Measured by the DCI the Chinese AI models are about 1.5 years ahead of US models.
DCI = Dust42 Capability Index: MBP Max 64GB, Qwen3-80B MLX 4bit quant, 40 tokens per second. It is not on Claude Opus level but very, very useful if you have no internet, i.e. on a flight. And occasionally it surpasses even Opus by far and large. Opus is a pain in the neck once the coding task at hand surpasses its capabilities. Qwen3 is much better to guide to get step by step to a solution.
Almost all Chinese models are open weight research models.
My theory is that these models serve the purpose of being relatively easy to run/tweak for researchers, and mainly serve to demonstrate the effectiveness of new techniques in training and inference, as well as the strength of AI labs that created them.
They are not designed to be state of the art commercial models.
By choosing bigger model sizes, running more training epochs, and drilling the models a bit more on benchmarking questions, I'm sure the Chinese could close the gap, but that would delay these models, make them more expensive and harder to run without showing any tangible research benefit.
Also my 2c: I was perfectly happy with Sonnet 3.7 as of a year ago, if the Chinese have a model really as good as that (not only one that benchmarks as well), I'd definitely like to try it.
Minimax has been great for super high speed web/js/ts related work. It compares in my experience to Claude Sonnet, and at times gets stuff similar to Opus.
Design wise it produces some of the most beautiful AI generated page I've seen.
GLM-4.7 like a mix of Sonnet 4.5 and GPT-5 (the first version not the later ones). It has deep deep knowledge, but it's often just not as good in execution.
They're very cheap to try out, so you should see how your mileage varies.
Ofcourse for the hardest possible tasks that GPT 5.2 only approaches, they're not up to scratch. And for the hard-ish tasks in C++ for example that Opus 4.5 tackles Minimax feels closer, but just doesn't "grok" the problem space good enough.
No, for example Alibaba has huge proprietary Qwen models, like Qwen 3 Max. You just never hear about them because that space in western LLM discussions is occupied with the US labs.
Well, my answer was partially tongue in cheek. However, under the circumstances I mentioned I had better results with a local model. But then up to today I really like Deepseek for dev - for me and my use cases it still outperforms Opus. The problem is we don't have good and universal benchmarks, inststead we have benchmaxxing. For my use cases Chinese models may be perfect but maybe for yours American one's may outperform them by a huge margin? So I urge you to use YCI - Your Capability Index.
They have been catching up pretty fast though. Since US have banned Nvidia chips export upto a certain extent to them they are coming up with more optimized training at least which is why US should be wary of them. China does more with less
This story has so many repeats by now it should be taught in schools. Constraints breed improvements, time and again. Whether in the petri dish or in a tech domain, if you want to see greatness substitute the latest and greatest for something that is two generations older and watch the miracle unfold.
What doesn't kill you really does make you stronger.
The US and China regularly use export controls (like the Nvidia ban), joint ventures, and legislation as levers of power over the other side.
For American and other non-PRC companies thinking of using Chinese models, doesn't this have to be balanced with the risk that the US or its leadership may kneecap the Chinese models through export controls, an executive order, or some other means?
Perhaps they're catching up because there's a massive problem with AI growth that is finally taking shape. Perhaps this is the end of the growth curve and the beginning of a flatline.
I suppose this is a more forward looking post though. It's about whoever gets to whatever is awaiting us in the future 7 months before the other.
And I guess the idea is is that there is this extreme inflection point in utility somewhere that makes it so getting there first gives you some incredible economic edge.
It might not exist though. Like either utility plateaus and its bubble crash of the century time or it just keeps going up but without any specific point where you can differentiate something.
The GP is talking about recursive self-improvement.
What yes, it's clear by now it's way beyond the capacity of those AIs, and the odds are pretty good it's impossible to a large extent (but some limited version of it may be possible).
I wish this was emphasized more. I'm American & rooting for America etc etc. but it's so fun to read high quality papers about more or less state of the art techniques and research. I get why the American labs don't publish but I really enjoy reading the Chinese papers.
We "distilled" modern cars from Model-T. You still driving the car that was "first" off an assembly line?
This is normal improvement to manufacture of stuff. Your handwavy "it was first so its winner-winner chicken dinner!" is little more than your personal form of expression.
Since LLMs are a distill of web content, by your poorly defined metric, you must not value LLMs and AI companies? The content already existed! They're just a new indexing tool.
Rhetorical goals about intention do not remake physics which comes with well understood constraints. Doctors intended to use bloodletting to cure illness and killed people instead. Words are not magical spells.
The machines these models run on are well known. They’re not black boxes. The results will be same-y despite the timeline, process, companies took to get there being different.
UPS trucks may carry different sizes and shapes of packages day to day but their upper bounds on total weight and geometry exist too.
