That's Kami Kaze for US frontier labs. There's no way from here for them towards trillion dollar valuations.
That's strategic sabotage to say the least.
Ban all open weight models! Cried the VCs.
That's strategic sabotage to say the least.
Ban all open weight models! Cried the VCs.
Those valuations are a scam, they have always been a scam, like an updated version of the collateralised debt obligations (CDOs) from 2008 [0]
[0] https://www.theguardian.com/business/2010/apr/18/goldman-sac...
it worked for the big short guys because the knew exactly when it was going to go bust
I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.
This is exactly right. The only AI that matters from an investor perspective is the AI that is built into your phone, your car, ships with Windows and Mac, and built into legal and business tools like Lexus Nexus and Salesforce.
Everything else is hobby.
what's important is where big enterprise point their budgets. and there we agree, it's not to chinese models (as hopeful as I am that we can avoid a duopoly and great local models)
In that regard it was a clever marketing move by Anthropic to release their paper "Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training" ....
I find such claims a bit like if 3M/DuPont released a paper on the carcinogen dangers of PFAS and someone said this was "a clever marketing move".
Like, great, this can have hidden dangers we only learn about years after it's irreversible… how does this make "our"* companies the good guys?
A lot of us were already concerned about backdoors mandated by the US government, but that was just encryption and this is everything that AI ends up being able to do.
* in the sense of "the G7" until the start of this year, because why would other nations prefer us over China in the first place, and thanks to Trump vs. Canada, Greenland, Iceland also now the rest of the G7 has to treat seriously the possibility that the US is more of an expansionist threat than China is.
Same trick, just too naive to see it.
The only AI that makes money is enterprise. Being open weights/self-hostable is a huge win before the pricing even enters the conversation, but pricing is also adding a ceiling on what US labs get to charge. And stuff like powering other software also works better with fine-tunes, hence legal models, etc.
Currently the price sovereignty is still not outweighing the cost of US dependency. But big providers are already working on finding ways to ensure customers independence of the cloud act.
European business users (+ consumers) can access GLM-5.3 via Mistral.ai hosting. (with GDPR)
Of course the same goes for any other model that you haven't trained up yourself.
Based on HN comments, every company would be running Gentoo and developing line of business applications in Haskell or OCaml.
The reality is what ever better and cheaper is where the money flows. Especially from an international corporation perspective.
They'd be wrong. Especially about Europe. Many companies are in a bind about this: they can't upload their confidential files to a service provider but they do want AI. So right now they end up with a choice: do nothing, breach their contracts, use a service provider that pinky promises not to share their data (which we have already seen they will violate) and run local models.
The latter is the reason you can't buy powerful GPUs for reasonable prices because a local model (GLM 5.3, DS 4, etc) + some hardware is all you need to solve the problem in a way that avoids the legal issues.
Mid tier insurance co is working with local inference providers and some of these now have thousands of GPUs up and running. Don't drink the HN cool aid that the EU is a backwater where nothing happens too much or you'll end up surprised one day.
The one thing where Europe really does lag is in training, that would be fair. But inference providers are popping out of the ground like mushrooms and there are some billion euro+ projects underway. We -unfortunately- also have some scammers that are bilking (or attempting to bilk) investors pretending they have more than they do, this is annoying but I would expect that other countries have similar players as well.
There are roughly 70 GW of datacenters under construction in the US right now, and a GW is roughly 500k GPUs, so 35 million GPUs.
The point was: they're buying them from the retail channels in relatively high volume because there is a massive shortage of GPUs in general, but that does not seem to stop parties with smaller projects who do not qualify for buying directly from NV (assuming NV even has stock to sell).
5090's now sell for the same amount (or more) that you could buy an RTX 6000 for a few months ago, and RTX 6000's are ~19K and up.
I found a stash somewhere, bought two, then two more and when I was ready to buy the remainder they were all gone. Serves me right for being too careful.
They are not, not even close. I wonder if you're aware how money is being "spent" between Nvidia and US AI corporations!
Its not just the US ... Where do you think all those 5090's end up? Its just crypto mining all over again. Most people do not realize that China was the biggest crypto mining operation because of its cheap electricity and people willingness to take big risks.
