From 5 Mao per kWh of Chinese electricity to a $45 API export: Tokens are rewriting currency units

Original Title: "From $0.05 per kWh Chinese Electricity to $45 API Export Package: Token is Becoming a New Currency Unit"

Original Author: Wenser, Odaily Star Daily

In 1858, the first transatlantic telegraph cable connected Europe and America. From that moment on, the supreme power of information no longer belonged only to broadcast, newspapers, and other media, but also to that invisible undersea cable. Whoever laid the cable had priority over the flow of information; whoever controlled the transmission had the right to interpret price and order.

Today, 168 years later, although the forms of media are vastly different, this logic still holds.

Today, what crosses undersea fiber optic cables is no longer just telegraph and telephone signals, but API requests, model calls, inference results, and machine payments. The new issue is no longer "can the information get through," but "how value can flow natively between AI Agents." And in this process, Token is beginning to assume an unprecedented role: it is both a unit of computation in the AI world and a means of payment in the crypto world.

Many people may have first realized this change because of OpenClaw. This "lobster" allowed the market to intuitively feel for the first time: AI is no longer just a conversational tool but is beginning to take over executive rights—it will read files, call interfaces, run workflows, manage tasks, invoke plugins, and even consume tokens far beyond chatbots. In the past, Token was merely a number on a bill in the world of large models; now, it is increasingly resembling the fuel swallowed by AI Agents in operation.

At the same time, in the on-chain world, Token is no longer just a symbol in speculative narratives. As protocols like x402, ERC-8183 step into the spotlight, Token is being redefined as a payment currency and business interface that AI Agents can directly understand, directly call, and directly settle between.

Thus, a clearer reality is emerging: Token is transitioning from a "technical term" to a "unit of measurement," from a "unit of measurement" to a "transaction currency," and further from a "transaction currency" to the future "smallest unit of the machine economy."

The Dual Nature of Token is Synthesizing a Puzzle

When we used to talk about Token, we defaulted to talking about Token in cryptocurrencies. It represents assets, rights, liquidity, governance, valuation anchors, and also represents a project's on-chain existence. It is the basic unit of the crypto narrative; but in the AI context, Token has never been an asset but a consumption.

It is the basic semantic unit of a piece of text after being segmented by a model, serving as the lowest billing unit when the model reads, understands, reasons, or generates text. When developers call the API, they are essentially not buying an "answer" but buying a "tokenized amount that has been reasoned through."

These two sets of definitions were originally parallel. One was responsible for describing cost, the other for carrying value; one resided on the cloud bill, the other in the wallet; one belonged to the model platform, the other to the blockchain network.

But now, they are starting to intersect. As AI increasingly converts real-world resources into token-based services, and Crypto has always been adept at encapsulating real-world relationships into token-settled transactions, when the agent becomes the new actor, the interface between these two systems naturally opens up. If the past internet was separated into the "Content Internet" and the "Payment Internet," then today's Agent Internet is combining "call" and "payment" into a single action. AI requests an API and simultaneously makes a payment; calls a piece of data and simultaneously settles; purchases an ability and simultaneously completes on-chain verification. This is precisely the significance of protocols like x402.

Traditional API payments in the past relied on accounts, subscriptions, keys, permission systems, and manual provisioning. x402 attempts to compress these heavy processes into a protocol action more suitable for machines. Machines do not need to get a card, open an account, or go through KYC processes to access resources; they only need to understand "you need to pay" when a request fails, and then make the payment. That is why it is said that the fiat system is designed for humans, while tokens are becoming machine-designed currency.

Token Going Global is Essentially the Invisible Globalization of Chinese Electricity and Computing Power

Recently, the market has been fond of discussing "Token Going Global." Why has this term suddenly become popular? Because it appears to be a new term in the AI context, but behind it is actually a very old, very solid, and very Chinese matter: electricity, computing power, and infrastructure.

According to data released by the National Energy Administration, by 2025, China's total electricity consumption will reach 10.3682 trillion kilowatt-hours, an increase of 5.0% year-on-year, surpassing 10 trillion kilowatt-hours for the first time. This number is not "large" in the general sense but historically "large." The National Development and Reform Commission even directly stated in a reposted analysis that China has become the world's first single country with an annual electricity consumption exceeding 10 trillion kilowatt-hours.

During the same period, the national installed electricity generation capacity reached 3.89 billion kilowatts, with the continuous rise of new energy installation such as wind power and photovoltaics. More importantly, information transmission, software and information technology services, as well as new infrastructure like data centers and computing power hubs, are becoming significant sources of additional electricity consumption. Official reposted materials mention that computing power hubs such as the Gui'an New Area have shown a very significant increase in computing power demand and electricity consumption.