A Honda and Ford can look different, but physical reality, whether the measure is user feedback (human biology exists is physical) or physics itself, still results in very same-y 4 wheels, etc etc.
What's strange to me is all the software engineers who ignore physics. All of our applied knowledge that gives rise to software engineering also constrains the outcomes. Our ability to sit down every day and arbitrarily slice up data in various ways is very much constrained by physics like everything else.
The easy money/endless hype era of ZIRP where SWEs failed up thanks to endless employment opportunities has resulted in way too many SWEs believing their efforts on some trivial shit like a JS framework, or some CSS designs is propelling humans into the future.
Nah, it's just physics as usual. You alls sensory memory is just parroting the crap it memorized.
> In any case, they wouldn't exist if not for superior models they were distilled from.
Doesn't matter: if they're good enough and cheaper, they'll sink the US model-makers eventually. The free market demands it.
The US invented solar panels, and led in solar panel tech for a long time. Who leads in solar panel tech now?
China has a playbook for de-industrializing its capitalist rivals. If we leave MBAs and free-marketers in power, China will "come to dominate all technologies, including A.I., and ... America [will] export little more than soybeans and corn" (https://www.nytimes.com/2025/12/17/opinion/trump-ai-chips-nv...).
The rate at which the deconstruction of the United States is progressing is very scary. It seems as if they want to make the former USSR look great, and every individual and institution that could do something about it is standing by with their hands in the air saying 'it wasn't me'. Tech dominance will be the least of the problem, that assumes a large variety of good outcomes where bad outcomes are now a real possibility.
> The rate at which the deconstruction of the United States is progressing is very scary. It seems as if they want to make the former USSR look great, and every individual and institution that could do something about it is standing by with their hands in the air saying 'it wasn't me'.
This kinda sounds like you're talking about Trump, but I think the problem predates him and is far deeper. If anything, Trump is a spastic reaction to the deeper problem. He won because his rhetoric gestured in the direction of fixing the problem, but he's too incompetent to pull it off (and the bulk of the competent people don't want to fix the problem for ideological reasons).
Definitely not just talking about Trump. The failure is institutional, the whole thing is just incredible watching from the outside in, you've never had a more 'clear and present danger' to the USA and to the world order and all of the institutions that are supposed to protect against that are failing one after the other.
This is how you go from stability to world wars. A couple of rich guys got together and decided they were going to redraw all of the maps and toss the rulebook overboard, and it is for the most part going their way. People are being executed and the useful idiots are falling over each other to defend it.
If you had told me in 1999 that this would happen by 2026 I would have happily declared you mad, but here we are.
> A couple of rich guys got together and decided they were going to redraw all of the maps and toss the rulebook overboard, and it is for the most part going their way. People are being executed and the useful idiots are falling over each other to defend it.
It's way deeper than that, though. It's stuff like US businessmen choosing to literally move the US's rare-earth magnet production capacity to China, teaching China how make them in the process (https://www.nytimes.com/2025/12/31/business/china-rare-earth...). It's the US knowing about it's rare-earth vulnerability for a decade or more but being completely unable to do anything about it. It's the US losing other strategic capabilities like large-scale electronics manufacturing capacity, and people being totally fine with that because "cheaper iPhones, more margins, good deal!"
This short term thinking over long term thinking goes back a long time and is happening in other places as well.
But the singular focus on destruction of what is a cornerstone of the stability of the Western hemisphere is absolutely unprecedented. And to see so many people falling for it, hook line and sinker. They are so blasted with crazy things that they no longer see anything strange at all about each and every day's happenings and they even jump to defend the absolutely indefensible, something that probably would have been - rightly - horrified by less than a decade ago is now perfectly normal.
> This short term thinking over long term thinking goes back a long time and is happening in other places as well.
> But the singular focus on destruction of what is a cornerstone of the stability of the Western hemisphere is absolutely unprecedented. And to see so many people falling for it, hook line and sinker.
IMHO, that short-term thinking over such a long span laid the groundwork for that destruction.
I read this the other day, and I think it's an interesting take that rings true:
> Instead of comparing what is happening under Trump with the situations in Hungary, Turkey and Russia, Goldstone argued that conditions in the United States are,
>> ironically, more like what happened in Venezuela, where after a century of reasonably prosperous democratic government, decades of elite self-serving neglect of popular welfare led to the election of Hugo Chávez with a mandate to get rid of the old elites and create a populist dictatorship.
>> I find that decades-long trends in the U.S. — stagnating wages for non-college-educated males, sharply declining social mobility, fierce political polarization among the elites and a government sinking deeper and deeper into debt — are earmarks of countries heading into revolutionary upheaval.
