The Chinese labs don't have to make money or be profitable. They are funded by the state to achieve the state's goals, and the global praise of their open models just serves as Chinese soft power.

They're state companies, not some kind of ethical VC charity fund project.

Correct. Open source is a PR and marketing strategy for new labs, regardless of origin.

https://try.works/#why-chinese-ai-labs-went-open-and-will-re...

You can still make money on open weight models.

The compute required to run these models is still very far out of reach for the average consumer, yet known enthusiast, therefore they still sell inference, whilst also getting consumer goodwill for providing open weights.

Thats because the USA has really nothing big to export. Yay, designs.

China? Im getting ready to watch the URKL (universal robot knockout league) go on. The USA is dicking around with failed robot dogs.

The USA has been a failed country, coasting on massive inertia. But the tech avenues from a article I cant find showed the USA 8/64 areas excelling. China was 56/64 areas excelling.

> Wikipedia is cheap compared to creating and training models.

DeepSeek said it spent $5.6M [1] on training V3, which doesn't sound too much for a near-SOTA model.

An open source entity can come up with a hybrid business model, such as requiring a small fee from those who want to host the model as a business for the first n months following the release of a new model, but making it fully free for individuals.

[1] https://arxiv.org/pdf/2412.19437

Very good point on using local ai to avoid data centers costs.

Running AI models on local hardware was exploratory at first, and if it's so easy today it's thanks to open source. It's a little bit coincidental that we have this today, and that mainstream hardware have this capability. The fact that a phone can run very small models is exploratory or some kind of marketing opportunity at best.

Why would hardware company ships cards with more AI capabilites (like more VRAM) in the foreseable future ? On what ground does the marketing for on device AI will keep generating interest ? For something as important, it's very uncertain. But above all, it should not depends on these brittle justifications.

Showing good will in distribution and research prowess today is positive communication, but it can be exactly the oppositite if/when an attack using those small models will reach a high value target.

For China the cultural difference is so huge, it's difficult to say. I would think they first and foremost need to show to evryone inside and outside of China that they match american models. Second, i would say that when americans prefer few very powerfull companies on the get go because they can leverage a lot of capital rapidly to industrialize, China will prefer leveraging a lot of smaller companies exploring a lot of things simultanously (so doing a lot of research), THEN creating legislation to let only the best (or a few) to survive effectively. In the end it's the same result (monopoly or oligopoly), but China may have a stronger core (research) and America may have stronger productive capital, that may be proved obsolete... In the long run, in either side it's a gamble, again.

Indeed cost can be another factor. Maybe also the main reason why Chrome added an offline model.

Storage has moved back and forth but I don't thnk compute has ever really gone back to thin client. Even Gmail, Google Docs, etc are running a buttload of javascript on the user device. Various attempts at avoiding that (remote .NET or JVM stuff on early "smart-ish" phones) crashed and burned.

Video game streaming is the closest thing, and it's never really taken off. (And this, IMO, is a good comparison because it's a pretty similar magnitude up-front-cost, $500-$4000.)

Once the local-AI-is-good-enough (Sonnet level for a lot of basic tasks, say) for a $1k up-front investment the appeal of having something that can chew on various tasks 24/7 w/o rate limits, API token budget charge concerns, etc, is going to unlock a lot of new approaches to problems. Essentially more fully-baked line-of-business OpenClaw-type things. Or the smart home automation bot of Siri's dreams. You can more easily make that all private and secure when all the compute is local: don't give any outside network access. Push data into the sandbox periodically via boring old scripts-on-cronjobs, vs giving any sort of "agentic" harness external access. Have extremely limited data structures for getting output/instructions back out. I'd never want to pass info about my personal finances into a third party remote model; but I'd let a local one crunch numbers on it.

Even if you need Opus/Mythos/whatever level for certain tasks, if 95% of everything else you'd pay Anthropic or OpenAI for can now be done on things you own w/o third party risk... what does that do to the investment appeal of building better AI appliances to sell end users vs building better centralized models?

I think "what if today's LLM performance, but running entirely under your control and your own hardware" opens up a LOT of interesting functionality. Crowdsource the whole world's creativity to figure out what to do with it, vs waiting for product managers and engineers at 3 individual companies to release features.

Except that buy is a trivial expense because the hardware has been bought already. You've got a whole lot of iGPU and dGPU silicon that's currently sitting idle as part of consumer devices and could be working on local AI inference under the end user's control.

It’s well within the capabilities of governments in developed countries. If Mistral did not already exist, I would definitely expect the French government to invest in a national LLM, if only because of how defensive they are of the French language.

<< That’s a thousand millions.

I can't say that you are lying and you are not exactly exaggerating either. It is true that a new SOTA model -- from literal scratch -- it would be expensive.

But, and it is not a small but, is the starting point really zero?

Outside of the USA it would not look like a wealth transfer to an oligarch.

Not every country is in a crypto-libertarian race to hoard power and wealth.