Nice research and structuring into 4-tier layer. For providers like Anthropic and OpenAI, subscription is the entry point for all these, right? Besides the measures proposed in the article, can token usage % determine these clusters of accounts?
I believe your statement. Labs do not publish subscription vs. api revenue and difficult to guess with no priors.
Subscription is to drive adoption - fixed cost, can adjust the usage eg. give resets, increase quota based on capacity available. We subscribers tend to take it as a mandatory benefit :-) For labs, it is not letting the capacity go waste.
api is the $$ driver - pay per use, enterprises.
Right now, Kimi needs to first hit the subscribers at the level of OpenAI and Anthropic. With the api usage skyrocketing due to K3, it will be clear in a few months on the actual subscription benefits.
> The US has invested trillions in AI that the companies involved are never going to make back. Even without competition from open models, but definitely not with it. And if those trillions turn out to be worthless, that's going to have a massive impact on the market and cause a lot of bankruptcies.
This is the point. And what nobody seems to bring up that inference is a massively profitable margin. The labs can still grow at 80% margin as opposed to 99% margin (I do not have the numbers). But that will hurt the valuation and investors.
With protection from Govt, you can compete at 1.5 or 2x of the equivalent open weights price. But it is not sustainable to keep the prices high, just a matter of time.
I think this goes to show that the newer models will be capable of. I won't be surprised if the Governments across the board come together to put a size limit on open weights model or ship them with guardrails in place. That will be really a sad day if that happens. It is difficult to imagine the state of the Internet if models of this capability are left open.
AI (llm) will be a commodity market => I am not sure it was obvious. As of last month, folks thought open weight models are lagging by 6+ months. Once K3 is taken for a deep run across many use cases, it will be clear where it stands. But yes, I agree that now that intelligence is commodity, everything changes.
I think in general rest of the world needs to take notice (not saying afraid), starting with the US. It cannot be taken for granted that China's frontier labs will be a few months behind. They might be at par or exceed.
The lessons from steel, solar and EV needs to be learned by all lawmakers. You have to respect and learn from how China Government puts the system in place for complete industry takeover and they have been very good at it. The problem with AI is that democracies will be inherently slow in adopting AI, unless something changes in the system.
At minimum, every democratic Government (US, Europe, India) need to build long-term AI vision and execute that no matter which party comes to power. Additionally, be ruthless about protecting domestic labs. It can only be possible if the intelligence pricing by domestic labs per productive task is in the similar range as open-weights models. Right now, it is not the case, even if the article gives the example of Sol vs K3.
Protecting domestic labs means not bailout, but fast track to cheapest energy, fast track approval for data centers, enforce some guardrails so customers get to use the open weights models only hosted in the country by US (or Europe) businesses. Without these protections, it might be a slow death.
In the earlier days of the USA we did the same thing, with our government having an industrial policy that fed US industry and put us ahead of Great Britain.
It doesn't have anything to do with the form of government, it has to do with the aims of the government.
What is this panic and protectionism supposed to be good for? This is open source software, there is no "AI industry", there's virtually nobody employed in this. "Domestic AI" makes about as much sense as a domestic Linux kernel. If the Chinese want to subsidize the world's water and energy use to supply the world with chatbots good luck to them. There's no need for guardrails or fast track data centers, they can plaster their entire country with data centers to churn out slop, I'm glad we don't
I think it is deeper than that. "LLM => peak of productivity" takes way less time and effort than "Linux kernel => any productive work". Compare Dec 2025 vs July 2026 models in terms of capabilities.
Nobody can predict 5 year out. However, the country that can be ultra efficient by making their governance, health, manufacturing, military, etc AI-native will be far ahead in the game.
There's no evidence that these things make anyone more productive, in fact the opposite, empirical research suggests users are less efficient while thinking they're more efficient. You're invoking "AI" the same way the blockchain people did before they all finally died out. "You need to put the government on the blockchain bro, you're gonna lose out to the future bro", turns out you don't
But that's not really even relevant to the debate. Insofar as software has made the world more efficient, it doesn't matter where it's written. That's the point of open source software, there's no tacit knowledge. When a country loses its nuclear engineering capacity that's dangerous because it takes a long time to rebuild. The only reason the Chinese are already competitive on LLMs but haven't managed to make a state-of-the-art jet engine is because the latter, unlike software, is difficult to copy and you don't need to worry about something you can copy.
There is no coming back. After all, open-weight is NOT open-source. It is basically free model. And you pay to host it.
The value proposition is that 100's of providers and host and sell it. 1000s of businesses (eg. Microsoft, Databricks, Palantir to small startups) can run it, finetune it and own the IP and pay only for hosting.
