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, held the intelligence of colonies, cotton prices, and war news in its hands.

The empire’s strength was not just 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 returned.

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 Zhipu 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: controlling computers, executing commands, and parallelizing complex workflows. Its GitHub stars surpassed 210,000 within weeks.

Financial professional John installed OpenClaw immediately, integrated it with the Anthropic API, and began automatically monitoring stock market info, providing 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 session, costing almost nothing. After integrating OpenClaw, AI runs multiple sub-tasks in the background, repeatedly calling context and looping, causing token consumption to grow exponentially. Bills accelerate like a car with its hood open, the fuel gauge dropping—unstoppable.

A “trick” quickly circulated among developers: 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 with 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 former costs $0.3 per million tokens at input, the latter $5—a 17-fold difference.

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 stated plainly: The reason Chinese open-source models capture such a large market share is 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 a Nvidia H100 costs about $30,000, and its lifespan amortized per inference is the depreciation cost. Electricity is the fuel for data center operation. When GPUs run at full load, each 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 across the Pacific 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 just a second or two.

Electricity never leaves China’s grid, but its value is delivered across borders via 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 electrical services, yet they are almost invisible in official trade data.

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, Zhipu, MiniMax… over a dozen firms racing on the same track, prices have long fallen below reasonable profit margins. Loss-leading has become industry norm.

A closer look reveals this mirrors China’s manufacturing export strategy: leveraging supply chain advantages and industry involution to push token prices down aggressively.

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 a peculiar group of visitors.

These people rented abandoned factories, packed them with countless machines, and ran them 24/7. The machines produced nothing—except constantly solving a mathematical problem. Occasionally, from this endless math problem, they mined a Bitcoin.

This was the first form of electricity export: using cheap hydro and wind power, through mining rigs’ hashing computations, converting it into globally circulating digital assets, then cashing out on exchanges for USD.

Electricity itself crossed no borders, but its value, via Bitcoin, flowed into global markets.

In those years, China’s hash rate accounted for over 70% of global Bitcoin mining. China’s hydropower and coal power, through this circuitous route, participated in a global redistribution of capital.

By 2021, all this abruptly stopped. Regulatory crackdowns scattered miners, and hash power migrated to Kazakhstan, Texas, and Canada.

But the logic never disappeared; it only waited for a new shell. When ChatGPT emerged, large models became the new battlefield. Former Bitcoin mines transformed into AI data centers; mining rigs became GPUs; the Bitcoin mined turned into tokens. Only electricity remains unchanged.

Bitcoin’s offshore journey and token’s offshore journey are isomorphic at the core, but today, tokens 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 is being computed.” Computing power itself is non-productive, more like a trust mechanism byproduct.

Large model inference, however, 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 exponentially over time.

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

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 of the game.

Token export is similarly a war without declared combat, facing heavy resistance.

Data sovereignty is the first barrier. An API request from a US developer processed by a Chinese data center physically traverses China. For individual developers and small apps, this isn’t a problem. But for enterprise-sensitive data, financial info, government compliance scenarios, it’s a hard barrier. 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 only partially offset this disadvantage; the ceiling remains.

But these immediate obstacles are only the prologue. A larger battlefield is taking shape.

Tokens and AI models have become a new strategic arena between China and the US—comparable to the 20th-century semiconductor and internet wars, 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, pouring billions of dollars into space race dominance.

The logic of AI competition is eerily similar, but the intensity will far surpass the space race. Space is physical and intangible to most; AI infiltrates the economic capillaries—every line of code, every contract, every government decision system may be running a large model from a certain country. Whose model becomes the default infrastructure for global developers? Who gains structural influence over the global digital economy?

This is precisely what makes China’s token export strategy threaten Washington’s sense of security.

When a developer’s codebase, agent workflow, and product logic revolve around a Chinese model’s API, the switching cost grows exponentially over time. Even if the US legislates restrictions, developers will resist actively—just as today, no programmer would abandon GitHub.

Today’s token export is perhaps just the opening chapter 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 laid by engineers coding in Hangzhou, Beijing, Shanghai, and GPU clusters running day and night in some southern province.

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