>> Just as the French monarchy, despite being the richest and archetypal monarchy, collapsed in the late 18th century because of popular immiseration, elite conflicts and state debts, so the U.S. today, despite being the richest and archetypal democratic republic, is seeing its institutions come under attack today for a similar set of conditions.
Once China's economy reaches a certain point, will not the same thing happen to them? I'm not sure who will be the next source of cheap/slave labor and lack of concern about negative externalities, maybe Africa?
> Once China's economy reaches a certain point, will not the same thing happen to them?
No, because it's not a problem of economic development, but political ideology.
China's political priority is technological dominance and capability, and it views free markets as a tool subordinate to those goals. The US's political priority is financial wealth, and an extreme ideological attachment to free markets that overrides most other priorities. The US has an ideological vulnerability that China is well-positioned to exploit.
This problem goes well beyond Trump, and has roots that are very deep.
Political priorities can change. As more and more Chinese become middle class or wealthy, they might view things differently from when they just hoped they had enough food for the week.
> Political priorities can change. As more and more Chinese become middle class or wealthy, they might view things differently from when they just hoped they had enough food for the week.
Lest you forget: China is controlled by the CCP and is not a democracy. It will not affect political priorities if "more Chinese become middle class or wealthy" and "view things differently." The Chinese political system does not answer to them, and will only throw them a bone if there's a major threat to stability.
You're echoing the 90s-era hope that free markets would bring political liberalization to China, but history has debunked that idea.
> Many would have said the same thing about the USSR.
What do you mean, exactly?
China isn't the USSR: they're not wedded to central planning. They've figured out how to use capitalism while keeping it squarely under their control. Arguably, they're playing the "capitalism" game more successfully than "capitalist" countries like the US.
When you compare the US to China, it's the US that looks sclerotic, like the USSR once did.
Once of America's big weaknesses is a common lazy assumption we'll always be at the top, so we don't respond to challenges until its too late. Then we tell ourselves some reassuring story and comfort ourselves by gazing at one of the few remaining industries where we're still ahead. I'm pretty sure if the US and China got into a conflict, the US would get its ass kicked like the Nazis and Japanese did during WWII, and for similar reasons.
I'm not saying it's the same situation, but few people in the 1970s would have imagined it possible that the USSR, a superpower nation, would have a complete political collapse and cease to exist within the next 20 years.
Yeah, but it's more likely the US will collapse like the USSR than it is for China to collapse. The big reason the USSR collapsed was its economic output couldn't keep up, and it couldn't afford the competition anymore.
China's mostly caught up technologically to the US. It's ahead or pulling ahead in many areas. It's production capacity is way ahead. Without Chinese production propping up the US, US stores would probably feel a lot like late-Soviet stores, with bare shelves and not enough products to satisfy demand.
> Without Chinese production, we'd simply still be producing stuff here.
No, the US can't anymore. The supply chains have moved to China now, and needed capital equipment and know-how has mostly been lost in the US. It would take a massive investment to get back to "simply ... producing stuff here."
And if anyone tries, the chorus of "muh iPhone expensive!" would be deafening, the politicians would retreat and go back to bickering about the culture war and plotting their next attack ad, and the businessmen would go back to counting their money.
7 months on average and decreasing. As the rate of progress in models slows down the head start of any entity in the field will slowly reduce until there is parity.
Question about English for natives: "[...] have lagged behind [..]" would be the grammatically correct version of the heading, I think. Or is "to lag" without "behind" actually a correct use? Is it merely headline-speak, news-speak, to make headlines shorter and convey more information in fewer words?
In my western US dialect, it is abnormal to use it as a subject-verb-object (SVO) construct. I have to guess at intent.
For me, there are three idiomatic forms:
1. Using "lag behind" gives a target/reference as a prepositional relationship, not as an object of the verb "to lag".
2. Using "caused to lag" allows one to specify a causal agent, but again not as an object of the verb "to lag".
3. Using "lag" alone is a subject-verb construct, leaving an implicit target/reference from context expectations. A coach or supervisor might scold someone for lagging.
As a bit of a tangent, I actually wonder if the etymology of "to lag" is more Germanic than some people assume. The verb lagern has many uses for placing, storing, and leaving behind. It's where our English concept of a "lager" beer comes from too, referencing the way the beer is fermented in (cold) storage. If this linguistic connection remained fresh, we might think of an SVO construct of lagging as the opposite of the intent in this article. The leader would lag the follower by leaving them behind!
Lag as a verb does imply following behind, but it can also be a noun, such as in "a time lag".
Adding behind after lag as a verb is more of a "because it sounds good", perhaps as a subconscious way to emphasize the verb, but it isn't a grammatical requirement at all.
Leaving it off is almost certainly more to keep the headline short than anything else.
