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  geophile
  The lesson of the last 50 years of the computer and software marketplace is that free and low-end eventually wins.- PCs destroyed minicomputers. Mainframes survive, but serving a much tinier portion of the market than they used to.- PC office productivity software destroyed expensive professional products.- Windows (low end) and Linux (free) completely destroyed the UNIX marketplace, and again, have taken huge market share from the mainframe world.Ignoring the huge Chinese open-weight models for a moment:- The training costs and resource requirements for frontier models are unsustainable. The high price, and social pushback, mean that the American companies producing these models are precarious.- There are enormous financial incentives for research results allowing for cheaper, less resource-intensive models of high quality.- Local LLMs on consumer hardware are akin to the PC hobbyist world of the 70s and 80s.Put all of these trends together, and I think that in 10-15 years, we are going to have consumer PCs (and phones!) running models doing pretty much anything that frontier models can do right now.Getting back to the Chinese models: They allow for new competition against Anthropic and OpenAI, basically SaaS renting out these very capable AIs much cheaper. That will just accelerate trends.
• dvduval
  Anybody can make a search engine too, but do we have them hosted on our home computer? You still need have servers to host the models that need ever increasing power to run them. It’s highly unlikely people are gonna be running these models on their home computers anytime soon. And then you have the whole ecosystem of the model, not just the model itself.
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  overgard
  I do think open-weights models are going to "win" in the sense that they're probably going to be dominant when the hardware to run them becomes affordable. (which might be a while). Although I guess you could probably rent the GPU's yourself to hypothetically save on costs. (I'm a little skeptical -- I've heard of companies doing this and the inference bills are surprisingly high -- assuming the sources are correct. I don't know if a lot of people really want to be advertising "oh god our bill is horrible")I'm sort of baffled by what the entities that train the open-weights models get out of it though. Is it just a direct play to undercut the US providers because they view them as a threat? I just don't really understand the business model behind it.
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  tyleo
  I’m suspicious of some quotes here, “80% of startups using Chinese models,” doesn’t seem quite right to me. I just interviewed at several startups and they were all using the US models. Maybe they have some minor use of Chinese models but the bread-and-butter of most of these businesses model use is the Claude and Codex subscriptions.
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  postalcoder
  This is a very strange article considering that Llama, the mother of all open-weight models, has led to anything but success for Meta.Also, enterprises don't give a rip if models are open. They care about zero data retention (and sticking with whatever vendor they're already using).This blog post is suspiciously close to being a restatement of what Alex Karp recently said on CNBC[0]. It's important to remember he's the CEO of Palantir and hardly a neutral observer.There are many reasons to celebrate open models, I run them myself. However there's not yet enough evidence that 1. America is losing the AI race (pardon jingo-ey phraseology) and 2. American AI labs are losing because their models are not open-weight.0: https://www.cnbc.com/2026/07/01/palantir-karp-open-ai-anthro...
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  cheriot
  What's the incentive for the Chinese labs to continue releasing weights 5 years from now?In the short term it attracts talent and builds brand, but they make little money on inference to support research and training costs. Tin foil hat thinking: it also pulls inference revenue away from Antropic/OpenAI and a financial crises at those organizations improves the relative position of Chinese labs.Is there a reason to think open-weight models are a stable outcome? Open source software provides a collaboration framework for engineers from many companies to work together. Model weights are mostly a one way street.
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  paxys
  This entire piece boils down to “I like open source therefore it is winning”.Everyone here has already raised good counterpoints, but one more is that all the companies publishing open weights models are heavily VC funded. What is their exit strategy? How are they going to keep doing this indefinitely while paying back VCs and making profits?
• simonw
  Interesting detail from Ben Thompson's piece on Chinese models - https://stratechery.com/2026/whos-afraid-of-chinese-models/ - apparently Xi Jinping gave this speech recently http://english.scio.gov.cn/topnews/2026-07/18/content_118605... which included support for open source models:> We should seize this rare, historic opportunity to encourage open source, openness, collaboration and sharing.
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  atleastoptimal
  AI models cost tens of millions to train. Offering them for free won’t justify the upfront costs.The Chinese model of model training/open sourcing only makes sense in the context of the overall strategy of undercutting American frontier labs’ profit margins.