The same happens now also, with people buying up 5090's (and lower class cards) in bulk, to strap into AI rigs. With Nvidia discontinuing the 32GB 5090s, we already see pressure on the lower end cards that had a better price / performance for a while now.
China will do China things *lol* ... People there are just more willing to take bigger gambles (and the cheap elec helps a ton). But that is also a factor why a lot of consumer level hardware gets under pressure. Its not just the supply chain to the enterprise market that is eating a lot for AI.
Europe isn't in a bind. They can, and have been, running open weights on inference providers around the world. And they pay a premium for US models and accept its risk for the same reason they remain US allies. The cost is worth it.
That being said it's not quite as simple as would be ideal, you do need to check whether there's an additional EULA on your specific model choice.
The perceived lack of independence of the FTC is a major driver behind the exodus on this side of the Atlantic and it isn't just the smaller players that are moving. Airbus for instance.
Now the datacenters supposedly operating under at-arms-length management are no longer sufficient for compliance.
There are calls to repeal the whole thing with respect to the US.
https://noyb.eu/en/us-supreme-court-just-blew-eu-us-data-tra...
Yes, biased source and title, but the contents are pretty good.
Well they are wrong, I'm at a large EU startup and they are currently considering Deepseek as their default model, Opus/Fable would still be available for complex tasks.
I think people don't realize the Salesforce SAP Palantir would love to ship these models, and they have/are shipping them.
The threat of exfilteration of data via these models is high but it's nowhere near as high as the margins.
For instance if you could cut your ai input bill by over 90% would you do it? Can you put some of that extra margin say 10-20% to make it more secure.
I know of atleast 10 fortune 500 companies that are entirely planning to or have moved to Chinese models for a large portion of their work.
It's insane people in finance are delusional enough to think that won't happen.
Maybe Govt will try to de-risk with bans on using open models but I don't think that's going to work at scale, people will literally spawn labs to launder DeepSeek/GLM models into a US model by some novel training etc approach or something.
I still don't think that it's as much a kami-kaze rather it's an attempt to normalize the world around the Chinese stack.
If DeepInfer is supported by everyone, it will be much easier to export stuff aka hardware that only supports it for now or is optimized for it.
Assume china starts selling hyper optimized Asics for inference at some point.
This feels like a race to the bottom as soon as possible because they have much lower costs, if there is a Wipeout in AI Labs in US chinese labs are largely insulated, and they can hopefully buy Nvidia chips for cheap if that does happen.
Because they can and there’s no consequence to drumming up fear, same shit since the days of Napoleon and Nelson…
Quite failure by someone to assume that EU businesses would use US over Chinese, based on the current political atmosphere. US causes even bigger concerns than Chinese labs.
If you think that is the choice basket to put your eggs in, best of luck.
Thanks God nothing like that could happen in the US, thanks to its constitution, courts and armed informed citizens. That's why I'm putting all my eggs in that basket.
If you don't think it's important or needed, well, there is still a lot for you to learn.
US per capita spending on healthcare: $13,473 per person
China per capita spending on healthcare: ~$763 per person
Both have average life expectancy of 79 years. LITERALLY China has better healthcare, better housing, literally better in all the ways that count.
What does our "democracy" get us exactly???
No midterm routs in China.
For Europe, the answer is using homegrown metal, even if it is severely underpowered, and accepting that it will be running American and Chinese open-source models for the near future. (The French lobbyists looked likely to turn Mistral into another Arianespace, but they’ll be resisting implosion for at least another year.)
A single court ruling overturning an order from Xi will shut me up immediately.
> In four years, you don't have to vote again. We'll have it fixed so good, you're not going to have to vote.
At least the Chinese president isn't a pedophile enriching himself at the expense of the Chinese people. China has steadily increased the quality of life for its people where the quality of life for the average American has steadily decreased.
I'm not saying this is good, I'm merely stating that the central committee power and Xi's power is still limited by the sheer size of the Chinese state. If you compare that dictatorship to the Stalin dictatorship or Gheddafi dictatorship you'll find that Xi does not have that kind of unfettered power through sheer violence, he still needs to make a high number of cogs to work in unison to exercise it.