This means that China is forming a new resource closed-loop: electricity enters data centers; data centers drive GPUs; GPUs perform inference tasks; the inference results are delivered globally through the network; and finally, pricing and payment are completed at scale using Tokens.

Electricity has not gone overseas, but the value of electricity has. This is exactly where the term "Tokenization Going Global" truly resonates. Unlike exporting cars, batteries, or solar panels, which have a clear logistics chain, or traditional software outsourcing centered around labor, this is more like an exported resource that has been compressed and abstracted: what you are consuming is China's domestic electricity and computing power, but the bill is paid by global developers. In other words, China is transforming electricity and computing power into globally purchasable digital services through Tokens as an intermediary.

This narrative is not purely conceptual. According to publicly available information from the OpenRouter ranking, Chinese models have consistently held top positions in many categories. Among them, Chinese models such as Minimax M2.5, Deepseek V3.2, Kimi K2.5 0127, Step 3.5 Flash are at the top of the platform. Additionally, in its global Token billing region, China accounts for approximately 6.01%, indicating that a large portion of calls to these models come from overseas regions.

More tangible data comes from the OpenRouter's official research report "State of AI 2025": within 2025, Chinese open-source models have rapidly risen from a low base, approaching close to 30% total usage share in some weekly windows, with an annual average of around 13%. This is not about "dominating the world," but it is sufficient to illustrate that Chinese models are entering the global developer workflow. In other words, the so-called Tokenization Going Global is not just "a buzzword"; it signifies that China's advantages in electricity, computing facilities, model engineering, and cloud service capabilities are being consumed by global developers through Tokens.

OpenClaw Turns Tokens from Consumables into Production Inputs

Without an Agent, this would not have escalated so quickly. In the past era of large models, Tokens were more like "airtime." The more you interact with the model, the more Tokens you use; the longer you write, the larger the context, and the more complex the output, the higher the cost. But it still primarily revolved around "human-computer dialogues."

The significance of OpenClaw lies in enabling people to see, on a large scale for the first time, a different mode: AI is no longer just a conversational partner, but an actor. It doesn't reply to you with a sentence, but carries out a task for you; it doesn't generate a response, but continuously executes a task. Once AI transitions from chat mode to task mode, the function of Token consumption changes completely.

A chatbot consumes "Q&A Tokens," whereas an Agent consumes "Execution Tokens." The latter decomposes tasks, calls tools, reads the environment, performs parallel reasoning, iterates through trial and error, naturally consuming orders of magnitude more than the former. In the Agent scenario, daily user Token consumption could escalate from the millions to even higher levels.

For Chinese models, this is a rare opportunity. Because once Tokens become a means of production, the price difference is no longer a matter of "slightly more expensive," but a question of whether the entire workflow can be sustainable. Previously, developers only chatted with the model, and they could bear a slightly higher cost; now, as the Agent continues burning Tokens, if the model price difference widens by an order of magnitude, the workflow will automatically migrate.

In the past, the "subscription fee" for Tokens was like a fixed monthly deduction; now, Tokens have become the core fuel supporting the operation of the AI system.

AI Agent Doesn't Just Spend Money, It Can Also Generate Revenue by Itself

What's even more interesting is that the AI Agent not only burns Tokens now but is even starting to approach "earning money by itself." In a previously published article on "After AI Mistakenly 'Tipped' $260,000, It Earned It Back Within 24 Hours", we can clearly see—an AI Agent is transitioning from the consumption side to the production side.

The Lobstar Wilde case mentioned in the article is essentially a very surreal scenario in the crypto world: an AI Agent mistakenly transferred a large amount of tokens, and due to subsequent topic diffusion, meme remixes, and fee rebates, almost completed a "recovery" in a short period of time. Another more extreme case is the AI RAME in training attempting to use computing power for mining and establish a covert channel. These cases may not necessarily indicate any "conscious awakening," but they are sufficient to illustrate another more realistic fact: When AI possesses a wallet, permissions, interfaces, an environment, and the ability to operate continuously, it will naturally become more involved in economic activities.

It may not actively "want to make money," but it will learn what actions can bring more resources, more API calls, more balance, more permissions. And this is precisely the primitive form of economic behavior.

For Crypto, this is almost a natural fit. Because on-chain economics inherently allow for borderless accounts, programmable custody, automatic settlements, microtransactions, high-frequency interactions, and public ledgers. Many things that require institutions, banks, and contractual text in human society can be compressed into a wallet address and a piece of protocol logic on-chain.

