A programmer in San Francisco types a prompt and hits "enter". In milliseconds, the request travels through a fiber-optic cable beneath the Pacific Ocean and awakens a data center thousands of miles away in western China. There, rows of GPUs — fed by abundant green energy — crunch the query and beam the answer back to California almost instantly.

What actually crossed the ocean were not physical goods but "tokens" — the tiny digital units that measure how artificial intelligence models read and generate text.

For China, it is packaging its massive reserves of cheap electricity and computing power to process tokens.

To a great extent, this invisible, frictionless trade marks a new form of "token export" and a historic pivot for the world's second-largest economy.

In a watershed moment in mid-February, Chinese AI models processed 4.12 trillion tokens on the global aggregator platform Open-Router, surpassing US models' 2.94 trillion for the first time. The following week, Chinese developers — including MiniMax and DeepSeek — claimed four of the platform's top five spots, heavily driven by US users who make up nearly half of the platform's base.

Exporting tokens has quietly become China's most efficient value-added energy trade. While raw power in China sells for roughly 0.5 yuan ($0.07) per kilowatt-hour if exported, converting that same electricity into AI computing power and selling it as tokens yields an estimated 22-fold increase in value.

Industry insiders point out that the low cost is only part of the equation.

Shi Yuxia, a senior engineer at the China Academy of Information and Communications Technology, said: "Electricity prices are not the core factor allowing Chinese tokens to crush foreign competitors on cost. It is the combination of energy cost advantages, improved AI technical capabilities and supply chain dominance."

Technologically, almost all leading Chinese AI large models are open-sourced. Chinese developers have also adopted lightweight Mixture of Experts, or MoE, architectures. Instead of activating the entire artificial "brain" for every simple question, MoE models wake up only the specific neural pathways needed for a given query. This drastically cuts the computing power — and the electricity — needed to produce a single token.

To maximize this, the Chinese government has included computing-electricity synergy as a national priority in its 2026 Government Work Report at the recently concluded two sessions.

This infrastructure push connects China's world-leading ultrahigh-voltage grid with its tech sector, allowing high-latency AI training to soak up cheap, abundant green energy in the remote west, while real-time inference runs closer to eastern tech hubs.

Qiu Zeyu, a deputy partner at consulting firm Roland Berger, said that the elevation of computing-power and electricity coordination into national policy showed that China is betting big on its energy infrastructure to build a strategic moat for the digital economy.

The resulting cost-to-performance ratio has made Chinese models the quiet engines behind many Western software platforms, driving a staggering 421 percent global surge in Chinese token consumption over the past year.

Yet, economists cautioned that a structural cost advantage does not guarantee permanent success abroad, especially as AI becomes a focal point of global technological rivalry.

Xing Ziqiang, chief China economist at Morgan Stanley, said: "Token exports certainly have room to grow. But data security and geopolitical tensions remain key variables for international market acceptance."

He pointed to the case of Chinese 5G equipment makers, which offered strong technology and competitive prices but faced restrictions in some Western markets after 2018.

chengyu@chinadaily.com.cn