Both versions are grammatically correct. "Lagged behind" is common for everyday speech, while using "lagged" as a direct verb is a standard, formal way to describe data gaps in business or news. So yes, the headline uses just "lagged" to save space.
I'm not a native, but lived in the US for a quarter century. I think you're correct that that "lagged behind" is the correct version, but if you replaced "lagged" with "trailed" it would also be correct without the "behind". Language is very fluid and always evolving, so using "lagged" as one would previously have used "trailed" may soon be considered correct usage.
Note also that these aren't really questions of grammar (syntax) but meaning (semantics). Does "lagged" mean the same thing as "trailed" in this kind of construction? It didn't some decades ago, but maybe it does today. Or will tomorrow.
"Lagged" alone is valid, but it is slightly less clear. Because, while it would be atypical, "X lagged Y" could be read to mean that X caused Y to lag. "X lagged behind Y" removes that ambiguity.
They just lack of performant hardware. They have enough knowledge. And so they choose a more effective strategy without wasting resources on training from scratch.
You can do a rough distill through the APIs. You don't need the weights.
It was much easier when companies had models on the /completion style APIs, because you could actually get the logits for each generation step, and use that as a dataset to fit your model to.
That isn't to diminish the efforts of the Chinese developers though, they are great.
so there has been quite a few instances of extensions logging AI chatbot conversations, I wonder if this is related to them training on that data given the accusations of deepseek 'stealing' chatgpt.
So basically the amount of time it takes for them to scrape existing US models and then train on that data. China doesnt have any intellectual property, they are just stealing
But companies like OpenAI collected a lot of data about the artificial intelligence through platforms such as OpenAI GYM, and people voluntarily contributed and published their code/models there because they believed that this was not a commercial organization and would act for the benefit of all mankind.
China produced foundational technologies (paper, compass, printing, gunpowder etc) long before the US existed, the US later built on global inventions too. Same here, LLM progress is cumulative and international, today's leaders won't be tomorrow's by default.
All frontier US models are closed weight. It's great what Chinese are doing because open weights help everyone. Also there is a lot of research thanks to these open weights, look how much research is being done using Qwen models in US (Microsoft etc) and in the rest of the world.
Multi-head Latent Attention (MLA) + DeepSeekMoE? plus an auxiliary loss free load balancing strategy and multi token prediction objective to train/infer huge MoE models efficiently.
Have you seen Manifold Constrained Hyper Connections (mHC) paper from a few days ago from Deepseek? Projects residual connection space onto a constrained manifold to keep identity mapping properties while enabling richer internal connectivity, so basically it eliminates a huge problem.
They also released A LOT of training tricks and innovation around optimizing inference and training.
As to other industries:
"China leads research in 90% of crucial technologies — a dramatic shift this century" [1]
And here's[2] "China Is Rapidly Becoming a Leading Innovator in Advanced Industries", a big report on where they lead and how.
They use the ECI - EpochAI Capability Index.
Measured by the DCI the Chinese AI models are about 1.5 years ahead of US models.
DCI = Dust42 Capability Index: MBP Max 64GB, Qwen3-80B MLX 4bit quant, 40 tokens per second. It is not on Claude Opus level but very, very useful if you have no internet, i.e. on a flight. And occasionally it surpasses even Opus by far and large. Opus is a pain in the neck once the coding task at hand surpasses its capabilities. Qwen3 is much better to guide to get step by step to a solution.
Interesting, does it mean they're optimizing for cases where China is disconnected from the internet completely?
Almost all Chinese models are open weight research models.
My theory is that these models serve the purpose of being relatively easy to run/tweak for researchers, and mainly serve to demonstrate the effectiveness of new techniques in training and inference, as well as the strength of AI labs that created them.
They are not designed to be state of the art commercial models.
By choosing bigger model sizes, running more training epochs, and drilling the models a bit more on benchmarking questions, I'm sure the Chinese could close the gap, but that would delay these models, make them more expensive and harder to run without showing any tangible research benefit.
Also my 2c: I was perfectly happy with Sonnet 3.7 as of a year ago, if the Chinese have a model really as good as that (not only one that benchmarks as well), I'd definitely like to try it.
It is arguable that the new Minimax M2.1 and GLM4.7 are drastically above Sonnet 3.7 in capabilities.
Could you share some impressions of using them? How do they feel like compared to OAI models or Claude?
Minimax has been great for super high speed web/js/ts related work. It compares in my experience to Claude Sonnet, and at times gets stuff similar to Opus. Design wise it produces some of the most beautiful AI generated page I've seen.
GLM-4.7 like a mix of Sonnet 4.5 and GPT-5 (the first version not the later ones). It has deep deep knowledge, but it's often just not as good in execution.
They're very cheap to try out, so you should see how your mileage varies.
