Last month, Chinese AI models surpassed American ones in use on OpenRouter, an AI platform that allows you to detect interesting trends. And this in fact was just confirmed this month and has accelerated, because what we are seeing is that despite the obstacles that the US has tried to put in place to prevent China from competing in this market, the Asian giant has found a key tactic to do it: the so-called “token export”.
Useless tariffs. The US government the era of globalization burst with the trade war with China and more recently with its aggressive tariff policy. That has had a clear effect on Chinese exportsbut the Asian country has found a way to avoid tariffs: with AI. Its artificial intelligence models can be used around the world without being affected by tariffs. Although they are inferior in performance and quality, they are much cheaper to use, so China is managing to convince the world with its old recipe: if the product or service is good enough and is also cheap, it wins.
On the OpenRouter platform we have been seeing for two months how Chinese models are used more than those from the US for a simple reason: they are much cheaper and perform reasonably well.
Token export. When we use energy we consume kilowatts. When we use AI we consume tokens from AI models. And that is where China is winning with the phenomenon called “token export”because the tokens of their AI models are extremely competitive and for many tasks those models are good enough. Minimax M2.5, Step 3.5 Flash or DeepSeek V3.2 clearly outperformed Gemini 3 Flash Preview, Claude Sonnet 4.6 or Claude Opus 4.6 in use in the last two months on the OpenRouter platform, for example. Developers from all over the world take advantage of these models and do so without being affected by tariffs: tokens do not pay those fees that, for example, apply to mobile phones, cars and many other products.
Devastating price difference. While an American premium model like Claude Opus 4.6 costs 5 dollars per million entry tokens (Sonnet 4.6 costs 3), Chinese models like the MiniMax M2.5 cost as little as $0.25, 20 times less, and the Step 3.5 Flash, also very popular, costs just $0.10, 50 times less.
AI agents ask for cheap models. That price gap is especially relevant now that AI agents —and especially, OpenClaw— begin to demonstrate their ability. These types of systems are capable of completing tasks for us and even controlling the machines to which we give them access, but to achieve this they use a huge amount of tokens. Using the best models guarantees better results, but it is also very expensive, but in many “simple” tasks, very cheap models like the Chinese ones They can perfectly solve the problem.
The subscription trap. In recent weeks, the rise of OpenClaw and similar platforms has provoked a curious response from companies like Anthropic or Google. To these companies they don’t like it that subscription plans for your AI models be used for these types of AI agents because they argue that those plans are abused, and there are certain restrictions to that type of uses. This has caused many users to opt for AI models from Chinese companies, which are precisely positioning themselves as the cheap and trouble-free alternative to be able to take advantage of these agents.
Why Chinese tokens are so cheap. There are several factors that favor the low cost of AI models in China. The first of them, cheap energy: the costs of industrial energy They are 40% smaller than in the United States. The second, its efficient architecture: as DeepSeek demonstrated, it is possible to achieve great results with techniques like Mixture of Experts (MoE). With it, the model is divided into multiple “experts” and only activates those that are necessary according to the request.
The irony of tariffs. Curiously, the US restrictions on the export of advanced chips may have ended up being the great catalyst for this situation. By not having access to the most advanced NVIDIA chips, Chinese companies were forced to perfect the efficiency of their models to the maximum, and that has now caused be more competitive in the AI inference market (that of the use of models in practice), which is where this new economic battle is being fought.
Challenges. Although the “token export” is currently profitable for China, it faces significant challenges. The data sovereignty is one of them: for a company or a government, sending sensitive data to data centers in China is a red line. There is also the problem of latency: the response of China’s AI models is affected by the enormous distances that these data packets have to travel. It remains to be seen if Washington ends up applying some kind of measure to also restrict the use of AI models from Chinese companies, although that seems more complicated.
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