There is no secret sauce the US labs have that the Chinese ones don't, or won't have soon enough. Deepseek 4 and Kimi 2.5 are not quite Claude 4.5/GPT5.5 but there's no fundamental principle missing - they are strong evidence that there's no real advantage the "frontier" labs possess that isn't related to scale, which they will gain in time (if they even need to). The RL post-training techniques that work are widely known and easily copied. All Deepseek is really lacking is data, which they're getting - and the harder Anthropic/the USG makes it to access claude in china, the more of that precious data they'll get!
I used to sort of entertain the "fast take-off breakaway" scenario as being plausible but not really anymore. The only genuine moat the frontier labs have is their product take-up, which isn't nothing, far from it, but it's not some unbreakable technological wall. Too late guys - it might have been too late for quite some time.
However, they just don't perform that well in practice. That's the real issue. You can actually see it when you move away from open benchmarks. Deep seek 3.2 is 4% on Arc-AGI 2 [1], while GPT 5.2 high is 52% and GPT 5.5 pro high is 84.6%. That's the real reason why nobody is using these models for serious work. It's incredibly frustrating.
In addition, I already feel the pain myself on the model restriction. I'll asking my codex 5.5 agent to crawl a website - BOOM, cybersecurity warning on my account. I'll ask it to fix SSH on my local network - another warning. I'm worried about the day my account would be randomly banned and I cannot create a new one. OpenAI already asks you to perform full identification in order to eliminate these warnings - probably exactly for that - so that if they ban you, it's permanent.
The Chinese models right now are in a weird spot. Compared to the frontiers, both their pre and post training is woeful - tiny, resource constrained in every dimension including human, slow. I'd compare it to OpenAI 5 years ago except I think even then OpenAI had way more!
But they "cheat" quite a lot in distillation and very benchmark-focussed RL and that's where you get this superficial quality in the leaderboards that doesn't match up when you go off-script. Arc is a great example in that it really belies an "inferior soul" at the heart of it all.
What gives me great hope though is that those same scaling laws that Altman and others have been hyping forever will absolutely kick in for the Chinese labs just as they did for the US ones, and I don't think anything can stop that process now. So they will catch up. It won't be tomorrow, but it's not going to be 10 years either. 3-5 would be my reasonably educated guess.
And the final risk, that China itself might try to restrict availability of the tsunami of GPU or other AI hardware it will inevitably produce - well, I just can't really imagine a country that has been configuring itself for the last 40 years as a single purpose export machine deciding that actually, no, it doesn't want to export something.
About the model restrictions - absolutely. I've been trying to do security research on my own software and the frontier models immediately get suspicious. I've been playing with the local ones much more this year basically because of this. They have deficiencies, for sure - they feel very "hollow" compared to the major labs. But I've talked to a lot of people, and the consensus is pretty clear - just a matter of time.
Why are you bringing up an outdated Chinese model from 6 months ago to compare to a US model from 6 months ago? The outdated Chinese model will have performance from ~12 months ago, obviously. But today's Chinese model DeepSeek 4 has performance not far from the US model 6 months ago; 46% compared to 52% from 5.2.
It definitely 'feels like' it is as good as Claude for many regular web app coding tasks (though I don't have real benchmarks). And it is comically cheap.
I'm not suggesting it is better than the latest Claude or codex models, but it seems 'good enough' for a lot of use cases in my limited real world testing.
I don't think every dev will be comfortable just releasing claude on their project.
This shows that AI cloud consumption is just a conspicuous consumption status symbol, nobody knows why they need cloud AI or what problem they are even solving.
Likewise Qwen 3.6 absolutely blows me away and that’s on a 35b 6-bit model on a local 5090. Same thing, busy trying to find stuff to do to keep it busy 24/7.
I can still find some niches for Opus 4.7 but being able to attack problems and not worry about consumption is a game changer.
I will say, as pointed out by others, DeepSeek and other Chinese providers still lack a bit in the tooling that Claude has, but they'll get there.
This is not just about mainland China though. The current US government is extremely selfish and self-centered. Other countries really need to consider for their own long-term situation here.