Ofcourse for the hardest possible tasks that GPT 5.2 only approaches, they're not up to scratch. And for the hard-ish tasks in C++ for example that Opus 4.5 tackles Minimax feels closer, but just doesn't "grok" the problem space good enough.
No, for example Alibaba has huge proprietary Qwen models, like Qwen 3 Max. You just never hear about them because that space in western LLM discussions is occupied with the US labs.
No, there are datacenters in China they can still use if their internet is down.
Well, my answer was partially tongue in cheek. However, under the circumstances I mentioned I had better results with a local model. But then up to today I really like Deepseek for dev - for me and my use cases it still outperforms Opus. The problem is we don't have good and universal benchmarks, inststead we have benchmaxxing. For my use cases Chinese models may be perfect but maybe for yours American one's may outperform them by a huge margin? So I urge you to use YCI - Your Capability Index.
Let's see who disconnected from the internet completely :)
They have been catching up pretty fast though. Since US have banned Nvidia chips export upto a certain extent to them they are coming up with more optimized training at least which is why US should be wary of them. China does more with less
This story has so many repeats by now it should be taught in schools. Constraints breed improvements, time and again. Whether in the petri dish or in a tech domain, if you want to see greatness substitute the latest and greatest for something that is two generations older and watch the miracle unfold.
What doesn't kill you really does make you stronger.
The US and China regularly use export controls (like the Nvidia ban), joint ventures, and legislation as levers of power over the other side.
For American and other non-PRC companies thinking of using Chinese models, doesn't this have to be balanced with the risk that the US or its leadership may kneecap the Chinese models through export controls, an executive order, or some other means?
Perhaps they're catching up because there's a massive problem with AI growth that is finally taking shape. Perhaps this is the end of the growth curve and the beginning of a flatline.
Definitely. And there’s lots of wasteful training practices in Singapore too.
How much less? Their companies clearly have access to the latest GPUs.
This video can bring some perspective https://www.youtube.com/watch?v=CrJJPlRO9bI around 5:11
They use H800 as opposed to major US ones on H100 (2-3x faster)
State of the art 7 months ago is good enough for a lot of use cases.
That was my thought. At my work, 7 months can be less time than it takes to get a project organized around a high-level plan. It sounds like nothing.
I suppose this is a more forward looking post though. It's about whoever gets to whatever is awaiting us in the future 7 months before the other.
And I guess the idea is is that there is this extreme inflection point in utility somewhere that makes it so getting there first gives you some incredible economic edge.
It might not exist though. Like either utility plateaus and its bubble crash of the century time or it just keeps going up but without any specific point where you can differentiate something.
Feels like that inflection point possibility passed a while ago since these models are starting to plateau in performance.
The GP is talking about recursive self-improvement.
What yes, it's clear by now it's way beyond the capacity of those AIs, and the odds are pretty good it's impossible to a large extent (but some limited version of it may be possible).
What makes you think they plateaued?
Exactly - for an average person's task, how different is AI today vs 7 months ago?
On the flagships, maybe. But on open models (and especially the small ones), China is kicking ass.
Aren't they just distills.
Deepseek, Qwen and Moonshot have contributed with lots cool and interesting papers.
I wish this was emphasized more. I'm American & rooting for America etc etc. but it's so fun to read high quality papers about more or less state of the art techniques and research. I get why the American labs don't publish but I really enjoy reading the Chinese papers.
Does it matter what they are if they outperform?
Do they outperform? In any case, they wouldn't exist if not for superior models they were distilled from.
First does not always equal superior.
We "distilled" modern cars from Model-T. You still driving the car that was "first" off an assembly line?
This is normal improvement to manufacture of stuff. Your handwavy "it was first so its winner-winner chicken dinner!" is little more than your personal form of expression.
Since LLMs are a distill of web content, by your poorly defined metric, you must not value LLMs and AI companies? The content already existed! They're just a new indexing tool.
Must be strange to work hard in a competitive environment and have all customers pretend your product is always exactly the same.
Each wizard school also seems to take a different approach and have different goals. Soon people will benchmark lawyers with Lego.
Rhetorical goals about intention do not remake physics which comes with well understood constraints. Doctors intended to use bloodletting to cure illness and killed people instead. Words are not magical spells.
The machines these models run on are well known. They’re not black boxes. The results will be same-y despite the timeline, process, companies took to get there being different.
UPS trucks may carry different sizes and shapes of packages day to day but their upper bounds on total weight and geometry exist too.
A Honda and Ford can look different, but physical reality, whether the measure is user feedback (human biology exists is physical) or physics itself, still results in very same-y 4 wheels, etc etc.
What's strange to me is all the software engineers who ignore physics. All of our applied knowledge that gives rise to software engineering also constrains the outcomes. Our ability to sit down every day and arbitrarily slice up data in various ways is very much constrained by physics like everything else.