I think there is also a perhaps the need to assign air-quotes to "investors" when talking about the US markets.
There's too much fluff and noise there. Too much (over)leveraged trading. Too much speculation.
What the real investors think is hidden behind the actions of the speculative traders.
> I think they do not believe that big corporations in the US or Europe would actually use chinese models
The Chinese models are open-weight. You can download them and run them on your own servers. Or you can outsource to Mistral, Privatemode or any of the many other US/EU inference hosters.
So the "security, regulatory and/or business continuity concerns" arguments are effectively non-existent. And whatever argument does possibly remain, also applies equally to Anthropic, OpenAI & co.
https://www.pewresearch.org/global/2026/07/15/people-in-many...
You're entire company would become ineligible for gov contracts if you have use DeepSeek. Something like that.
Correct. And they're likely very correct in the belief.
When people on the internet claim that frontier labs are done for because Chinese open-weight models exist, they really don't appreciate that the people spending the money do not want to hear "we can just run it cheaper ourselves!" Any software engineer with even a few years of experience knows that phrase is absurd, and executives are simply not interested in the risks associated with such an endeavour when they can just buy the solution outright.
Consumers will have access to open-weight models just like how consumers have access to Linux. But you can just go look at the market share of operating systems to see why something being free and openly available doesn't matter to executives who just wants to get things done and is willing to pay a premium to a trusted business to do the work for them.
And none of that even touches the fact that these frontier labs have only ever been in-front of open-weight alternatives. Again, if you're an executive, and you're questioning if you should pay a premium for a better version of a tool which you presume is important for your company's ability to compete, then the answer is immediately obvious: pay the premium or risk falling behind competition who is willing to pay the premium. And when you're talking about global companies who can pay these bills without it being significant enough to even show up on a quarterly financial statement, then it's an obvious sell.
That's why most of the internet runs on Windows IIS rather than Linux or BSD. That's why everyone here is running a VM on their Mac that hosts Windows containers to do development in.
I think you're missing two things here.
1. The margin by which a hosted product is operationally superior to self hosting an open source alternative is precisely calibrated. The SaaS provider has no reason to invest beyond the point were they can reliably make the sale.
2. Self hosted open source solutions come with a big bonus re: the ability to read and modify their code. But realistically ain't nobody got time for that.
AI upsets the apple cart in both cases. It's now far easier to manage locally hosted open source solutions, which means that in order to maintain the favorable effort ratio for making a sale, products must all get significantly better than their open source alternatives. That's gonna be a slow process involving innovative product owners. AI is getting better faster than it can happen.
Also, since AI is trained on the open source code, it's very good at integrating open source components. Previously nobody was bothering to gain that kind of mastery over their tools but now you can leverage it right out of the gate--but only if you're using projects that are in your assistant's training data. Maintaining a moat around a software product has always been orthogonal to making your product useful, but as we lean on AI more, it'll get worse. The more you protect your IP, the more its usability degrades. This was always true, but now it doubly true.
Executives may want to pay for a solution to their problems. But the companies that might provide those solutions no longer have a sustainable path.
The future of software is as a tool, not as a product or a service.
It's generally understood that for better or for worse, if you're working on anything (not just IT) that is security-sensitive, you're going to have restrictions on what can and cannot be done that may seem absurd at first, but hold up to scrutiny once more thoroughly examined. I would say that you don't even need to thoroughly examine this particular restriction. I have prod data at work that I can't give to humans outside of the United States. Not in India, not in the UK, not even in Canada. Clients insist on these clauses in contracts. This has been a known practice across many fields in this industry for decades.
Now we're suddenly seeing a chorus of posts saying that we should loosen up and send data to a non-human intelligence that was developed by a known geopolitical rival with a history of malicious intrusion on Western networks. Where does that come from?
The piece I think we're missing is that, currently, AI is for software development. It theoretically has other uses, but nobody has found much of a way to capitalize on them. For the time being, most of the money being made is in models and harnesses for software development. There's already precedent here to use more open/cheaper solutions.
