The (quite excellent) article discusses several of your points. If you haven't read it, I recommend it.

  - Commodity market profitability is determined by marginal cost of production. LLMs have marginal cost; traditional software does not.

  - Models are not free. Downloading them is free. Running them is not. This has manufacturing economics, not software economics; the idea that they are "free" is an economic category error as it relates to their actual use

  - The highest tier Chinese models are not more economical than US frontier models. Try GLM 5.2 and see how much it costs to do real work. I did, and it was more expensive than GPT 5.6.

  - This is because US labs are leading on cost efficacy of inference ($/task)

  - Training will decline as a percentage of costs as inference expands compute share due to agentic workloads. A big part of training now is optimizing token efficiency. It's hard to distill token efficiency; that is perhaps why Chinese LLMs are so inefficient.

  - With increasing inference as % of total compute, if labs create efficient models -- which they can, because they can create highly optimized models amortized over very high inference loads -- they can be low cost producers, and be competitive at $/task rates

Imagine how cool it would be if actual competition prevents Anthropic or OpenAI from becoming an Apple/Google kind of cartel. I don’t care if it comes from China or not.

The valuations are unjustified even at the prices they’re charging now.

They’re going to try their best to offload these investments into our pensions before the inevitable crash.

I for once welcome the donations to the public of our generous basilisk worshiping overlords

I think everyone understands models will be a commodity.

Its the user base (with ads and upselling) and proprietary wrappers which will make money for typical customer.

Even enterprise customers arent going to be spending a lot on tokens. Once labs no longer have to subsidize trainings tokens costs will drop 10x and once models get burned on chips costs will drop 10x more and you physically won't be able to burn significant number of tokens unless you're deliberately trying to.

We both know the answer. Write offs. If your fund was not in AI heavy you’d have no investors.

I would say it's not just the VCs but the various other entities that will be left holding the bag of debt if the AI-fueled datacenter construction boom/bubble pops. For a list of large and well known projects and their scales:

https://epoch.ai/data/ai-data-centers

> The people who are most afraid of Chinese models are the VCs who poured into Anthropic and OpenAI at astronomically high valuations.

Correct. These chinese labs has proven that having just the model is not a moat, and the safety concerns were all just attempts at regulatory capture.

This is why labs like OpenAI and Anthropic are panicking and are racing to the exit before their valuations start being questioned.

I don't think it's that black and white. OpenAI and Anthropic are building valuable tools on top of their models. You get a very rough and much less polished version of that with open source tools and and open source models. And you still need inference infrastructure to run those. But at this point most of the competition is in the tool ecosystem, not the models. And while there are plenty of people toying with things like opencode there's a clear pecking order emerging where Codex and Claude Code/Cowork are generally considered the top choices before tools like MS Copilot, Gemini, and then a rapidly shrinking long tail of alternatives to those.

In the end what companies pay for is not tokens but results. A DIY kit of models, mac minis or whatever, and a bunch of poorly integrated OSS tools doesn't solve their problem. For the same reason, people use Office 365 rather than running Libreoffice. And for the same reason things like AWS dominate the market rather than people DIYing their infrastructure together themselves. Most of the money is in polished turn key solutions. Which is what Anthropic and OpenAI offer.

The juicy market here is the enterprise market. That's mostly business users, not programmers. They'll be hooking up all their SAAS tools (which they also over pay for), and other stuff. They'll be paying for boring things like data residency, compliance, etc. And they need access to reliable infrastructure to run all this stuff. They'll want this shit to just work and not to be dealing with a lot of poorly integrated stuff.

Most of the billions invested are being sunk into infrastructure, chip design, and access to resources (land, water, energy) needed to run data centers. A handful of companies now own most of that infrastructure and they also happen to have the top models, researchers, the best tools, and warm customer relations. And they sell access via very convenient subscriptions with high enough limits that people don't have to worry about things like token cost. The game here is recurring revenue from customers that like predictable pricing, reliable quality of service, and iron clad compliance and data security & residency, and quality guarantees. These companies don't want to be chasing model quality and have to upgrade their entire company every few weeks. They want continuity and predictability. Mostly they just pay Anthropic, OpenAI, MS, or Google to take care of this for them. There might be some niche EU players that become a bit bigger. But I don't see a large scale switching to Chinese suppliers for a full polished alternative. The Chinese might give away their models. But I don't think they'll be generating a lot of revenue.

And if you want to run your own models, you'll still need infrastructure to run it. These four companies together with the usual cloud giants control most of that and as well of the supply of resources (chips, data centers, energy, etc.) in the EU and US markets. There's going to be a long tail of self hosted and gobbled together stuff but it's going to be a much rougher experience for end users and it won't likely be most of the market any time soon.

they will likely suffer enormous real losses too, not just paper, though not as enormous

for VCs, breaking even is losing

But there a ton of other VCs who poured money into SaaS businesses. They have the opposite incentive. They want tokens to be cheap like a commodity so the value accrues in the SaaS/app layer.

I guess I shouldn't try to buy shares of OpenAI on the private market...

Good. Over the past few years, VCs have proven that they’re warmongering psychopaths. Hopefully China puts every last one of the Palantir/Flock/Anduril class out of business.

mmm, the chinese models are also working on local GPUs at consumer grades. so theyre not just drainig cloud moats.

Not sure most of money is from VCs.

VCs are just pass-through investors, the money comes from billionaires. And when billionaires face losing money, the whole system re-arranges itself to stop that from happening.

[dead]

I'm a civilian, not a VC. In my own case, I'm worried how many things pass through the CCP. How censorship of mentions of Tiananmen Square is something they're quite interested in