The easy money/endless hype era of ZIRP where SWEs failed up thanks to endless employment opportunities has resulted in way too many SWEs believing their efforts on some trivial shit like a JS framework, or some CSS designs is propelling humans into the future.
Nah, it's just physics as usual. You alls sensory memory is just parroting the crap it memorized.
> Do they outperform?
For the size/performance yes.
> In any case, they wouldn't exist if not for superior models they were distilled from.
So? Those models wouldn't exist without the sum total of human knowledge. As long as a work is transformative why does it matter?
> In any case, they wouldn't exist if not for superior models they were distilled from.
Doesn't matter: if they're good enough and cheaper, they'll sink the US model-makers eventually. The free market demands it.
The US invented solar panels, and led in solar panel tech for a long time. Who leads in solar panel tech now?
China has a playbook for de-industrializing its capitalist rivals. If we leave MBAs and free-marketers in power, China will "come to dominate all technologies, including A.I., and ... America [will] export little more than soybeans and corn" (https://www.nytimes.com/2025/12/17/opinion/trump-ai-chips-nv...).
The rate at which the deconstruction of the United States is progressing is very scary. It seems as if they want to make the former USSR look great, and every individual and institution that could do something about it is standing by with their hands in the air saying 'it wasn't me'. Tech dominance will be the least of the problem, that assumes a large variety of good outcomes where bad outcomes are now a real possibility.
> The rate at which the deconstruction of the United States is progressing is very scary. It seems as if they want to make the former USSR look great, and every individual and institution that could do something about it is standing by with their hands in the air saying 'it wasn't me'.
This kinda sounds like you're talking about Trump, but I think the problem predates him and is far deeper. If anything, Trump is a spastic reaction to the deeper problem. He won because his rhetoric gestured in the direction of fixing the problem, but he's too incompetent to pull it off (and the bulk of the competent people don't want to fix the problem for ideological reasons).
Definitely not just talking about Trump. The failure is institutional, the whole thing is just incredible watching from the outside in, you've never had a more 'clear and present danger' to the USA and to the world order and all of the institutions that are supposed to protect against that are failing one after the other.
This is how you go from stability to world wars. A couple of rich guys got together and decided they were going to redraw all of the maps and toss the rulebook overboard, and it is for the most part going their way. People are being executed and the useful idiots are falling over each other to defend it.
If you had told me in 1999 that this would happen by 2026 I would have happily declared you mad, but here we are.
> A couple of rich guys got together and decided they were going to redraw all of the maps and toss the rulebook overboard, and it is for the most part going their way. People are being executed and the useful idiots are falling over each other to defend it.
It's way deeper than that, though. It's stuff like US businessmen choosing to literally move the US's rare-earth magnet production capacity to China, teaching China how make them in the process (https://www.nytimes.com/2025/12/31/business/china-rare-earth...). It's the US knowing about it's rare-earth vulnerability for a decade or more but being completely unable to do anything about it. It's the US losing other strategic capabilities like large-scale electronics manufacturing capacity, and people being totally fine with that because "cheaper iPhones, more margins, good deal!"
This short term thinking over long term thinking goes back a long time and is happening in other places as well.
But the singular focus on destruction of what is a cornerstone of the stability of the Western hemisphere is absolutely unprecedented. And to see so many people falling for it, hook line and sinker. They are so blasted with crazy things that they no longer see anything strange at all about each and every day's happenings and they even jump to defend the absolutely indefensible, something that probably would have been - rightly - horrified by less than a decade ago is now perfectly normal.
> This short term thinking over long term thinking goes back a long time and is happening in other places as well.
> But the singular focus on destruction of what is a cornerstone of the stability of the Western hemisphere is absolutely unprecedented. And to see so many people falling for it, hook line and sinker.
IMHO, that short-term thinking over such a long span laid the groundwork for that destruction.
I read this the other day, and I think it's an interesting take that rings true:
https://www.nytimes.com/2026/01/06/opinion/trump-presidentia...:
> Instead of comparing what is happening under Trump with the situations in Hungary, Turkey and Russia, Goldstone argued that conditions in the United States are,
>> ironically, more like what happened in Venezuela, where after a century of reasonably prosperous democratic government, decades of elite self-serving neglect of popular welfare led to the election of Hugo Chávez with a mandate to get rid of the old elites and create a populist dictatorship.
>> I find that decades-long trends in the U.S. — stagnating wages for non-college-educated males, sharply declining social mobility, fierce political polarization among the elites and a government sinking deeper and deeper into debt — are earmarks of countries heading into revolutionary upheaval.
>> Just as the French monarchy, despite being the richest and archetypal monarchy, collapsed in the late 18th century because of popular immiseration, elite conflicts and state debts, so the U.S. today, despite being the richest and archetypal democratic republic, is seeing its institutions come under attack today for a similar set of conditions.