Not to mention, if you make data security guarantees or have specific contracts, you can't even use US providers anyway.
So, they choose to believe, lacking a better strategy. They will also try to lobby their belief into existence.
The labs pushing this cyber scare is an attempt to cry wolf. The corps don’t give a fuck
My mind is at: Even though it's overvalued, it will likely keep climbing and won't crash.
Where is the market at?
Then...it's not overvalued?
Unless you mean "it will crash relative to inflation over 20 years, but not over 5 years" or something like that.
The classic dotcom example is pets.com. Would you liken Anthropic to pets.com?
if these hold a year after an IPO then we can talk.
Rather than caring about whether it's over for western providers, I look at what competitors for the western providers have been doing since their first moment in the spotlight. And what I see is that their offerings keep getting better and better, and that at the same time they're opening not just their weights but their architecture and experience.
As a customer (rather than a pundit), I just like their tools and the user experience more than I do those of hte US giants. I admire the US offerings in many respects, but also find the user experience has a lot of friction and annoyances. Deepseek et al don't always deliver the same immediate 'wow factor' but when I sit down to build something, I enjoy using their tools. After 40 years of using computers for fun and profit, I will always always bet on a product that's fun to use.
It is clear from the beginning that the Chinese Open Model are a proxy for economic warfare. Anyway their singular goal is to dethrone US monopoly on SOTA model and burn all the economic hype and investments. If this strat works, which we will see after Anthropic/OAI IPO, we'll be in for an interesting ride
I mean, what would you expect? Like USA isn't openly planning to weaponize their current AI primacy [1, 2].
[1] https://www.whitehouse.gov/presidential-actions/2025/07/prom...
[2] https://www.whitehouse.gov/wp-content/uploads/2025/07/Americ...
Way too many monopolies these days
https://public-inspection.federalregister.gov/2026-21447.pdf
ahahahah
ahahahah
The DHS order only bans buying DeepSeek products directly (e.g. doing inference on their China hosted servers). It does not apply to open weights at all. And DeepSeek just gave their response to the DHS order.
Now, most software products developed with DS can pass an audit, whether human or from a US AI provider, that they do what they say and aren't secretly funneling telemetry to Beijing. When I say 'most..can pass an audit' I mean that most products are simple enough to undergo such an audit, rather than implying that some have exfiltration mines buried within; it's possible but I have have no reason to think it's probable. I believe the purpose of the broad wording is to facilitate the waiver requirement, which costs money to apply for and will require payment to an accredited or government approved audit provider, thus generating DSP on the US balance sheet even if the original prototyping/buildout was done with Deepseek.
"third-party products and services developed using DeepSeek implementations".
So gov can't use western inference of DeepSeek either.
I hope more hedge funds start doing that. Basicaly funding open development to profit from tanking uptight super serious American stocks, to fund even more open development.
If you can't beat them, give the common folk means to skip them and profit from their fall.
Drop a few mil on tokens to make enterprise grade database to put out for free and bet against Oracle. Or train a model, or something.
Moat-like things going for them:
- access to the US government (for huge inflated government contracts as a source of free capital, having the competition banned, having their products legally mandated, getting other preferential treatment, having foreign governments bullied into granting similar advantages)
Too unsustainable, too fragile, too small:
- Strong brands: Brand loyalty seems like a pretty insignificant factor in AI right now
- Semi-exclusive hardware access, RAM buyouts: Unsustainable even in the short term
- Lock-in effects: Their models aren't very stable across versions, or very unique, and switching providers is about as easy as it can be in a highly competitive market.
- Exclusive technology that is important, advanced and hard to replicate to a degree that would materially set them apart and justify potentially much higher cost. Maybe I'm missing something here, but a lot of the claims they make to that end fall apart even on light scrutiny (due to things like test sets that are small, hand-picked and clearly overfitted on, or broad general claims that cannot be substantiated). I'm getting the feeling they don't have anything that materially sets them apart at all, but that's seems impossible to measure in any meaningful way, so who knows, they might have something here.
I can click a button in Azure foundry and run open weight models that are approved through my compliance and procurement teams.
