Token goes global, selling Chinese electricity to the world

Author: Black Lobster, Deep Tide TechFlow

In the summer of 1858, a copper-core cable crossed the Atlantic Ocean floor, connecting London and New York.

The significance of this event was never about transmission speed, but about power structures—who laid the submarine cable could siphon off the flow of information. The British Empire, through this global telegraph network, controlled intelligence from colonies, cotton prices, and war news.

The empire’s strength was not only its fleet but also that cable.

Over 160 years later, this logic is being reenacted in an unexpected way.

By 2026, China’s large models are quietly consuming the global developer market. According to the latest data from OpenRouter, Chinese models account for 61% of token consumption among the top ten models on the platform, with the top three all from China. Developers in San Francisco, Berlin, and Singapore send API requests daily, crossing the Pacific via submarine cables to Chinese data centers, where computing power is consumed, electricity flows, and results are sent back.

The electricity never leaves China’s power grid, but its value is delivered across borders through tokens.

AI Model Migration

On February 24, 2026, OpenRouter released weekly data: the top ten models on the platform consumed about 87 trillion tokens in total, with Chinese models accounting for 53 trillion, or 61%. MiniMax M2.5 led with 2.45 trillion tokens, followed by Kimi K2.5 and Zhizhi GLM-5—all from China.

Latest data as of February 26

This is no coincidence; a spark ignited everything.

Earlier this year, OpenClaw emerged—a truly open-source tool that allows AI to “do work” directly on computers, execute commands, and parallelize complex workflows. Its GitHub stars surpassed 210,000 within weeks.

Financial professional John installed OpenClaw immediately, integrated it with Anthropic API, and began automatically monitoring stock market information, providing timely trading signals. Hours later, he stared at his account balance in disbelief: a few dollars, gone.

This is the new reality brought by OpenClaw. Previously, chatting with AI involved a few thousand tokens per conversation, costing almost nothing. After integrating OpenClaw, AI runs multiple sub-tasks in the background, repeatedly calling context and looping iterations, causing token consumption to grow exponentially. The bill accelerates like a car with its hood open, the fuel gauge dropping—unstoppable.

A “trick” quickly circulated among developer communities: using OAuth tokens to connect Anthropic or Google subscription accounts directly to OpenClaw, turning the monthly unlimited quota into free fuel for AI agents. Many developers adopted this approach.

Official countermeasures soon followed.

On February 19, Anthropic updated its terms, explicitly banning the use of Claude subscription credentials for third-party tools like OpenClaw. To access Claude’s features, API billing must be used. Google also broadly banned subscription accounts accessing Antigravity and Gemini AI Ultra via OpenClaw.

“Long have the people suffered under Qin,” John then embraced domestic large models.

On OpenRouter, domestic models like MiniMax M2.5 scored 80.2% on software engineering tasks, while Claude Opus scored 80.8%. The difference is negligible. But the prices are worlds apart: the input cost per million tokens is $0.3 for the former, $5 for the latter—about 17 times higher.

John switched over, workflows continued, and bills shrank by an order of magnitude. This migration is happening globally in parallel.

OpenRouter’s COO Chris Clark explained plainly: Chinese open-source models capture a large market share because they are disproportionately used in US developer workflows.

Power Going Offshore

To understand the essence of token export, one must first grasp the cost structure of a token.

It appears lightweight—roughly 0.75 English words per token. A typical AI conversation consumes only a few thousand tokens. But when these tokens stack into trillions, the physical reality becomes heavy.

Breaking down token costs, there are two core components: computing power and electricity.

Computing power is the depreciation of GPUs. Buying an Nvidia H100 costs about $30,000, and its lifespan amortized per inference is the depreciation cost. Electricity fuels data center operation—each GPU at full load consumes about 700 watts, plus cooling costs. A large AI data center’s annual electricity bill can easily exceed hundreds of millions of dollars.

Now, map this physical process.

An American developer in San Francisco sends an API request. Data travels from California via submarine cable to a Chinese data center. GPU clusters start working, electricity flows from China’s grid to the chips, inference completes, and results are sent back. The entire process may take only one or two seconds.

Electricity never leaves China’s grid, but its value is delivered across borders through tokens.

Here’s a magical aspect that traditional trade cannot match: tokens have no physical form, no customs, no tariffs, and are not counted in current trade statistics. China exports vast amounts of computing and electricity services, yet in official trade data, it is almost invisible.

Tokens have become derivatives of electricity; token export is fundamentally electricity export.

This is also thanks to China’s relatively low electricity prices—about 40% lower than the US—an inherent physical cost advantage that competitors can easily replicate.