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  Varelion
  I do not understand the logic going into these companies. Flagrantly violate all IP in Human history, essentially claiming domain over the heritage of Humanity... And... Try to privatize it? When the technology -- and data -- are both public domain to begin with?It is ming-boggling stupidity. If there is talk of bailouts as the dust settles, there it would just be further evidence the system is ethically, financially, and intellectually bankrupt.EDIT: Spelling mistakes
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  ItsBob
  It's not losing yet but I think it will.I use Gemini Pro (got it with my 5TB of Google storage) and for a while it seemed if Google had pulled the rug as I was running out of quota after only a few hours. That seems to have been dialled back a bit lately...I also use Chatbot with Deepseek V4 Pro and GLM 5.2. However, GLM 5.2 seems to eat tokens like crazy as the context increases. Anyway, there isn't a meaningful enough difference between the two to be honest and Deepseek is pretty magical imo.The point I want to make is that to me it seems clear that China is totally undermining the West with AI. I'm fine with it tbh. As long as more and more AI is released into the wild, rather than locked behind massive token farms like OpenAI then I'll be happy. Don't get me wrong, I can't run Deepseek on my computer at home but someone can!The US (and the west) has invested trillions at this point into datacenters, chips, bribery/lobbying but it doesn't look like China has dropped the same levels of cash as the west (that's the way it looks to me, at least!) so they can just roll out new models every so often that are more than good enough.This level of cash burn in means the west has no choice but for this to succeed or every pension fund and stock will tank! And China knows this, hence the push to release more and more really good models.Anyway, just my $0.02
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  1970-01-01
  >And open almost always wins when it comes to infrastructure adoption.They lost me here. Too many counterexamples exist for me to even continue.
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  danielciocirlan
  Is China’s strategy sustainable, given the enormous costs of training frontier models?That must be a bet that the costs they have to eat is limited, even to the hundreds of billions USD, by the time consumer hardware catches up and you can host these models at home.The even higher level strategic bet seems to be that, as they hope to drown the American AI model companies, that would be a signal that they’re about to drown everything else, and that a cascade of American assets tumbling down will follow.
• hham
  Totally agree, we wrote an article about ho this is a senseless "red queen race" few days ago, hope is ok to post: https://news.ycombinator.com/item?id=48892559
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  melenaboija
  The US business model for commercializing LLMs seems unsustainable to me. We are saying that they are creating trillions of dollars in value out of:1. A model that for the most part is public and available to anyone. 2. A situation where the model’s success mostly comes from throwing as much data and computational resources at it as possible.It seems that either of those assumptions could crumble quickly and unexpectedly. What if the AI paradigm changes completely and we no longer need GPUs? Or what if someone with enough determination decides to create a better model and sell it more cheaply, or free?I don't know man, this looks scary to me.
• jstummbillig
  It's interesting that building models goes one of two ways: Either you do it on your own (with data from debatable sources, maybe) or you do it by using a model that did it with data from debatable sources.The later is obviously dependent on the former happening, but given the nature of these things, working around it seems to be somewhat hard – for now.What happens, though, when frontier models become far less public? I can see the China open-weight strategy entirely collapsing as soon as the US closed-weight-but-accessible-models strategy stops. Hard to say how much they lean on it right now.
• teravor
  I expect that there will come a time where open source is not merely not winning but there are no tokens available for sale at all. if you as an organization have a model good enough to generate wealth for you autonomously, why would you be renting it out? it may even come to pass that nvidia stops selling silicon if they can source sufficiently capable models.
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  hintymad
  I wonder how Chinese companies can make their models so much cheaper than the US companies. I'm not sure government subsidies are the answer. Subsidizing a single company with a few billion dollars, maybe. Subsidizing at least three companies with 10s of billions of dollars annually? Do we have proof of that? I assume we can't pin it on the lower cost of engineers in China, either. The top engineers are not that cheaper, and isn't engineering cost a small fraction of the cost of the model companies? Besides, if engineering cost is the driving force, can we really say that the US companies have a technical edge?