On the other hand, you have OpenAI and Anthropic, who need to charge at 90%+ inference margin. It is because of 1) sunk cost, 2) sky-high salaries that they paid to keep the talent. Companies like Meta screwed things up badly by paying billions of $ for chief engineers.
Chinese labs are doing a favor to the world. But I can also say with 100% certainty that if US labs were to close shops next year, Chinese labs would immediately start charging $$. In fact, I think it might happen with open weights model soon. But still these fees will be one-fifth or one-tenth per token. Also it does not come with all the guardrails.
Solution: US labs need to reduce their costs, cut the salaries across the board and compete. AI and robotics are the last hope of US to get back to industrialization and continue being the superpower.
> Chinese labs are doing a favor to the world. But I can also say with 100% certainty that if US labs were to close shops next year, Chinese labs would immediately start charging $$.
How would do you explain the pricing of Chinese solar panels, after managing to destroy other countries' solar industries? The prices are still dropping per watt.
Could it be China's internal demand for solar is big enough, and its long-term governmental strategy on renewables result in an outcome that almost looks like largesse to the rest of the world? I suspect Chinese AI may follow a similar path.
FYI if you look into what has happened in the wholesale solar market since the end of 2025, this is no longer true. Prices are now 20% higher than they were in Nov/Dec, and were even higher earlier this year. Hard to predict the future but we may have reached a price floor, as at 2025 prices the module suppliers were below cost and losing money. The market dynamics have changed significantly since then
China may well save the world with green energy but I’m skeptical to assume we should just trust them to share their best intelligence with us freely, it’s a totally different think to sharing their best intelligence.
The low prices were below cost and everyone knew it. Modules fell to $0.07–0.09/W through 2024 and early 2025 while Chinese manufacturers took heavy losses to hold share. In H1 2025 alone the top four module makers lost a combined $1.54B. JinkoSolar, LONGi and JA Solar shipped 100GW+ between them and still posted revenue declines of 33%, 15% and 36%. It was a systematic takeover financed by 1) cheap capital, 2) local-government land and tax support, 3) a tolerance for losses that no Western balance sheet can match.
Then the state decided the bleeding should stop, and prices went up. Polysilicon utilization was cut to 55–70% and prices jumped 48% in September 2025 alone. On Dec 25, 2025, LONGi, TCL Zhonghuan, Gokin and Shuangliang jointly raised wafer quotes ~12%. Module prices had already rebounded from CNY 0.6 to ~0.9/W, and 2026 talk is toward CNY 1.00 (~$0.21)/W. Same firms, same factories, same cost curve. Different instruction.
So the structural advantage is completely real. China’s share of every stage — polysilicon, ingot, wafer, cell, module — exceeds 80%, which is more than double its share of global demand. It also hosts all ten of the world’s top PV equipment suppliers. Xinjiang alone is 40% of global polysilicon. One in seven panels worldwide comes out of a single facility. That is the whole belt: raw material, the machines that make the machines, and final assembly, all co-located.
So there are two different things here. The floor is cheap because of clustering, scale and learning curve. The below-floor pricing was strategic, and it has already been switched off now that the competition is gone. Only the first one survives without a policy decision behind it.
Below-cost pricing ends the moment the sponsoring state decides it should.
This comment has been flagged in our software as AI-generated. Of course it could be a false positive (though from reading it myself it does come across as LLM-influenced). But if you've used AI to write or polish the text, even just a little bit, please don't. The guidelines specifically ask us not to do this: https://news.ycombinator.com/newsguidelines.html#generated
While this has clearly been written by / with help from an LLM, the general info is correct and matches what I have heard from those suppliers (although $0.21/W future pricing is far higher than the estimates I've seen)
Pangram believes this is 100% AI generated. High confidence. If you just used AI to edit your work, then it would say it was human influenced or low confidence, which is contradictory to another comment you claimed.
Just out of curiosity, what is the change and how are you measuring its rate?
From no internet to internet the change is pretty profound. But my job is already very automated for the most part. It's true AI might automate it a bit more, but it's not like I'm going from zero automation to full on automation. That's not nothing, and it is worth something, but it's also not internet from no internet level of change either.
“The lawmakers said a recent analysis by a commercial company provided to the committee indicates that these devices may potentially collect and transmit extensive user data -- including sensitive personal information to servers under Chinese jurisdiction without explicit user consent.”
They could do that according to an unspecified "commercial company", as reported in an article titled, "Lawmakers want US Commerce Department to probe Chinese smartphone maker OnePlus".