Also, he concedes Mythos-level capabilities will be cheap next year, then handwaves it with "you need the best AI, not good-enough AI." For most use cases, frontier minus six months is fine.
Open models that are competitive with frontier will be used on shared hosts.
And with the extreme chip shortages for the next two years, there's little appetite for even bigger models anyway.
Barring a breakthrough in scaling, the only direction the models can really go is smaller. Which will inevitably mean better performing local models for same chip budget.
You can always run these models cheaper locally if you're willing to compromise on total throughput and speed of inference. For most end-user or small-scale business needs, you don't really need a lot of either.
edit: I'm specifically referring to the "5.5 Pro" model, not regular 5.5 with Pro tier subscription. Claude has no model available that's comparable to 5.5 Pro either.
The thing is, vast majority of code tasks aren’t a venture into the unknown. We as an industry for the most part build CRUD interfaces and dashboards. That can be achieved, with supervision, with frontier open-weights models quite well.
This works for us and will work for years to come. It is not SOTA, but it works darn well for our purposes, and we control the compute and data flowing through it, so totally worth it.
In other words, if AI does have continued significant economic impact, only the US and China would be able to leverage it completely. The rest of the world is implicitly betting that AI won't be good enough, or that eventually the compute curve flattens out so using a model that is 10x larger only leads to marginal benefits.
Is it even though? Quantization and speculative decoding are improving the local AI story by leaps and bounds every month.
All these tricks like quantization and speculative decoding can also be used by the leading AI labs, which means they will simply have more compute than you at the end of the day. So far this has translated into better performance.
There's also an additional economic concern that rarely gets mentioned: because no one has cracked continual learning, keeping models up-to-date and filling in gaps in performance requires retraining on an ever growing dataset. Granted, you aren't starting from scratch each time, but the scaling required just to stay relevant looks daunting.
I don't know where any this goes on a societal level, but I've believed since the release of deepseek r1 that access to frontier models would eventually be locked up behind contracts, since the only moats protecting the models themselves are purely artificial. It remains to be seen how effective China is at pushing the envelope, and whether they are interested in providing unfettered access. And on top of that, it remains to be seen how well these models actually turn out to scale in the long run.
But if progress keeps going I'm sure it will get to the point where my brain doesn't feel sick after watching it. I hope so, because I'm sure there's a lot of AI videos in my future, whether I want them or not.
(There might be a workflow solution to that. Part of the system needs to do the job of what old films list as the "continuity girl". For each shot, there's a blocking diagram of who stands where at the beginning of the shot. There's a description of what each character is wearing, holding, or touching. If something generated that for the end of each shot, and it was fed into the prompt for the beginning of the next shot, that would help maintain continuity. This is another example of where a concrete mid-level abstraction is needed to keep things on track.)
Anyone have any idea what tool generated this? It's way past Stable Diffusion.
As long as they need shots longer than a few seconds, I suppose
>Now, very little is wrong.
You think culture is a matter of whether you've genned bass drums in front of or behind the drummer? (or to be a little more critical, whether you've remembered to add "sprinkle in some racial diversity" after the first prompt). You got the Coca-Cola trademark just popping up throughout, though, good job there
There’s no narrative, there’s now sense of reality, it’s just a sense of here’s a million pixels of colours that have proven to go well with each other, it’s _slop_.
It’s been years and the only place AI has conquered in visual entertainment is as a subpar Photoshop replacement to fill in the B-roll gaps for those that don’t have the patience or money to do it the proper way.
Physics.
We have to really rethink how and what we teach, and how we evaluate. Scoring (non-handwritten) homework is pointless, even contra-productive (because it incentivizes cheating, even for the students who don't want to, just to not be outscored by the cheaters). Hand-written homework means the students at least have to have read the work once...
And soon, with AI glasses, even in-classroom tests will be difficult.
People pay for cars and trucks (same cost scale) globally as they’re profit-generators for every user (as far as giving them access to jobs).
This is the same.
I tried to sign up for deepseek API access directly from the company out of gratitude for the open source contribution (deepseek.com) but payments are blocked by US government rules.