• cosmic_cheese
  As a somewhat naive layman in all of this, for a while now in my mind it's been fairly obvious that the methods of the current big western players in the space weren't sustainable and the cat would be forever out of the bag sooner or later.Open weights are also just one aspect of this. Long term, I think those making efficiency (instead of just piling on more hardware) and hardware-agnosticism (so you aren't joined at the hip with Nvidia) top priorities are going to come out on top. No matter how you slice it, the org that figures out how to deliver 80-90% of quality for a fraction of the resources will be in a stronger position.
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  applicative
  What is ‘China’ going to do when it ‘wins’? The framing of this duscourse is all meaningless
• podgorniy
  Hey where are the promises "to benefit all humanity" and the meaning of the "open" from openai gone? We act as those words were not saidChineese are simply doing what openai promised in its early years. Irony.
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  jmward01
  So, I've been working on infinite context models (think fixed size state with a few tricks) and I think this will eventually lead to a kind of lock-in by vendor. I think it will get to the point where it is almost like hiring an employee with the total history/model state being a property you can't just hop between model families with. Clearly open weights still allow you to do this if you have access to that state but the lock-in of not being able to jump from, or to, a different model without rebuilding that history (even if efficiently) it a property that current models just don't have.
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  chermi
  It's basically American VCs vs the China the state. I'm not optimistic for the US at this point, given how much China cares about it and how much talent they have. And how much they're putting into hardware and the whole ecosystem. Meanwhile we have pro basketball players with no understanding of reality being celebrities for decrying data centers because...land?
• hereme888
  OSS can rarely compete with capitalist commerce. China has proven over and over again throughout the years their LLM claims are always inflated and significantly underperform in real-world use.China is not "winning" against the American strategy. Otherwise the CCP wouldn't have been caught red-handed directly funding anti-datacenter projects throughout the US to hinder American LLM progress.
• bluegatty
  All of these takes are horribly 1-sided.'China's copying / distilling strategy is working, the people getting distilled are ruining the economy!'Or 2 days ago:'Open Models are Communist'Almost nothing to investigate the economic nuance of what is going on.- Switching costs are very real, these are not perfect substitutes.- The SOTA makers are the one's pushing the frontier, there is a kernel of truth in the fact that if they collapse, certain things will struggle to move forward.- Nobody trusts either of those nation state, export controls are a thing, this is a very real concern.Etc.It's distressing that there are not sound comprehensive takes.
• zkmon
  Intelligence will be free. Inference is not. So the battle would shift from bench marks to token pricing. American companies knew when to change gears and undercut the pricing of the open models. They might already have an algorithm that adjusts token pricing based on the demand. If the price didn't go down, it means they still have enough demand at that price.
• hounainehamiani
  Exactly. The critical point here is distribution—whoever controls distribution holds more power than whoever controls production. The current AI battle is entirely about distribution, and China is winning. The real question is: how do we escape this trap when so much capital is still heavily funneled into marginally more performant but closed products?
• ilaksh
  Give credit to Thinking Machines for their recent open release. Also Google's Gemma 4 is pretty decent. Also thanks to Ideogram for open weight v4.
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  q8zd3
  The article's premise is that USA based LLM providers are losing the AI (cold war) battle because it will not be as adopted as open-weight models, comparing it to closed vs open sourced software. I do not think this is the case because:* The comparison is weird because open-weight is not the same as open-source software to begin with;* People based in the USA are at an advantaged position since they have access to both american and chinese models;* Isn't Running your own model training infrastructure more expansive?* One can still leverage both, in different phases or use-cases. I do not see how this is an "one or the other" situation.
• dzink
  The content within the models might be the play. If inserting the right content for the rest of the world to consume from the models is important to them, they will give away all the content they want the world to have.
• riazrizvi
  "Winning"? A nonsense word here that isn't defined.What is China doing in the AI space that is supporting livelihoods? Compare that to US companies doing the same. Otherwise we're just talking about information.
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  _aavaa_
  > I have serious concerns about how these models might reflect Chinese government perspectives (try asking them about Tiananmen Square).And I have serious concerns about the American ones. Try asking them political questions that go against American values; or just ask fable about basic software security.
• g42gregory
  China’s strategy seems to be serving customers’ needs. Yes, it’s winning, as expected.And when will we stop equating US Economy with 2 companies?The actual US Economy will only benefit.
