Over the past six months, the cloud computing sector has been singularly focused on one theme: the proliferation of Tokens.

Nearly all major cloud service providers have embraced Token-based billing for their AI services, rapidly phasing out traditional CPU and memory leasing models that relied on time-based billing. The cloud industry has suddenly become all about Tokens.

Following the blockbuster success of Seedance 2.0, ByteDance's average daily Token consumption in the video model market has soared to 80% of the entire market share. Tokens are flying off the shelves.

In March of this year, Alibaba unveiled the Alibaba Token Hub (ATH) business group, directly overseen by CEO Wu Yongming, with a strategic vision to "create, deliver, and apply Tokens." To support this vision, Alibaba Cloud even implemented a Token-value-centric sales assessment system.

While internet cloud providers are enthusiastically embracing Tokens, new cloud computing players, particularly telecom operators, are not content to play second fiddle. In May, China Mobile officially launched its Token operation ecosystem at the 2026 Mobile Cloud Summit, forming the Token Operation Ecosystem Alliance with ecosystem partners.

At this juncture, it's clear that in 2026, Tokens will dominate discussions at every cloud computing-related conference and event. The cloud landscape is awash with Tokens.

But is selling Tokens really that straightforward? Is the widespread adoption of the Token economy driven by genuine demand, or is it merely wishful thinking on the part of cloud providers?

I'd like to offer a different perspective on this Token-infused cloud phenomenon.

The primary advantage of Token-based billing lies in its alignment with the flexible usage patterns of AI. It allows users to pay only for what they consume, making AI calls more cost-effective for small and medium-sized developers.

However, most things in life have two sides. What benefits small and medium-sized developers may not necessarily be advantageous for large enterprises.

Large government and enterprise users have substantial AI call demands, often resulting in astronomical Token consumption. For them, Token-based billing may not be cost-effective and poses a significant challenge: budgeting becomes nearly impossible.

Token fees are essentially a form of IT expenditure, and for large enterprises, IT spending is characterized by fixed costs, advance planning, and strict budgeting.

Many IT department roles are dedicated to budgeting and cost control. However, with Token-based billing, IT spending becomes highly variable and difficult to manage. If the business department decides to embark on a challenging project on a whim, the Token bill could skyrocket overnight, potentially exhausting the IT department's annual cloud service budget in a single night.

To facilitate enterprise AI usage, IT departments may plead and coordinate with all parties to increase the budget. However, the following month may see a sharp decline in Token consumption, leaving the increased budget idle. This raises questions about how future AI budgets should be set, or even if they should be set at all. Who should ultimately bear the cost of AI—the IT department or the business department? After heated debates, the likely conclusion is that public cloud + AI is not yet mature, and on-premises deployment may be preferable.

No one can accurately predict costs in advance, not only because Token triggers are unpredictable but also because cloud providers' discount models are often manipulative.

Token prices are dictated by leading cloud providers and large model companies, resulting in highly volatile pricing. The usual tactic is a price war, where cloud providers aggressively slash Token prices to attract users. Once users are hooked, the discounts are withdrawn, and subsidies are reduced, leaving enterprises with exorbitant Token bills. This year, we've already witnessed many popular models experience price hikes of tens or even hundreds of times per thousand Tokens.

Small businesses may fare better, as they can be flexible and stop using Tokens when prices rise. However, large enterprises face significant business inertia and high validation costs, often left to suffer in silence when cloud providers manipulate prices.

For over a decade, cloud computing has been seen as more accessible to small businesses and less attractive to large enterprises. The focus on the Token economy has only exacerbated this issue. Large enterprises are hesitant to adopt AI that renders their budgets meaningless.

If the cancellation of discounts and subsequent price hikes represent the billing black box of the Token-based model, then in actual usage, enterprises will discover that this new model is riddled with layers of complexity. While the Token economy is still in its infancy, the opacity surrounding Tokens created by cloud providers is already evident.

Traditional cloud service billing models, such as charging by rental time or the number of servers rented, are relatively straightforward, akin to a flat-rate charter service. However, Token-based billing resembles a taxi meter, seemingly charging by distance but leaving passengers unaware of whether the driver is taking a detour or if the meter is jumping every 800 meters instead of every kilometer.

Many enterprises report that cloud providers' Token deductions generally exceed their estimated usage. This phenomenon is particularly evident when purchasing AI relay services, where systems may inflate call volumes, lack usage caps, and encourage users to consume more Tokens.