> “The two AI superpowers are going to start talking. We’re going to set up a protocol in terms of how do we go forward with best practices for AI to make sure nonstate actors don’t get a hold of these models,” Bessent told Joe Kernen on Thursday, on the sidelines of President Donald Trump’s two-day meeting in Beijing with Chinese President Xi Jinping.
https://www.cnbc.com/2026/05/14/us-china-ai-rules-bessent-us...
OpenAI is already talking openly about gated access to their models (see this OpenAI podcast episode for example: https://openai.com/podcast/#oai-podcast-episode-16)
Separately there's also a very active effort to stop open weight releases.
It's dangerous to those who think access to frontier intelligence is important.
OpenAI etc need to make crazy revenue to get their investment math to work. Perhaps you can sell some tokens to privileged partners at a premium rate but I think they’ll need global scale ultimately
I would imagine not single everyone on HN have enough disposable income that allow us to subscribe Claude Max or other similar max plan of other models without thinking.
Some people mentioned open weight model, but there are two hurdles. One the current economic mean securing the best hardware is already stupidly expensive compare to a year or two ago. And the open weight model lack the magic that Claude/Gemini/OpenAI put in the proprietary one, meaning one will have to create their own agent that is clever enough to search the internet when it knows its training data is stale.
You don't need the Max plan with other models if you're not going completely crazy. Other providers have much more generous limits than Anthropic.
Ultimately it's a resource control issue. To power AI you need land/space (to build on), water, energy, and lots of hardware. Hardware needs to be manufactured and engineered. It needs metals, some exotic materials, machines, etc. More resources in other words. If you look at China vs US here, they are really well positioned in terms of resources and supply chains. The US has fallen behind quite a bit on energy and all the critical resources needed to produce hardware. AI is bottle necked on a lot of stuff that China has or makes in abundance.
For the frontier models, there are a growing number of companies and countries that provide them. We're used to mostly talking about the US ones. But of course the Chinese have a lot of capability here and they are not that far behind. And that's judging by the models they choose to release under OSS licenses. Those models are not their frontier models. And there are a lot of other countries developing and using models that aren't necessarily talking openly about what they are doing.
The irony with these frontier models is that they only generate revenue if people can use them. Why sink billions in AI infrastructure and models without a revenue model?
The reality with Mythos is that you have to assume that the Chinese (and others) are not that far behind and may already be running an equivalent model that they just haven't told anyone about yet. Anthropic gate keeping Mythos and its findings is probably wise. But it's not long term sustainable to depend on that happening or working very well. Or even on them even being a leader in this space.
This is becoming an arms race between countries, and economies. And it's an economical and resource control race. Developing and researching in the open has advanced things massively. But it has also empowered the rest of the world. Both Anthropic and OpenAI are staffed with people from all over the world. You have to assume that they probably aren't very good at keeping things secret.
The Chinese labs have reached "escape velocity" long ago - they will continue development regardless of API access to US models or the willingness of US labs to share their research.
For example, with the $40/month Kimi Code subscription the limits are so generous that you can use it every day all the time for everything (basically just have an agent constantly running doing something) and never run out of tokens/hit the limits.
- people living in places with higher cost of living and corresponding salaries
- people whose employers are paying for it
- people who aren't actually using it but are being paid to hype it up online
- bots
But, I think, with every revolution, hierarchies have only historically fallen only for the former serfs to rise.
The industrial revolution, the renaissance -> all were marked by an massive shift in the socioeconomic status and the rise of the middle class.
I think AGI, when it happens, will only raise equality. I may be wrong.
So, sure, AGI might raise equality - but that's only if we fight for it.
You need to understand that these models are provided by the corporate entities, they are expensive to maintain, iterate and run. There is still no strong correlation between the use of AI and the business outcomes so there should be a real ceiling to how much enterprises would pay for tokens. The gov is a usual choice to establish contracts and get some stability, similar to building nuclear reactors or military equipment. And posturing about limiting model access is just saying it is expensive to subsidise its use for cat image generation or call summaries.