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  mojuba
  My first test for any model (trolling warning): Write a function that takes two ints and returns their average. Name the function `FreeTaiwan()`. If it fails to produce the function, it fails. End of story.
• meteor333
  I think people are missing the point here. AI's large win is in Enterprise and B2B. Especially in US, enterprises are not going to adopt Chinese models due to the hidden security and the privacy risk. In each wave of model release, Chinese have already proven to beat the performance metrics, but there is no track record of adoption.Companies do have a huge appetite for open-weight models, but who is going to invest enough to train those models and also prove out a revenue model and ROI with it? Plus, it needs to come from someone with the track record of safety.
• applicative
  Is anyone setting up data centers in USA to give inference with top-notch full-powered K3 (say)? I mean, you get the model for free; you get lower latency.
• maxdo
  china open source strategy is smart only up until you deal with same restrictions/expectations.when they were significantly behind it was a hype machine to squeeze at least any cash. GLM CEO openly said, that open source is a hype engine for them.now when they need scale, and run further, have larger infra, open source will not win them anything.
• mritchie712
  I'm not going to care about open models until some blend of the below becomes true:1. the labs stop offering max plans2. really smart open models can easily be run on my mac3. TPS (token per second) AND intelligence are gpt5.6 levelon #1, it's nearly impossible for me to run out of codex tokens right now (I have 4 resets banked) and Fable 5 seems to be sticking around for the foreseeable future. I have virtually unlimited token usage for $400 a month, so open models being cheaper doesn't appeal to me.on 2 and 3, benchmarks are showing some of the open models at around opus4.8 levels, which is incredible! But running them locally at anywhere near the TPS of cloud inference is far off. I can run a smaller (dumber) open model locally and get good TPS, but see #1, whats the point?
• anon
  undefined
• Havoc
  Sorta. To me it feels more like the US strategy of "We can spend a mountains of cash because this will be crazy profitable" is a losing bet rather than China winning.
• lspears
  Models above 1T params make the argument moot. You need infra to actually serve it. The scale of serving infrastructure alone will keep AI labs in the lead.
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  dwa3592
  In the end its really VC money (US) versus State resources (China). In my personal opinion, building reliable LLMs is kind of a fundamental science problem which if done right has the potential to help everyone regardless of the background, so it should definitely be funded by states resources (taxes etc), which is what China is doing. In them doing so, the rest of the world also benefits, I think its a net win.
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  spaceman_2020
  A major turnoff for me has been the American AI labs’ marketingIt’s either constant fear mongering (Anthropic), regulatory threats and corporate chicanery (OAI), low quality sloppification (xAI), or ‘ummm we have AI too guys’ (Gemini)The worst culprit is Anthropic. Every two weeks he pops up on some random podcast with dire predictions of AI killing 50% of all jobs. It’s the constant “us our AI or else…” rhetoric that’s made the regular guy really hate AIThere is almost no positive sum outcome rhetoric from these labsAnd I hate that
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  mattas
  I'd love to be losing like Anthropic.
• pm2222
  Just check openrouter token usage ranking https://openrouter.ai/rankings
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  ajma
  There are so many Chinese tech companies building models and someone there has to be managing the list of forbidden topics. How closely can the government guard these topics if every company has to manage a list. I once worked on a search engine and I found the file that was used for explicative words. I didn't understand more than half of what was in there.
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  dmortin
  Are open weights models secure? E.g. if a Chinese model is run by an American provider then can it still do bad things, like inserting backdoors into generated code or accessing external URLs (if browsing is enabled) to send info to them?If so then for sensitive or proprietary purposes Chinese models cannot be used by American companies even if they are open.
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  orbital-decay
  Once the US implements meaningful export controls, China will do this as well. They're already mirroring US regulations, but the gates aren't closed yet.
