Author: Liu Honglin

Today I attended an exchange event about Web3 and AI at Fudan University. While chatting at the venue, a rather interesting question suddenly popped into my mind.

What exactly are these companies that provide large model APIs, such as Kimi and MiniMax, selling?

On the surface, they are selling model capabilities, such as question answering, generation, reasoning, search, and tool invocation. However, if we put aside these packaging terms and look only at the most basic business transactions, you will find something quite similar to Web3:

Each time you call a model, the system deducts a portion of your tokens.

At this point, when you look back at public chains, you will find that these two sets of things are, in fact, very similar.

In the Web3 world, one might say, "I made a transaction, consuming 0.01 ETH." In the AI world, another person might say, "I called a model, consuming 100,000 tokens."

The former sounds like language from the blockchain world, while the latter sounds like a billing method from cloud computing or SaaS products. But if we look deeper, what they are doing is actually quite alike:

They are both cutting a type of underlying resource into the smallest units that can be computed, consumed, and settled, and then selling these to developers and users.

From this perspective, I think many of the things AI companies are doing today are actually structurally similar to what many public chain projects were doing in the past.

They are both selling tokens.

Of course, the "tokens" here do not mean that AI companies have actually issued a coin that can be traded freely, listed on exchanges, or speculated upon, like public chain projects. That is not the point. What I mean is that they are both selling a standardized resource invocation unit.

01 Essentially Selling Invocation Rights

Using Kimi is not simply buying "an article" or "an answer." What you are buying is the model's capability to process text, the usage of context windows, the consumption of the reasoning process, and the frequency and volume of API calls. The platform just breaks down these originally abstract concepts into tokens and charges you based on consumption.

Similarly, when you do things on a public chain, you are not directly buying the words "transfer successful," but are actually paying for the resources consumed in completing an accounting, verification, sorting, or state update for the network. The on-chain world refers to this resource consumption measurement unit as gas, which you ultimately pay for using native tokens like ETH or SOL.

Therefore, AI companies and public chain projects are indeed very similar at a very fundamental level: they are not directly selling results, but rather "the right to invoke underlying computing resources."

02 Similar Appearance, Different Nature

However, if the article ended here, that would not be sufficient. Because while the tokens sold by AI companies and those sold by public chain projects may look alike, they are actually different things.

The core difference lies in the distinct rights structure behind them.

The tokens sold by AI companies are essentially a billing unit internal to the platform. You recharge, open an account, receive an API key, and then consume quotas according to the platform's rules. What you possess is not an asset that can circulate freely, transfer freely, or exist independently outside the platform; it is a type of usage right recognized by the platform.

What can you compare it to? It resembles in-game currency, or the invocation limits in a cloud vendor's backend, or the balance in a membership system. This has value, of course, because it can be exchanged for services; but its value boundaries, usage rules, and price adjustments are fundamentally controlled by the platform.

But public chain tokens are different. ETH, SOL, and similar tokens are not just measurement units within the system; they are also native assets within the network. They can be held, transferred, traded, staked, mortgaged, and can exist independently of any specific invocation action.

03 One is Platform Pricing, One is Network Pricing

Today, the pricing of AI company tokens is mainly determined by the company itself. Which model you invoke, how much you input, how much output you get, how much long context costs, and how much tool invocation costs are all predetermined by the platform. Whether users accept it or not, it is essentially the platform's pricing.

In contrast, the gas on public chains is not simply a set price tag set by the platform. On-chain fees are influenced by network congestion, market supply and demand, user bidding, and protocol mechanisms.

The billing logic of AI tokens is essentially enterprise pricing; the billing logic of public chain tokens is much closer to protocol and market pricing.

04 AI Teaches Web3 a Lesson

The most valuable aspect of this observation is not that "AI is very similar to Web3," but rather that it can help us re-understand an old issue: why do many Web3 projects ultimately fail, while the token billing of AI companies seems naturally reasonable to everyone?

The reason is simple.

Because AI company tokens have very clear resource objects behind them, as well as very clear reasons for payment.

When you use a model, you are genuinely consuming computing power. Running long context truly occupies window resources. Conducting searches or invoking tools genuinely increases the platform's costs. With each additional invocation, the platform bears a portion of the marginal cost.

Therefore, when the platform breaks down this consumption into tokens and charges based on tokens, the logic is quite smooth. Users can easily understand: the money they spend corresponds to the resources they actually consume.

But the problem with many past Web3 projects does not lie in calling it a token; it lies in the fact that behind it, there isn't actually such a strong real consumption scenario. Many projects, when discussing their business model, focus not on why users would continue to use or keep paying, but rather on "how to make tokens work."

05 Establish Use Cases Before Discussing Tokens

I believe the biggest inspiration that AI companies can provide to Web3 entrepreneurs may be here.

First, clarify: who is the user actually paying for?

Then establish: why would users continue to pay?

And then, check if there really exists a resource consumption that can be segmented, measured, and settled within this business.

Instead of starting by asking, how to issue tokens, how to get listed, and how to manage market value.

06 Not Everything Is Worth Going on Chain

Not everything is worth going on chain. Because many businesses are inherently more efficient on centralized platforms, with clearer contractual relationships, and there is no need to force them into an on-chain structure.

Not every measurement unit is worth trading. Because many measurement units are suitable only as internal settlement tools; once freely traded in the market, they may distort the original usage logic.

Many times, the best token is not the one that spikes the most but the one that does not require you to constantly watch its price yet can continuously be consumed, settled, and repurchased in real business.

07 Conclusion

So returning to today's topic: "AI Companies Haven't Issued Tokens, but They Are All Fiercely Selling Tokens."

What AI companies sell is not a coin in the sense of the cryptocurrency sphere. What they sell is a token that has been corporatized, productized, and contracted.

The Web3 world should not just sell a coin that can rise and fall. Its truly valuable part should be the original pricing ability for a certain resource, network capability, or state change right.

So let’s not always think about issuing coins. First, clarify what you are actually selling.

Are you selling a story or resources?

Are you selling imagination or invocation rights?

Are you selling a financial illusion or a real underlying capability that can be continuously consumed, continuously priced, and continuously repurchased?

This may be the most valuable reminder AI brings to Web3.

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