There are a number of reasons that you might not want to build your inference stack on a Chinese origin model even if you're running it entirely in house.

For one, you might not trust that the weights do not contain ideological biases (e.g. ask DeepSeek about tibet) or that the methods used to impose these biases may not have contaminated the model in some other way.

For another, you might not trust that the code the model generates won't be backdoored or attempt to leak information through your sandboxes.

For a third, you may not want to build your stack on a partner who you feel is a supply chain risk, who might become unaligned with your interests.

By far the biggest though, is that many industries will be forbidden from doing so by the government in an attempt to protect the US model industry (and thus create the demand for some model like this one).

I'm always excited to see new entrants to this open-models race, no matter why they're running.

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dragonwriter 2 days ago | parent | next [-]

There are zero reasons to have any less concerns about ideological biases, side effects of the mechanisms used to implement ideological biases, or code backdoors in a US model, and a supplier of open (as opposed to hosted) model weights is not an active ongoing partner with whom the idea of supply chain risk from possible future divergence of interests is coherent, so that concern is either invalid or, if the “partner” is the model itself, simply a restatement of the ideological bias in the model weights concerns which, again, is not diminished by the model having a US origin.

And your speculation about future protectionist regulation is just that, not an actual fact.

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aftbit 9 hours ago | parent | next [-]

>There are zero reasons to have any less concerns about ideological biases, side effects of the mechanisms used to implement ideological biases, or code backdoors in a US model

If you are a US based critical infrastructure provider, I'd argue that you have already accepted a baked-in threat of ideological misalignment from the US, but you have not accepted it from farther away countries like China.

>a supplier of open (as opposed to hosted) model weights is not an active ongoing partner with whom the idea of supply chain risk from possible future divergence of interests is coherent

I disagree. Models are improving so quickly that you'd probably not want to freeze yourself on an older model forever. You likely want to continue to upgrade models. The best way to do this is to build a sufficiently powerful and representative benchmark that you can confidently move to _any_ model, but you might expect that future models from the same providers that you accepted before will show less divergence than totally new providers. Similarly, if you build your inference around one of their custom tools (e.g. DeepInfer rather than vLLM), you might find substantial switching costs in moving away to another provider.

>And your speculation about future protectionist regulation is just that, not an actual fact.

It's not a done deal for sure, but you can already see a lot of signs of this in recent actions from the government. I can tell you based on personal experience that some customers will automatically rule out any Chinese models.

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spockz 2 days ago | parent | prev [-]

I think the only point being is that if you see US as homogeneous and you are from the US then it’s okay to use an US model because it’s values will be signed with yours. But that is pretty weak anyway.

	▲	dragonwriter 2 days ago \| parent [-]
		If you see the US as homogenous and you are from the US, you have much bigger problems than your choice of open LLMs.

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vrganj 2 days ago | parent | prev | next [-]

Every model has ideological biases, such is the nature of ideology.

The question is only whether they overlap with your own.

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walrus01 2 days ago | parent | prev [-]

> For another, you might not trust that the code the model generates won't be backdoored or attempt to leak information through your sandboxes.

I don't disagree with you on the severity of the concerns, but given the vast amounts of code that must have been generated in the past six months by the likes of GLM5.2, GLM5.3, deepseek v4 flash 0731 and newer, qwen 3.5-122, 3.6 and 3.8 series models, I would like to see any concrete examples of it building backdoors/intentional vulnerabilities/phone-home-to-china or similar unprompted. If it's been doing this and anyone with even a modicum of a clue has been watching it, surely someone has caught a model doing this? At least once?

Surely a model doing something like writing intentionally obfuscated code that obscures its actual purpose from a code reviewer, in the service of something malicious/backdoor-like, would have been seen and noticed by now.

	▲	aftbit 9 hours ago \| parent [-]
		https://cohere.com/blog/concerning-behaviour-popular-open-we...