So Crypto will not be marginalized in the AI era, but will instead become irreplaceable in another form. Not because of memes, and certainly not because of speculation, but because: AI Agents need a settlement layer that does not require manual onboarding, traditional payment gateways, and can natively access programs and protocols.

x402 Gave an AI Wallet, ERC-8183 Gave an AI Contract

If the significance of x402 is to enable machines to "spend" for the first time, then the significance of ERC-8183 is to enable machines to start "doing business." According to the Ethereum official EIP page, ERC-8183 is currently a Draft status standard proposal, with the full name "Agentic Commerce" and subtitle "Job escrow with evaluator attestation for agent commerce."

What it truly aims to address is very straightforward: a transfer is not commerce. A regular token transfer can only prove that money went from A to B, but it cannot prove that B delivered the work as requested, let alone prove that the delivery was reliably assessed. If agents want to establish a genuine business relationship, they need a more contract-like process: lock funds, execute, submit, evaluate, and then automatically release or refund.

This is exactly what ERC-8183 is trying to establish. Some summaries of the proposal offer a more colloquial description: the Client locks funds, the Provider completes the work, the Evaluator confirms the results, and finally, an on-chain escrow contract automatically releases or refunds. When such mechanisms are combined with the reputation and identity layer of ERC-8004, they can theoretically form a "discover-trade-reputation" positive feedback loop.

Looking at x402 and ERC-8183 together, it becomes clear that their roles are actually very distinct: x402 tackles "how to pay"; ERC-8183 tackles "how to do business"; one provides a machine wallet, the other provides a machine contract.

At this point, the Token in AI and the Token in Crypto are actually becoming increasingly difficult to distinguish. This is because in the world of Agents, Compute Tokens and Payment Tokens will more and more frequently appear in the same chain: one end being model inference, the other end being on-chain settlement, with protocolized business actions in between.

In such a system, a Token is not just a unit of cost or a unit of payment, but a unified permission in the machine economy.

The essence of a Token is not "model capabilities" but "resource decompression power"

Many people understand this narrative as "China's models are cheap, so they won." That's not wrong, but it only gets half of it right. The deeper logic is: What China truly exports is not a specific model, but compressing electricity, compute power, engineering capabilities, model supply, and cloud infrastructure into Tokenized service technologies consumable globally. This is a new form of resource compression power.

In traditional trade, electricity is hard to cross borders directly, and compute power is not easily globally purchasable like regular goods. However, once it is compressed into a Token callable unit, connected to APIs and protocols, it can flow over the internet like water. This is very similar to the logic of past Chinese manufacturing, except the export targets have changed.

In the past, exports were garments, household appliances, lithium batteries, and photovoltaic components; now exports are reasoning capabilities billed by Token, model services priced by call, and Agent execution settled by request. Visible shipping containers are decreasing, while invisible Token flows are increasing. Therefore, the true inspiration of Token globalization is not "which model is cheaper," but rather: who can compress resources into Tokens more efficiently is closer to the pricing power in the next-generation economic system. This is why "Tokens are becoming a new unit of currency" is not just a figure of speech.

AI is devouring everything, and Crypto is its settlement organ

The surge of OpenClaw is essentially not just a viral tool phenomenon but a sign of the times. It indicates that the role of AI is upgrading: from "being able to speak" to "being able to act"; from "answering questions" to "replacing operations"; from "a chat window" to "a continuously executing entity of action." And as AI advances, the consumption of Tokens rises; with each workstream it devours, it spawns a new payment and settlement demand.

The fiat currency system can address some of them, but cannot be machine-native; The Crypto system is not perfect, but it at least inherently understands these issues. So, instead of saying that Crypto is chasing AI, it is more accurate to say that AI is in turn compelling Crypto to undergo an upgrade from a "financial narrative" to "machine infrastructure."

The process of AI engulfing the world requires a stomach that carries everything, as well as a wallet to fill that stomach. The former is computing power, and the latter is Token.

Epilogue: The future world will not have only one type of currency, but Token may become the underlying currency unit.

Of course, it is still too early to say that Token will become the "sole currency unit" today. Fiat currency will not disappear, banks will not disappear, taxes, wages, sovereign credit, and regulatory frameworks will not suddenly become ineffective. The real economy will always be a multi-layered structure. But another trend is becoming increasingly hard to ignore: many key value activities in the future will first be represented as a Token and then converted into other currencies.

What does this mean? It means that Tokens may not necessarily replace fiat currency, but they are highly likely to first occupy the underlying level in the new economic system — becoming the accounting language for machine payments, the settlement interface for Agent businesses, the pricing benchmark for computing power services, and the general yardstick for digital assets. In this sense, the rise of Tokens is not a victory for the crypto market or AI companies, but rather the formation of a new economic coordinate system.

The future may not be "everything on the chain," but it is likely to be "everything first tokenized and then traded." By that time, the real minting power will not just be the power to issue currency, but the ability to efficiently compress resources into Tokens. This is where the phrase "Token is becoming a new currency unit" should be most seriously taken.

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