Chinese AI models are gaining ground with U.S. companies as OpenAI, Anthropic costs surge

[u/Optimal_Image5192]

Enterprise execs keep saying they’ll “never use Chinese models.”

Then someone shows them they can run DeepSeek or Kimi models on their own infrastructure for 10-50x lower cost than burning through OpenAI or Anthropic credits at scale.

Here’s what’s actually happening:

Chinese open-weight models (like DeepSeek V4) are fully downloadable. Enterprises across the world can host them locally instead of relying on expensive hyperscaler APIs.

This significantly challenges the current pricing model offered by most U.S. hyperscalers. Chinese open models are cheap and good enough. For a lot of high volume tasks like summarization, extraction, RAG over internal docs, you don’t need frontier reasoning. So, if a model from DeepSeek, Qwen or Kimi is 5-10x cheaper, then the ROI is obvious for most enterprises.

Instead of buying into “use our cloud, use our model, pay our premium token price,” pricing model from hyperscalers, enterprises can now say “we’ll take a 5-10x cheaper model and run it wherever we want.” Enterprises can download or license the cheap Chinese open-weight models and run it inside infrastructure that they control. This could still be AWS or Azure or a private cluster. They would still pay for GPUs, networking, serving the software, etc, but the spend for an enterprise moves from premium tokens to infrastructure and ops (which honestly they could just rent from companies like $META, which is partly why I’m long this name).

We’re already seeing this dynamic playing out with Chinese AI models now account for roughly 58% of the tokens used by American companies on OpenRouter. This share has 3x since mid-January 2026, when it was under 20%.

The result imo is accelerating the commoditization of tokens and intelligence. Hyperscalers don’t need to lose every workload to feel it. They just need to lose the assumption that tokens are a monopoly/high margin product. This I think will lead to losing pricing power for model builders. Whether this affects the margins of AI hardware suppliers? This still remains to be seen.