Thank you, that is very enlightening, I had not made that link.
Once China's economy reaches a certain point, will not the same thing happen to them? I'm not sure who will be the next source of cheap/slave labor and lack of concern about negative externalities, maybe Africa?
> Once China's economy reaches a certain point, will not the same thing happen to them?
No, because it's not a problem of economic development, but political ideology.
China's political priority is technological dominance and capability, and it views free markets as a tool subordinate to those goals. The US's political priority is financial wealth, and an extreme ideological attachment to free markets that overrides most other priorities. The US has an ideological vulnerability that China is well-positioned to exploit.
This problem goes well beyond Trump, and has roots that are very deep.
Political priorities can change. As more and more Chinese become middle class or wealthy, they might view things differently from when they just hoped they had enough food for the week.
> Political priorities can change. As more and more Chinese become middle class or wealthy, they might view things differently from when they just hoped they had enough food for the week.
Lest you forget: China is controlled by the CCP and is not a democracy. It will not affect political priorities if "more Chinese become middle class or wealthy" and "view things differently." The Chinese political system does not answer to them, and will only throw them a bone if there's a major threat to stability.
You're echoing the 90s-era hope that free markets would bring political liberalization to China, but history has debunked that idea.
Many would have said the same thing about the USSR.
> Many would have said the same thing about the USSR.
What do you mean, exactly?
China isn't the USSR: they're not wedded to central planning. They've figured out how to use capitalism while keeping it squarely under their control. Arguably, they're playing the "capitalism" game more successfully than "capitalist" countries like the US.
When you compare the US to China, it's the US that looks sclerotic, like the USSR once did.
Once of America's big weaknesses is a common lazy assumption we'll always be at the top, so we don't respond to challenges until its too late. Then we tell ourselves some reassuring story and comfort ourselves by gazing at one of the few remaining industries where we're still ahead. I'm pretty sure if the US and China got into a conflict, the US would get its ass kicked like the Nazis and Japanese did during WWII, and for similar reasons.
I'm not saying it's the same situation, but few people in the 1970s would have imagined it possible that the USSR, a superpower nation, would have a complete political collapse and cease to exist within the next 20 years.
Things can change.
> Things can change.
Yeah, but it's more likely the US will collapse like the USSR than it is for China to collapse. The big reason the USSR collapsed was its economic output couldn't keep up, and it couldn't afford the competition anymore.
China's mostly caught up technologically to the US. It's ahead or pulling ahead in many areas. It's production capacity is way ahead. Without Chinese production propping up the US, US stores would probably feel a lot like late-Soviet stores, with bare shelves and not enough products to satisfy demand.
> it's more likely the US will collapse like the USSR than it is for China to collapse
Certainly not ruling that out.
> Without Chinese production propping up the US, US stores would probably feel a lot like late-Soviet stores
I don't agree here. Without Chinese production, we'd simply still be producing stuff here.
> Without Chinese production, we'd simply still be producing stuff here.
No, the US can't anymore. The supply chains have moved to China now, and needed capital equipment and know-how has mostly been lost in the US. It would take a massive investment to get back to "simply ... producing stuff here."
And if anyone tries, the chorus of "muh iPhone expensive!" would be deafening, the politicians would retreat and go back to bickering about the culture war and plotting their next attack ad, and the businessmen would go back to counting their money.
yes and its weird for people to claim otherwise
Nice. So ~ half a year and we get open-weights Opus 4.5 capability? I'm all for that!
Imagine the size of those weights.
Someone else who's not a big, american vampire corp feeding on VC money can worry about that for me...
7 months on average and decreasing. As the rate of progress in models slows down the head start of any entity in the field will slowly reduce until there is parity.
I could not find GLM on there, it is one of the best open weight Chinese models now, probably not at the top but seems only a few months behind.
Can't wait for GLM-5, it's currently being trained
Question about English for natives: "[...] have lagged behind [..]" would be the grammatically correct version of the heading, I think. Or is "to lag" without "behind" actually a correct use? Is it merely headline-speak, news-speak, to make headlines shorter and convey more information in fewer words?
In my western US dialect, it is abnormal to use it as a subject-verb-object (SVO) construct. I have to guess at intent.
For me, there are three idiomatic forms:
1. Using "lag behind" gives a target/reference as a prepositional relationship, not as an object of the verb "to lag".
2. Using "caused to lag" allows one to specify a causal agent, but again not as an object of the verb "to lag".
3. Using "lag" alone is a subject-verb construct, leaving an implicit target/reference from context expectations. A coach or supervisor might scold someone for lagging.
