> I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

They'd be wrong. Especially about Europe. Many companies are in a bind about this: they can't upload their confidential files to a service provider but they do want AI. So right now they end up with a choice: do nothing, breach their contracts, use a service provider that pinky promises not to share their data (which we have already seen they will violate) and run local models.

The latter is the reason you can't buy powerful GPUs for reasonable prices because a local model (GLM 5.3, DS 4, etc) + some hardware is all you need to solve the problem in a way that avoids the legal issues.

> I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

Quite failure by someone to assume that EU businesses would use US over Chinese, based on the current political atmosphere. US causes even bigger concerns than Chinese labs.

> they do not believe that big corporations in the US or Europe would actually use chinese models

This is exactly right. The only AI that matters from an investor perspective is the AI that is built into your phone, your car, ships with Windows and Mac, and built into legal and business tools like Lexus Nexus and Salesforce.

Everything else is hobby.

If you believe those investor, I assume you mortgage and bet all your wealth on it. SpaceX? Anthropic? Chinese has talents, electricity and Huawei. I really believe those investors are tulip blind to pile money into those western AI. China even now world number 3 ssd+ram ahead of SK Hynix. So armageddon of RAM SSD LLM model at dirt cheap price. And as time progress, large ram and small gpu will be built into handphone (which again dominate by Chinese).

> the relevance that investors assign

I think there is also a perhaps the need to assign air-quotes to "investors" when talking about the US markets.

There's too much fluff and noise there. Too much (over)leveraged trading. Too much speculation.

What the real investors think is hidden behind the actions of the speculative traders.

> I think they do not believe that big corporations in the US or Europe would actually use chinese models

The Chinese models are open-weight. You can download them and run them on your own servers. Or you can outsource to Mistral, Privatemode or any of the many other US/EU inference hosters.

So the "security, regulatory and/or business continuity concerns" arguments are effectively non-existent. And whatever argument does possibly remain, also applies equally to Anthropic, OpenAI & co.

There were pretty specific rumors about IPOs happening early this year, up to apparent insider bets on prediction platforms. Don't you think the apparent delays in IPOs could have something to do with the open weights/open source competition? The monetary conditions (interest rates,...) were better early in the year, arguably predictably so, so what would be your alternative explanation why they chose to postpone?

This isn't true, especially not with the inference engine becoming public, now you can build your on models on the same or similar architecture and ship massive gains on top of these stacks.

I think people don't realize the Salesforce SAP Palantir would love to ship these models, and they have/are shipping them.

The threat of exfilteration of data via these models is high but it's nowhere near as high as the margins.

For instance if you could cut your ai input bill by over 90% would you do it? Can you put some of that extra margin say 10-20% to make it more secure.

I know of atleast 10 fortune 500 companies that are entirely planning to or have moved to Chinese models for a large portion of their work.

It's insane people in finance are delusional enough to think that won't happen.

Maybe Govt will try to de-risk with bans on using open models but I don't think that's going to work at scale, people will literally spawn labs to launder DeepSeek/GLM models into a US model by some novel training etc approach or something.

I still don't think that it's as much a kami-kaze rather it's an attempt to normalize the world around the Chinese stack.

If DeepInfer is supported by everyone, it will be much easier to export stuff aka hardware that only supports it for now or is optimized for it.

Assume china starts selling hyper optimized Asics for inference at some point.

This feels like a race to the bottom as soon as possible because they have much lower costs, if there is a Wipeout in AI Labs in US chinese labs are largely insulated, and they can hopefully buy Nvidia chips for cheap if that does happen.

> I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

European business users (+ consumers) can access GLM-5.3 via Mistral.ai hosting. (with GDPR)

https://docs.mistral.ai/models/zai-glm-5-3

https://legal.mistral.ai/terms/get-started/

If they are open sourced, it means any random data center could host it domestically and AI becomes a utility.

Europe is going to be just as worried about using US models for large parts of government related functions and they're going to feel alot better about open source self-hosted chinese models than US models which can literally get turned off on a whim by Trump. They'd prefere home grown models if they can, but if they can't they'll go self-hosted and that'll be Chinese at this rate.

> I think they do not believe that big corporations in the US or Europe would actually use chinese models in their business operations due to security, regulatory and/or business continuity concerns.

Well they are wrong, I'm at a large EU startup and they are currently considering Deepseek as their default model, Opus/Fable would still be available for complex tasks.

There's very little understanding of business operations on HN, especially outside the tech echo chamber. The "software will eat the world" mindset.

Based on HN comments, every company would be running Gentoo and developing line of business applications in Haskell or OCaml.

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"valuations" are irrational and make dot com _valuations_ look like a miniature caricatures

"the market can stay irrational longer than you can remain solvent"

I am of course eager to pay needlessly more to support poor Anthropic/OpenAI.

Well, what can I say? If you play dirty, then so can everyone else. The way I see it, consumers are the real winners here. Just another variation of classic competition. If such open models didn't exist, then make no mistake, OpenAI and Anthropic would be making sure you are bleeding dry with your wallet without much innovation.

> It is clear from the beginning that the Chinese Open Model are a proxy for economic warfare.

I mean, what would you expect? Like USA isn't openly planning to weaponize their current AI primacy [1, 2].

[1] https://www.whitehouse.gov/presidential-actions/2025/07/prom...

[2] https://www.whitehouse.gov/wp-content/uploads/2025/07/Americ...

No, that isn't going to happen. The US can't afford to lose the AI race and US companies that can't compete will get thrown under the bus and replaced with those that can.

The DHS order only bans buying DeepSeek products directly (e.g. doing inference on their China hosted servers). It does not apply to open weights at all. And DeepSeek just gave their response to the DHS order.

Yeah, but they can't ban the rest of the world from using it :)

Isn’t this a ban on it being used by the state, rather than people/civilians?

From government and regulated places perhaps but a large portion will not care

Thats like sticking your head in the sand :)

Today the closed-source giants maintain a substantial cost-per-token advantage due to proprietary inference tricks like speculative decoding kernels, ultra-optimized FlashAttention derivatives, multi-GPU pipeline orchestration and dynamic prefix-caching algorithms.

I'm not sure whether the DeepSeek's open-sourced inference engine does all of these, but it appears that plenty of inference tricks have just been revealed for the open source community to learn from and start improving upon.

What moat?

In theory, this can allow a small US lab to compete with O/A/G and take marketshare from them with small open models deployed centrally or (and this is think is the real moat) on-prem for enterprises.

Their success is subsidized heavily by distillation, and even then, the Big Labs are no more than an OOM larger.

Not really. Anthropic’s headcount isn’t huge, and only a subset of their employees are working on the frontier. It’s also easier when you’re a follower.