Moreover, Chinese AI large models have algorithmic and “involution” advantages.

DeepSeek V3’s MoE architecture activates only parts of the model during inference. Independent tests show its inference cost is about 36% lower than GPT-4o. MiniMax M2.5, with 229 billion total parameters, activates only 10 billion.

At the top level is involution—companies like Alibaba, ByteDance, Baidu, Tencent, Moon’s Shadow, Zhizhi, MiniMax… over a dozen firms compete fiercely on the same track, with prices already below reasonable profit margins. Loss-making and hype-driven strategies are now industry norms.

This resembles China’s manufacturing export strategy—leveraging supply chain advantages and industry involution to push token prices down sharply.

From Bitcoin to Tokens

Before tokens, there was another form of electricity export.

Around 2015, power plant managers in Sichuan, Yunnan, and Xinjiang began welcoming strange visitors.

These people rented abandoned factories, filled them with dense machines, and operated 24/7. The machines produced nothing but kept solving a mathematical problem—occasionally, from this endless math problem, a Bitcoin was mined.

This was the first form of electricity export: cheap hydropower and wind power converted into globally circulating digital assets via mining hardware, then monetized on exchanges for dollars.

Electricity didn’t cross borders, but its value, carried by Bitcoin, flowed into global markets.

During those years, China accounted for over 70% of global Bitcoin mining hash power. Its hydropower and coal power, through this indirect route, participated in a global redistribution of capital.

In 2021, all this abruptly stopped. Regulations tightened, miners dispersed, and hash power migrated to Kazakhstan, Texas, and Canada.

But the logic never disappeared; it was just waiting for a new shell. When ChatGPT emerged, large models became the new battleground. Former Bitcoin farms transformed into AI data centers; mining hardware became GPUs; the Bitcoin mined turned into tokens. Only electricity remains unchanged.

Bitcoin’s offshore journey and token’s offshore journey are structurally isomorphic, but tokens now hold greater commercial value.

Mining is purely mathematical computation; the Bitcoin produced is a financial asset. Its value derives from scarcity and market consensus, unrelated to “what was mined.” Computing power itself is non-productive, more like a trust mechanism byproduct.

Large model inference is different. GPUs consume electricity to produce real cognitive services—code, analysis, translation, creativity. The value of tokens directly stems from their utility to users. This is a deeper embedding: once a developer’s workflow depends on a model, switching costs grow over time.

A key difference: Bitcoin mining was expelled from China, but token export is actively chosen by global developers.

Token Wars

The submarine cable laid in 1858 symbolized the British Empire’s sovereignty over the information highway—who owns the infrastructure can set the rules.

Token export is similarly a war without declared hostilities, facing many obstacles.

Data sovereignty is the first barrier. An API request from a US developer processed through a Chinese data center means data physically flows through China. For individual developers and small apps, this isn’t a problem. But for enterprise-sensitive data, financial information, or government compliance scenarios, it’s a serious issue. That’s why Chinese models have the highest penetration in developer tools and personal applications but are almost invisible in core enterprise systems.

Chip bans are the second barrier. China’s AI development faces export controls on high-end Nvidia GPUs. MoE architectures and algorithmic optimizations can partially offset this disadvantage, but a ceiling remains.

But these obstacles are only the beginning. A larger battlefield is forming.

Tokens and AI models have become a new strategic arena between China and the US—comparable to the semiconductor and internet wars of the 20th century, or even closer to an ancient metaphor: space race.

In 1957, the Soviet Union launched Sputnik, shocking the US, which then launched the Apollo program, investing hundreds of billions of dollars to ensure it would not fall behind in space.

The logic of AI competition is eerily similar, but the intensity will far surpass the space race. Space is physical and imperceptible to most people; AI infiltrates the economic capillaries—every line of code, every contract, every government system may run a large model from a certain country. Whoever’s model becomes the default infrastructure for global developers will gain an invisible but profound influence over the global digital economy.

This is precisely what makes China’s token export deeply unsettling for Washington.

When a developer’s codebase, agent workflows, and product logic revolve around a Chinese model’s API, switching costs grow exponentially over time. Even if US legislation restricts it, developers will resist with their feet—just as today no programmer can abandon GitHub.

Today’s token export may only be the beginning of this long game. China’s large models have not claimed to overthrow anything; they simply deliver services at lower prices to every developer worldwide with an API key.

This time, the cables are being laid by engineers in Hangzhou, Beijing, and Shanghai, and GPU clusters running day and night in some southern province.

There is no countdown to this contest; it’s ongoing 24/7, measured in tokens, fought on every developer’s terminal.