As a bit of a tangent, I actually wonder if the etymology of "to lag" is more Germanic than some people assume. The verb lagern has many uses for placing, storing, and leaving behind. It's where our English concept of a "lager" beer comes from too, referencing the way the beer is fermented in (cold) storage. If this linguistic connection remained fresh, we might think of an SVO construct of lagging as the opposite of the intent in this article. The leader would lag the follower by leaving them behind!
Lag as a verb does imply following behind, but it can also be a noun, such as in "a time lag".
Adding behind after lag as a verb is more of a "because it sounds good", perhaps as a subconscious way to emphasize the verb, but it isn't a grammatical requirement at all.
Leaving it off is almost certainly more to keep the headline short than anything else.
Both versions are grammatically correct. "Lagged behind" is common for everyday speech, while using "lagged" as a direct verb is a standard, formal way to describe data gaps in business or news. So yes, the headline uses just "lagged" to save space.
I'm not a native, but lived in the US for a quarter century. I think you're correct that that "lagged behind" is the correct version, but if you replaced "lagged" with "trailed" it would also be correct without the "behind". Language is very fluid and always evolving, so using "lagged" as one would previously have used "trailed" may soon be considered correct usage.
Note also that these aren't really questions of grammar (syntax) but meaning (semantics). Does "lagged" mean the same thing as "trailed" in this kind of construction? It didn't some decades ago, but maybe it does today. Or will tomorrow.
"Lagged" alone is valid, but it is slightly less clear. Because, while it would be atypical, "X lagged Y" could be read to mean that X caused Y to lag. "X lagged behind Y" removes that ambiguity.
It is correct, if somewhat uncommon in daily use. I published an article awhile ago and the editor revised it similarly.
lag is a verb meaning "to fail to keep up" so IMO, lagging behind is redundant. It is not uncommon to hear, but strictly unnecessary.
that's because they are distilling the frontier models
Frontier models aren't released, they are closed source.
And the Chinese have been a huge source of innovation in the field.
distilling does not require the models to be released. They simply use the apis.
They have been a source of innovation but probably not in training them.
They just lack of performant hardware. They have enough knowledge. And so they choose a more effective strategy without wasting resources on training from scratch.
You can do a rough distill through the APIs. You don't need the weights.
It was much easier when companies had models on the /completion style APIs, because you could actually get the logits for each generation step, and use that as a dataset to fit your model to.
That isn't to diminish the efforts of the Chinese developers though, they are great.
is there any evidence that this is significant contribution?
My intuition that one need ALOT api credits to distill such large models.
And how much have they spent compared to US companies? What of carbon footprint?
China generates twice as much clean energy compared to US, in raw gigawatt-hours: https://www.reuters.com/markets/commodities/chinas-power-gri...
Looks like they are not far off on fossil fuels as well. And at around 5x the population.
so there has been quite a few instances of extensions logging AI chatbot conversations, I wonder if this is related to them training on that data given the accusations of deepseek 'stealing' chatgpt.
So basically the amount of time it takes for them to scrape existing US models and then train on that data. China doesnt have any intellectual property, they are just stealing
none of the American AI companies have IP either. They just scrape and steal everything too. They just started earlier.
usa companies invented these models
Not disputing that. But the vast amounts of data and information they were trained on that makes them useful was all stolen.
It's thieves all the way down.
no its not
it is
But companies like OpenAI collected a lot of data about the artificial intelligence through platforms such as OpenAI GYM, and people voluntarily contributed and published their code/models there because they believed that this was not a commercial organization and would act for the benefit of all mankind.
China produced foundational technologies (paper, compass, printing, gunpowder etc) long before the US existed, the US later built on global inventions too. Same here, LLM progress is cumulative and international, today's leaders won't be tomorrow's by default.
All frontier US models are closed weight. It's great what Chinese are doing because open weights help everyone. Also there is a lot of research thanks to these open weights, look how much research is being done using Qwen models in US (Microsoft etc) and in the rest of the world.
china has produced very little real innovation
Multi-head Latent Attention (MLA) + DeepSeekMoE? plus an auxiliary loss free load balancing strategy and multi token prediction objective to train/infer huge MoE models efficiently.
Have you seen Manifold Constrained Hyper Connections (mHC) paper from a few days ago from Deepseek? Projects residual connection space onto a constrained manifold to keep identity mapping properties while enabling richer internal connectivity, so basically it eliminates a huge problem.
They also released A LOT of training tricks and innovation around optimizing inference and training.
As to other industries:
"China leads research in 90% of crucial technologies — a dramatic shift this century" [1]
And here's[2] "China Is Rapidly Becoming a Leading Innovator in Advanced Industries", a big report on where they lead and how.
1. https://www.nature.com/articles/d41586-025-04048-7
2. https://itif.org/publications/2024/09/16/china-is-rapidly-be...