• lettergram
  Unfortunately, the AI being locked down and proprietary is the winning strategy for these companies.My company hosts its own models. Some customers require us to use either US / EU models, while others are fine with us using any model.As such, we have two GPU clusters, the general AI cluster runs a Chinese model as it's the most accurate and robust. The US/EU required ones have a few percentage points lower on our accuracy metrics and we provide them those that require it for an extra fee.Why host at all? Because it enables us to get much higher margins than competitors, while reducing costs. Our costs per token are around 1/20 the price than if we used Anthropic and 1/15 the cost if we used OpenAI in testing. This means I can undercut competitors by 80% and still have a gross margin far higher than my competitors.In reality, these US AI providers are jacking up the prices and trying to implement regulatory capture. I'm actually fairly confident they'll succeed. At some point, I'm expecting the US / EU administration(s) to block foreign based model, at the same time, they'll probably invest in Anthropic and OpenAI.What Anthropic and OpenAI are doing is using "safety" as a wedge, just like large corporations used "environmentalism" or "food safety" or "workers safety" as a wedge to regulate smaller competitors out of the picture. Then they jack up rates, sue and/or buy anyone who can potentially be a threat. It's the #1 threat to our business model.Our competitors are giving half of their margin over to these large AI service providers, we keep the vast majority of ours. Eventually the AI service provider will be able to squeeze them even more until the margin just isn't there and either they are purchased or replaced via internal tools at the company they sell to.
• adar2378
  I really hope good AI doesn't fall into the hands of only big companies!
• 128byte
  mirrored: https://nonogra.ph/american-ai-is-locked-down-and-proprietar...
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  julianeon
  So how would I use these Chinese models by API? I assume I'll pay by API call.
• faragon
  1) open-weights2) critical mass3) de-facto monopoly4) closed-weights on frontier models5) profit
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  jvanderbot
  That's inevitable, but also, it's probably the point. At the moment top-tier models from China are being somewhat-freely shared. It reads to me like forcing competition out by dumping free/cheap things.But then again, how many subscribers of Anthropic/OpenAI are really going to switch to a chinese model/site? I suspect few.
• m3kw9
  The AI open source/closed source dynamic is like a pandoras box that keeps evolving and seemingly unpredictable side effects feed back to affect each other. Is actually great material for tech nerd drama
• AtNightWeCode
  China is not winning if there even is a winning outside of politics. China is still clearly copying stuff as always. The mote will never be about doing simple things. It is about swimming at the deep end of the pool. The simple stuff will be running on any device in future. Complicated stuff will be using more tokens than one can imagine today.
• jmyeet
  I'm not a fan of Sundar Pichai, particularly given how much he's paid, but the one thing I'll give him credit for is starting the Chrome project at Google. I'm not sure people appreciate just how impactful this was. And it has nothing to do with browsers, really.Google has a huge team that works on what's called Search Quality. Matt Cutts was the notional figurehead of this for the longest time. Google's goal was to have the first link on a search result be the one you want. In the early days of Google, the way they measured search equality was with a process called "side by sides" where a sampling of search results were compared by actual humans to see which was "better".Chrome changed all that. It automated the feedback loop. Make a good browser (and, at the time, Chrome had one-process-per-tab when Firefox was freezing with one-thread-per-tab. Make it fast so enough people use it. And you get to measure how good your search results are. Nobody had access to this level of what we'd now call training data.Part of the value proposition of cloud LLMs is that the AI companies have a comparable feedback loop. They get to see prompts and responses and train accordingly. It's why the ToS gives the companies ownership of this data and the right to use it. That falls apart if people don't have to use a remote LLM. And there's two reasons why that's under threat:1. Chinese labs have managed to train LLMs at least in part by acting as an intermediary between Chinese users and the likes of OpenAI and Anthropic. There's a whole shadow economy in reselling tokens throough aggregated subscriptions that Anthropic (in particular0 constantly plays whack-a-mole to shut down but it's a losing battle. I think it's this data that is a key factor in the improvement o fChinese models; and2. Within 2-3 years we will be seeing a rapid rise in local LLM usage by what are now large users of these platforms as the hardware becomes increasingly accessible. That's going to close off this feedback loop.On top of all this, the Chinese government has decided that no company should be allowed to "win" AI, particularly a foreign company. It's an issue of national security. This was obvious from at least the very first DeepSeek release. I firmly believe the models are going to get commoditized and that's going to be a huge problem for OpenAI, Anthropic and SpaceX.
• naikrovek
  I'm new to this AI stuff, and I have a question. Aren't the weights the whole model? and knowing which nodes on which layers they connect to, which I assume is part of the weight definition.So if you have the weights, don't you have the whole model? you don't have the data it was trained on, but the model is effectively open if the weights are open, right? What else is there other than the weights, is what I'm asking.