I don’t know how open sourcing this stuff helps deepseek but it means I’m getting ever better and cheaper models so I’m fine with it.
I'm not sure whether the DeepSeek's open-sourced inference engine does all of these, but it appears that plenty of inference tricks have just been revealed for the open source community to learn from and start improving upon.
But the key point is that something good enough always attracts more interest and contributions because a productive outcome is very realistic and tangible.
Open Weight models and competing open source inferences engines massively undermine monopolies; in theory at least.
See how cloud is easy to divest and “nationalise”.
And I imagine this engine is by default mostly just deepseek compatible and inference engines are not universally applicable to all models?
It sounds significant for competition but I'm not sure how it sinks Anthropic/openAI. Presumably they still have their frontier models, the training data they're vacuuming from current users and access to hardware to serve at a ridiculous scale, right?
In that scenario, even if global Token usage increases 100-fold in the future, that alone would not be enough to justify these foundation model companies being worth one or two trillion dollars.
Deepseek manages to be ridiculously cheap and efficient with prompt caching, i spent 550M~ (1.9b input cache miss, 1.7b output) tokens and it cost me 5~ bucks, that would be ~150 bucks on Opus 5.5, if i ran that workload in parallel that would be $50 vs $1500, e.i. i wouldn't want to subagent heavily with anthropic models.
now imagine Kimi K4 or GLM 5.5 with those cost savings
If SpaceX was reset to 2016, they would still be ahead of everyone else even today. Their deployed capabilities today are ahead of the plans of most of their competitors.
Anyway, where's the revenue from space going to come from? Obviously not data centres now that Deepseek is commoditising inference.
The telecom business? Amazon is catching up there and Europe/the rest of the world is racing to build capabilities to not be dependent on Musk.
They may be catching up, but not anytime soon.
but perhaps you are thinking that starlink is the key? sure probably a bigger market - but any market it accesses is bound to eventually prefer ground lines.
so the only way to justify the valuation is if the AI side of the business becomes the most dominant AI business
Global space launch market is 6.5B in 2026. Even the total global satellite market is only 23B in 2026.
You have to assume some pretty large numbers for YoY growth, market share, and profit margin to get to 2T valuation.
I don't understand the reference to Kamikaze in this context. Is Deepseek destroying itself in order to deep-six US frontier labs?
The term is used generically in modern warfare for an attacking vehicle which is itself destroyed when attacking a target; for example, a kamikaze drone. [0]
US companies are throwing money at the problem, and considering how good Opus 5.5 is I’m not too concerned about them.
Meanwhile OpenAI has grown their revenue like 10x and Anthropic has grown theirs like 65x in that same time period.
There's no cap on what you can do with frontier intelligence, nor how much of it you can use. Yes, DS and other open weight models will continue to grow like crazy (as long as they can source compute), but so will the frontier labs. I ran like 20 agents overnight last night on Opus, Fable, Sol, and Astra last night, trying to use up quota before my weekly reset, and I'd gladly have done 10x that much and used agents 10x more intelligent if I could have. And in six months I probably will.
The moat is custom inference hardware, lower power, higher throughput, etc.
The overall market will still be big, very big, if it replaces real people or augments every single worker.
Some contracts will go to your local provider (US Gov, etc.).
And there is still a moat between them and DeepSeek.
As long as i can afford it, i use Opus.
I'm not bound by it and switching is very fast
They'll need to release cheaper, better models to compete. Which may not be possible.
All other models are also either by <1k labs or side hustles by tech companies who are not particularly known for LLMs
People will take the novel bits here and port them to the above. The community as a whole will benefit. Including infrastructure engineers inside OpenAI and Anthropic.
But a lot of what's in here is already in published papers out of DeepSeek already.
https://polymarket.com/event/anthropics-valuation-end-of-oct...
These have not really budged (yet) on this news.
It's possible to be correct that the AI companies have no future, but not be able to time the exact month they collapse.
If by 'collapse' you really mean a 50%+ fall, timing is not going to make or break you by any means.