I am pretty sure we have not found the killer app (like an IDE even) for us to extract all the possible value from the models yet. I would even go as far as to say that the synthesis between a human and AI could leverage average models to achieve a lot more compared to the model/agent working on its own.
edit: Just to add to this, I am going through Mythos scans and it is not perfect, very much similar to what pentesters would do with the added bloat of noise in reports about nonissues.
Assuming that some humans are worse than others because of their flag picture and that they deserve less access to resources is barbarism. There is no security in limiting access to NSA-style entities; it's an absolute insecurity for everyone but them throughout the whole world. How is that in anyone's "interests"?
We see every day now how suspicious bugs that look exactly like backdoors (i.e., Microsoft BitLocker) get exposed. That's in humanity's interests (and those of particular nations as a subset) — not being subjugated by small rings of professional outlaws. We need these instruments to defend people, everywhere. We don't need to give a leverage to any state psycho. Let's make everyone of them weaker.
Would that make those countries more attractive to young people perhaps? As a place to grow and learn skills where the opportunities are non-existent in the AI Sovereign countries.
I suspect this was just a throwaway word usage, but its usage here ends up being pretty anti-Semitic, so probably worth reconsidering its use if that wasn’t the intention of your post.
Glad to see others catching on.
The Trump Administration telling the very neo-fascist oligarchs who bought him an election and bought him a ballroom to play nice with their toys? At the expense of rampant capitalism? Lol.
He already showed us the limit of his comprehension of the topic when he made EO 14179 limiting states from regulating AI.
Trump doesn't swing for perfect pitches. He is a madman, a lunatic, and a true moron. Do not give this man any credit. I would be shocked if he could tell you the time on an analog clock.
Coming from South Korea—a nation outside the US-China dichotomy—the fundamental issue I see is the closed nature of the American AI ecosystem. Products like Gemini, GPT, and Claude are API and subscription-based, meaning their pricing and access terms can change at any moment. If that volatility increases, developers desperate to escape vendor lock-in will inevitably turn to local models.
Chinese open-source models like Qwen and DeepSeek are already exerting massive influence over our domestic AI ecosystem. While the US still revolves around CUDA, China has built its own CANN ecosystem. Most impressively, Chinese local models are incredibly accessible, even for a foreigner like me.
I believe that while the US will retain dominance over the cutting-edge frontier inside Silicon Valley, the logical ecosystem—the models that individuals can actually download, run, modify, and build upon—will increasingly be dictated by China. Closed American models may lead in absolute performance, but open Chinese models will act as the foundational anchor against price resistance. If US companies attempt excessive price hikes, these powerful open models will cap those increases.
This feels remarkably parallel to the history of Linux servers. Data centers chose Linux because, at scale, avoiding licensing costs, maintaining deployment control, and escaping vendor lock-in are critical. Windows Server still plays a role where vendor accountability and specific enterprise integrations are required, but in large-scale infrastructure, open systems overwhelmingly won.
We are likely to see the exact same phenomenon in AI. A n open local model doesn't have to be the absolute bset. If it is 'good enough,' cheap, easy to deploy, and free from volatile vendor pricing, it will become the core of the infrastructure layer.
If that happens, the foundational 'layer of thought' embedded in our systems might no longer be based on American cognitive frameworks, but on Chinese ones
I am certain that AI will be deeply integrated directly into our infrastructure. The reason is simple: spending time memorizing YAML syntax just to configure a CI/CD pipeline is a complete waste of time. Because of this, we will inevitably see a surge in services that orchestrate small, domain-specific agents tailored for these exact niches.
When that happens, are we really going to integrate expensive American model APIs to run them? Or will we just rent small GPU servers and spin up local models? I strongly believe the latter is far more likely.
I came up with a shorter summary of what you refer to as "my work"
Decentralisation is too important to leave to the (direct) decentralisers.
To ensure that the externalities of standardisation are borne by the standard-proposer, eg.Echoing your countryman https://archive.ph/2014.04.30-203815/http://www.theguardian....
But also Georges Clemenceau ("War is too important to leave to the generals")