Beyond inflated calls, the Token model may also involve misrepresentation. Many enterprise users find that the APIs they purchase cannot pass official model authentication, likely due to the substitution of expensive closed-source models with fine-tuned open-source models.

Another tactic is for cloud providers to offer customers "value-added services," such as Agent frameworks and model instances, at bargain prices, essentially giving them away. Initially, enterprises may feel cared for, only to discover later that these services are designed to lock them in. Once adapted, switching to other cloud services incurs significant costs. If an enterprise's AI architecture becomes deeply reliant on a single cloud provider's ecosystem, it can be exploited in conjunction with Token price hikes, allowing the cloud provider to maximize profits.

Even if an enterprise resolutely migrates to another cloud ecosystem, the problems persist. They find that API specifications, Token billing models, and model ecosystem tools vary significantly across cloud providers. Enterprises must start from scratch, learning and adapting, only to encounter another layer of complexity from a different cloud provider.

The lack of industry standardization is the root cause of all Token-related opacity.

Who invented this little Token thing? It may be small, but it's got plenty of tricks.

For enterprise users, accessing large models on public clouds presents an inherent challenge: security.

The Token economy has risen too quickly, and cloud providers' ambitions have blinded them to security considerations. Compared to traditional IT or software services, enterprise large models are inherently insecure scenarios. Accessing large models on the cloud means enterprises must send all relevant information to the cloud, where cloud providers can see all user requests and responses. As Tokens circulate, all sensitive enterprise information is transferred en masse.

Is there a solution to this problem? At least currently, no cloud provider has offered a technically convincing solution. Instead, they emphasize their institutional oversight and corporate ethics. Friends, this is the cutthroat battlefield of cloud services. Believing in their moral compass requires some evidence of past achievements, doesn't it?

While Tokens leak enterprise information, users may also face a series of security-related issues. For example, can service continuity be guaranteed? How can timely operational support be ensured under Token-based billing? How can large models be adapted to enterprises' stringent production environments?

These security risks remain unresolved at this stage. The Token + cloud craze is essentially in a state of wild growth and disorderly expansion.

Let's shift our focus to cloud providers. The cloud computing sector witnesses new trends every year, but few manage to turn a profit. Each new trend forces cloud providers to reshape their business landscapes and organizational structures, but they're used to it by now.

The key question with the Token economy is whether it can differ from past AI trends and enable cloud providers to actually make money.

It's hard to say at this point. High-quality, even monopolistic models, have seen strong commercial feedback so far. However, it's also true that most cloud providers continue to invest in and incur losses from Token economies and related large models and Agent businesses.

The fiercely competitive cloud computing landscape means that every commercially viable niche model sector faces intense competition. When competition becomes too fierce, cloud providers typically slash Token prices, leading to another overall decline in cloud computing revenue. At that point, the Token economy shifts from a lucrative opportunity to a barely palatable option. This cycle repeats endlessly.

The underlying logic that undermines the Token economy's potential is that Tokens need to help cloud providers' users make money. However, the nature of this billing model is that as enterprise revenues and user numbers increase, Token consumption rises accordingly. This means that enterprises developing AI applications and scenarios may end up working for cloud providers. This is a difficult business model to sustain.

But it doesn't matter; new trends will emerge after technological upgrades. Last year, it was selling SaaS; this year, it's selling Tokens. As the song goes, "I've done everything to make money."

Ultimately, cloud providers aim to sell fixed model and infrastructure costs at high margins and with decreasing marginal costs. At this stage, the Token economy represents an economically viable trend with substantial average order values and profit margins. The rush to capitalize on this opportunity is undeniable.

The issue lies in the fact that the Token economy craze has inadvertently created a chaotic, wild west-like environment. Non-standardized industry rules, endless billing tricks, and unresolved security risks allow cloud providers to exploit users' pursuit of AI and hot trends to quickly recoup costs. However, this business model is ultimately unsustainable, akin to killing the goose that lays the golden eggs.

These issues require resolution and should not be allowed to fester, leaving customers increasingly dissatisfied. Cloud providers have no retreat. AI was once considered cloud computing's second front, but now it has become the primary, perhaps even the sole, battleground.

This battlefield demands not only cheap Tokens and Token-centric strategies but also more powerful models, enterprise-friendly technologies, commercial credibility, and corporate responsibility.

The future of Tokens lies in the cloud computing industry; the answers about Tokens are still drifting in the wind.