news.ycombinator.com/item?id=49167787
Edit: more examples
1. AI on an old CPU: coding gains don’t justify investment; bubble will burst. https://news.ycombinator.com/item?id=48938412
2. Nvidia–OpenAI deal stalls: GPU bubble, inflated demand. https://news.ycombinator.com/item?id=46834749
3. Lisp machines retrospective: AI bankruptcies and another bubble. https://news.ycombinator.com/item?id=45990309
4. Nvidia customer concentration: AI bubble will pop despite useful technology. https://news.ycombinator.com/item?id=41411258
5. DeepSeek open-source announcement: inflated AI valuations will collapse. https://news.ycombinator.com/item?id=43126535 https://news.ycombinator.com/item?id=43126619
6. OpenAI–AWS deal: spending commitments could bring everything crashing down. https://news.ycombinator.com/item?id=45802550
7. Anthropic funding: final big push before the bubble bursts. https://news.ycombinator.com/item?id=45105333
8. Enterprise AI adoption: disappointing returns will pop the bubble within two years. https://news.ycombinator.com/item?id=48025025
9. OpenAI cash burn: railroad-style bubble and massive investment downturn. https://news.ycombinator.com/item?id=46439964
At this point AI company valuations only make sense if each of them captures most of the value of the entire IT sector. Soon. If that doesn’t happen, it’s a matter of time before reality catches up, but how much time? Who knows. It could be years still.
Or AI could in the next few years generate more value than the whole IT sector a few times over. That would be cool.
OOC did you have this list prepared? You posted it very quickly as a response
Like I said, brigading botlike behavior.