Except there are providers that serve both chinese models AND opus as well. On the same hardware.
Namely, Amazon Bedrock and Google Vertex.
That means normalized infrastructure costs, normalized electricity costs, and normalized hardware performance. Normalized inference software stack, even (most likely). It's about a close of a 1 to 1 comparison as you can get.
Both Amazon and Google serve Opus at roughly ~1/2 the speed of the chinese models. Note that they are not incentivized to slow down the serving of Opus or the chinese models! So that tells you the ratio of active params for Opus and for the chinese models.
And Microsoft's Azure. It's on all 3 major cloud providers. Which tells me, they can make profit from these cloud providers without having to pay for any hardware. They just take a small enough cut.
Deployments like bedrock have no where near SOTA operational efficiency, 1-2 OOM behind. The hardware is much closer, but pipeline, schedule, cache, recomposition, routing etc optimizations blow naive end to end architectures out of the water.
Many techniques are documented in papers, particularly those coming out of the Asian teams. I know of work going on in western providers that is similarly advanced. In short, read the papers.
How is this related to the inference, may I ask? Except for some very hardware-specific optimizations of model architecture, there's nothing to prevent one to host these models on your own infrastructure. And that's what actually many OpenRouter providers, at least some of which are based in US, are doing. Because most of Chinese models mentioned here are open-weight (except for Qwen who has one proprietary "Max" model), and literally anyone can host them, not just someone from China. So it just doesn't really matter.
I mean sure, but in terms of cost per dollar/per watt of inference Nvidia's GPUs are pretty up there - unless China is pumping out domestic chips cheaply enough.
Also with Nvidia you get the efficiency of everything (including inference) built on/for Cuda, even efforts to catch AMD up are still ongoing afaik.
I wouldn't be surprised if things like DS were trained and now hosted on Nvidia hardware.
> The new 1s have a mandate to at least run on local hardware.
They do? Source?
But if that's true, it would explain why Minimax, Z.ai and Moonshot are all organized as Singaporean holding companies, with claimed data center locations (according to OpenRouter) in the US or Singapore and only the devs in China. Can't be forced to use inferior local hardware if you're just a body shop for a "foreign" AI company. ;)
They do have different infrastructure / electricity costs and they might not run on nvidia hardware.
It's not just the models.