Two aspects to consider:

1. Chinese models typically focus on text. US and EU models also bear the cross of handling image, often voice and video. Supporting all those is additional training costs not spent on further reasoning, tying one hand in your back to be more generally useful.

2. The gap seems small, because so many benchmarks get saturated so fast. But towards the top, every 1% increase in benchmarks is significantly better.

On the second point, I worked on a leaderboard that both normalizes scores, and predicts unknown scores to help improve comparisons between models on various criteria: https://metabench.organisons.com/

You can notice that, while Chinese models are quite good, the gap to the top is still significant.

However, the US models are typically much more expensive for inference, and Chinese models do have a niche on the Pareto frontier on cheaper but serviceable models (even though US models also eat up the frontier there).

It's all about the hardware and infrastructure. If you check OpenRouter, no provider offers a SOTA chinese model matching the speed of Claude, GPT or Gemini. The chinese models may benchmark close on paper, but real-world deployment is different. So you either buy your own hardware in order to run a chinese model at 150-200tps or give up an use one of the Big 3.

The US labs aren't just selling models, they're selling globally distributed, low-latency infrastructure at massive scale. That's what justifies the valuation gap.

Edit: It looks like Cerebras is offering a very fast GLM 4.6

Third party providers rarely support caching.

With caching the expensive US models end up being like 2x the price (e.g sonnet) and often much cheaper (e.g gpt-5 mini)

If they start caching then US companies will be completely out priced.

Valuation is not based on what they have done but what they might do, I agree tho it's investment made with very little insight into Chinese research. I guess it's counting on deepseek being banned and all computers in America refusing to run open software by the year 2030 /snark

Yet tbh if the US industry had not moved ahead and created the race with FOMO it would not had been easier for Chinese strategy to work either.

The nature of the race may change as yet though, and I am unsure if the devil is in the details, as in very specific edge cases that will work only with frontier models ?

They're not that close (on things like LMArena) and being cheaper is pretty meaningless when we are not yet at the point where LLMs are good enough for autonomy.

I would expect one of the motivations for making these LLM model weights open is to undermine the valuation of other players in the industry. Open models like this must diminish the value prop of the frontier focused companies if other companies can compete with similar results at competitive prices.

People pay for products, not models. OpenAI and Anthropic make products (ChatGPT, Claude Code).

Then you should short the market

There is a great deal of orientalism --- it is genuinely unthinkable to a lot of American tech dullards that the Chinese could be better at anything requiring what they think of as "intelligence." Aren't they Communist? Backward? Don't they eat weird stuff at wet markets?

It reminds me, in an encouraging way, of the way that German military planners regarded the Soviet Union in the lead-up to Operation Barbarossa. The Slavs are an obviously inferior race; their Bolshevism dooms them; we have the will to power; we will succeed. Even now, when you ask questions like what you ask of that era, the answers you get are genuinely not better than "yes, this should have been obvious at the time if you were not completely blinded by ethnic and especially ideological prejudice."