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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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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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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.
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> 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.

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> Why should US or China matter if its open weights?

Weights aren’t source that can be inspected for nefarious tricks that would impact use, so, to the extent that there is a dinension of trust associated with nation of origin, being open weights doesn’t obviate the concern (I would argue, though, that there is very little reason to for nation of origin to be a significant factor in trust alone, though a finer grained consideration of origin might be sensible.)

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I wish it didn't matter to me, but it does. I work in government and we self host. No matter how much I explain to them that by hosting weights on our own hardware, it doesn't matter where they came from, they still refuse to let me deploy anything from China.
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> Why should US or China matter if its open weights?

Well, you might want to know what propaganda/censorship you are subjected to. Case in point, a regional government in Austria just learnt that their AI doesn't know about the Tiananmen Square massacre.

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