If Anthropic is going to crash 50% or more at some unknown time in the next two years, and you have foreknowledge of this, you can easily make a massive profit by placing a bet weekly. The odds are VERY long per week, so on each losing bet you only lose a tiny amount, but on your winning week you will more than make up for it.
Timing is, as a general rule, important. In the particular case we're discussing, the odds of a 50% swing are so low that you can tolerate being VERY wrong on the timing if you are correct on the swing.
idk, if "prediction markets" remain a real thing, there should probably be some requirement for previous experience in options-adjacent markets to ensure people actually understand the economics of time-valued positions.
Deepseek started as Liang's side project funded with his hedgefund couch change compute. That set the economics for everyone else in PRC. If deepseek releases for free because Liang doesn't give a shit about making $$$ on his hobby, every other PRC player has to follow. And serendipitously, due to US export controls, PRC tech companies can't dig themselves into ruinous seppuku debt buying compute even if they wanted to - what they can buy, i.e. everything around DC infra including power, they get for fraction of the cost expediently.
TLDR Liang said fuck profits... which means every other PRC competitor had to fuck profits, which ends up fucking profits of western labs so deep in debt due to rampant financialization and can not afford to say fuck profits.
Sometimes a billionaire is fine just burning $$$ on a hobby while remaining a billionaire instead of trillionaire, and it just so happens the side effect might mean preventing others from being trillionaires as well. Bonus others is geopolitical adversary who is hedging economy on trillion $$$ returns.
Seems kind of pointless? Wouldn't anyone in the US/western world simply use the chinese models in their own inference? That would not strengthen the Chinese position because the models got downloaded for free off HuggingFace, and then cloud inference bills would just put money into US companies.
According to Greek economist and former finance minister Yanis Varoufakis, an open source AI strategy is one way a capitalist economy can avoid the rent trap (platforms being created, monopolizing resources, and extracting ever higher rents from everyone else).
https://www.yanisvaroufakis.eu/2026/08/31/ai-is-reviving-chi...
One person's hobby started the industry in PRC and set the trend and inspired talent in nascent field with no established business model. PRC competitors didn't want to FOMO and just knew they had to compete with opensource and everyone fast followed. They bought what limited compute they could, hired what talent they could and just told them get to work. There's a reason even Chinese Uber / DiDi was releasing open source models. There wasn't some grand coordinated posture to compromise US markets, it's incidental to PRC industry being PRC industry. Very few in PRC thought they could close gap this fast with compute deficit. US chose to continuously dump venture $$$ and company warchests quarter after quarter on their own to increase exposure. There's no grand conspiracy to turn US into communist state (wut), there is not "bet", just typical PRC domestic involution business shenanigans clashing with US financialized VC shenanigans. In alternate world if PRC models not competitive, open source wouldn't even matter to US valuations. In alternate world if PRC models competitive and US AI isn't leveraged to shit to multiple % of gpd, i.e. systemic contagion risk, it also wouldn't matter.
It doesn't matter if US/west makes $ off PRC models, PRC doesn't have enough indigenous compute let alone spare to meaningfully compete globally. In so much it matters economically (again happy happenstance for PRC) is denying US AI making $$$$$ while spending $$$$ vs US AI making $ while spending $$$$. Extra happy happenstance that $$$$ US spending on is basically all the VC money and FAANG warchest stockpiled by US tech over decades... i.e. US spent so much that it meaningfully constrains private money to spend more in future. Meanwhile PRC AI spending $ to make $ (or less), but still have $$$ in reserve for other shit. It also doesn't help that half of business model depends on building infra on tight schedule that US is... not great at.
I'm out of my league on knowing if these ChatGPT projections are close, a little off, or way off, but we currently pay about $5k per month for Claude for our whole team. The projection for "run Deepseek on AWS to replace Claude" is coming in at $30k+ for GPU hours.
Well deserved too! The chutzpah of trying to peddle the AI equivalent to knives which refuse to cut flesh because it might be human flesh... astounding, and utterly disrespectful to their customers. Claude's guardrailing was so bad during OpenAI's HF attack that HF had to go to Beijing!!
I'm hoping Anthropic and OpenAI drop like stones on IPO. Never thought that liberation in this space would come from the Chinese!