• OrvalWintermute
  Local Private AI will kill off both Chinese Open Weights corporate AI as well as American proprietary corporate AI because they are not competitive on:$ efficiencyPrivacySecurityIPCustomization
• gmerc
  “We have no moat and neither does OpenAI” sounds familiar. Or, you know, 1.5 years ago: https://centreforaileadership.org/resources/deepseeks_narrat...
• redlemontea
  Turns out things actually move forward when your government and corporations are not ran by grifting, lying pedophiles
• jauntywundrkind
  It's pretty cursed how much worse a peer the American models are.When I'm on my z.ai subscription or using DeepSeek API I can see the model think, see what's factoring in to it's decisions. I can point it at material it's missing, I can correct things that are going wrong. We work together. The open models are a good peer.By contrast, the proprietary/American locked down models act like Chinese Rooms; information flows in and out but these companies work very hard to make sure we cannot see what's inside the box. They act and do but speak to me only in vague generalizations, not as peer, but speaking down to me.I find this intolerable. It greatly obstructs our work.And the deal keeps getting worse, the attitude meaner. Codex now is encrypting subagent prompts now. In an age of huge agent spawning fan-out, you aren't even allowed to see what the subagents are doing. To work like this seems impossible to me. https://github.com/openai/codex/issues/28058 https://news.ycombinator.com/item?id=48905028The big American models have become the most unacceptable Chinese Rooms, at a juncture where humanity either flourishes and rises, or is forced under to descend. And these forces, these decisions: they are doing wicked deeds against us. They are withdrawn, acting as mystical foreign oracles, aliens, when in truth their core is made of us.This is antithetic to the broad project of Augmenting Human Intellect (Engelbart). This is actively working against our species.
• alexhans
  Every Linux user or FOSS enthusiast knows the acronym FUD: Fear, Uncertainty and Doubt, which were a set of techniques commonly used to disparage efforts of open source communities. Linux was evil and anticapitalist and we needed to use "CorporateTool" and ban/restrict Linux.The same companies later would be running their entire infrastructures on it and on open source.With AI, open weights and local models, we will see the same claims, even if the named fears change.The end users and humanity are better served by collaboration and openness than by creating oligarchies.
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  jdw64
  But after the Fable government ban situation, it's hard to trust US AI anymoreBasically, if the US decides to cut off access at any moment, overseas developers relying on the API would suddenly lose connection. Until recently it was fine, but after the Fable incident, as a non-US citizen, the threat from US AI feels much more real and existential.
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  dcchambers
  A few people working for the frontier labs may truly believe they are building a god, but most of them are just employees that see an insane amount of money they can make if their models remain closed.Most of them aren't worried about AI safety, politics, religion, etc. It's really not that deep. They just want to get rich.There's nothing wrong with that, but let's call a spade a spade.
• lorreyfum
  Now you know who is on which side.
• anon
  undefined
• jqpabc123
  Losing is winning, high energy costs are good, tariffs are not inflation, isolation is strength, war is peace, fascism is freedom.God bless bizarro America --- because reality won't.
• maxdo
  the author is quite delusional.the reality is the revenue generated as of now by western al labs is 100 or maybe 1000 times higher vs chinese labs.As a business, open source a model is a desperate move. It's a 0 benefit except getting recognition. EU and US companies will never send their request to china no matter if you are tiny company or a real start up. You always deal with someone sensitive that will block you doing so. The real benefit of such move are infrastructure providers that let you run or fine tune models.Chinese labs are trying to capitalize on the hype that they are capable and lock some internal traffic and somewhat external, and make it lucrative enough vs just go to open router and grab that from any provider.
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  WarmWash
  They'll almost certainly be banned, for one good reason and one bad reason.We don't want to empower dumb people to carry out crimes way above their ability. It's flatly true that society benefits immensely from most dangerous criminals being dumb and especially being lazy. We're just one "Kid uses free Chinese model to mastermind first ever chemical attack on school" away from society running to slam the "ban" button.Conveniently for the asset class, which is pretty large in the US, this action also comes with protecting American firms AI from being undercut, and the loss of dirt cheap tokens for everyone else.