China's three major telecom operators accelerate token business amid surging AI demand

As artificial intelligence permeates various industries, the commercialization of the token economy has drawn increasing attention.

Token Factories Enter Experimental Phase

The newly released China Token Factory Development White Paper (2026) (hereinafter referred to as the White Paper) indicates that token factories have moved beyond the concept incubation stage and entered a multi-track experimental phase encompassing project construction, capability procurement, and platform operations. However, from an industry perspective, the proportion of projects that have actually commenced production and operations remains low. The core challenge is also evolving: previously, the focus was on "whether computing power is available"; now, the question is "whether effective tokens with competitive pricing can be produced consistently and stably."

This shift is driven by the rapid growth in AI application scale. According to data from the National Data Administration (NDA), China's daily token calls stood at approximately 100 billion in early 2024, surged to 100 trillion by the end of 2025, and exceeded 140 trillion as of March 2026. Liu Liehong, Director of the NDA, previously stated that tokens are measurable, priceable, and tradable, serving as the "settlement unit" connecting technology supply and commercial demand. Meanwhile, data from the Ministry of Industry and Information Technology (MIIT) shows that as of the end of June 2026, China's intelligent computing power reached 2,185 EFLOPS, with an overall rack utilization rate of 71.4%.

From "Selling Resources" to "Selling Services"

According to the White Paper, a "token factory" is defined as an industrialized production system that "uses electricity as the energy input, GPU hours as the production process, tokens as the product, and unit effective task cost as the core metric." Notably, the emphasis is not on simply increasing token volume, but on producing "effective tokens."

Under this definition, only output tokens that simultaneously meet service-level requirements such as latency, availability, and accuracy—and are ultimately seen and used by end users—are considered effective tokens and eligible for commercial measurement.

Industry observers believe that the emergence of the "token factory" concept reflects a shift in the evaluation system for AI infrastructure. In the past, after a data center or intelligent computing center was built, investors primarily focused on server, GPU, and facility scale. However, in the inference stage, the true determinant of commercial value is whether these hardware assets can be utilized continuously, stably, and efficiently. This means AI infrastructure is gradually transitioning from selling "resources" to selling "services."

This trend aligns with the development stage of the computing power industry. MIIT data shows that as of June 2026, the national computing facility rack utilization rate was 71.4%, with intelligent computing power reaching 2,185 EFLOPS. Faced with growing computing supply, simply expanding hardware scale no longer automatically translates into economic value. Improving computing utilization, reducing unit inference costs, and converting computing power into stable AI services have become key priorities for the next phase of industry development.

At the inaugural Token Cloud Service Conference, the China Academy of Information and Communications Technology (CAICT) proposed that tokens are gradually becoming an important service unit connecting computing supply, large model capabilities, and industry applications. It called for further improvements in service architecture, resource scheduling, metering and billing, quality assurance, and security and trustworthiness standards. The national standard Artificial Intelligence Token Metering Framework and Testing Methods has also been initiated, with participation from organizations including the China Electronics Standardization Institute.

Wang Qinglin, Manager of the Ruihengda Industrial Research Institute, believes that the impact of token factories may not be limited to adding a new type of computing project. Instead, it is driving the industry to use multiple effective metrics to evaluate the return on investment (ROI) of AI infrastructure. For local governments, computing investors, and cloud service providers, this also means that the previous approach of "build first, find demand later" is being challenged. Whether a project can generate sustained orders will increasingly determine its investment returns.

Telecom Operators Race for the Token Gateway

While token factories remain in the experimental phase, telecom operators—who are also actively exploring token operations—have entered a period of rapid product and platform iteration.

According to a recent research report by Xia Maosen, a China research analyst at Omdia, when the three major telecom operators first launched token packages in May, prices generally ranged from 3 to 5 yuan per million tokens. By July, core package prices had dropped to approximately 1 yuan per million tokens, gradually approaching the levels of leading domestic cloud service providers. This round of price adjustments indicates that operators are quickly abandoning the strategy of profiting solely from token price margins and are instead seeking comprehensive value from networks, computing power, models, channels, and industry customer resources.

From a strategic perspective, the three operators have adopted different focuses:

• China Mobile emphasizes a platform-based approach. In June, it established a group-level Token Office responsible for integrating the entire process of "creating, delivering, and applying tokens." At the same time, China Mobile began combining tokens with traditional services such as 5G packages and offering multi-model capabilities to individual and enterprise users through an AI distribution platform. Xia Maosen believes that the significance of this move lies in unifying previously fragmented token business pilots at the group level, thereby reducing coordination costs between different business units.

• China Telecom places greater emphasis on productization. From its "From Bit to Token" value proposition to its Tianyi Cloud Token products and the Xingchen Token Hub, China Telecom is attempting to package tokens directly as standardized products for individuals, families, and enterprises. Currently, China Telecom offers a personal package of 9.9 yuan per month for 10 million tokens and an enterprise package of 299.9 yuan per month for 150 million tokens. Its Token Hub provides access to over 100 model options. This approach closely resembles the packaged, product-oriented operations of traditional telecom services.

• China Unicom focuses more on industries and scenarios. After implementing an organizational restructuring in July, China Unicom incorporated "strengthening token operations" into the responsibilities of its Product Innovation and Marketing Department. At its recent partner conference, China Unicom further proposed enhancing the full-chain capability of token "creation, storage, transfer, cleaning, and application" and fully opening its "Agent + Token + AI Cloud" operating system.

China Unicom Chairman Dong Xin publicly stated that the company aims to integrate computing supply, model calls, and scenario returns into a single "accounting book," driving the transition from "transporting traffic" to "supplying tokens," from "transmitting bits" to "empowering intelligence," and from "connectivity" to "productivity." China Unicom also launched Unicom Cloud 8.0, a trusted token infrastructure, and Unicom Yuanjing MaaS, among other achievements, seeking to upgrade tokens from a mere billing unit to a foundational service for industry clients.

More notably, China Unicom is addressing the long-standing "metering black box" in token commercialization. According to reports, China Unicom has introduced the "Yuanzhu Metering and Billing System" to standardize token measurement across different models, addressing issues such as inconsistent standards and difficulty in tracking usage. Unicom Cloud 8.0 further proposes a "six-coordination" framework involving computing-electricity, computing-network, computing-chip, computing-data, computing-model, and computing-security, targeting key scenarios such as government services, healthcare, education, finance, and state-owned enterprises.

The strategic moves of the three major operators indicate that tokens are no longer just a new service package for them. They are redefining the relationship between operators, the AI industry, and end users.

Omdia's assessment aligns with this logic: token services themselves are rapidly becoming commoditized. In the long run, the real opportunity for operators to build differentiated advantages lies not in simply "selling tokens," but in leveraging their existing capabilities—national networks, computing infrastructure, enterprise customer relationships, billing systems, and security—to become the AI infrastructure and delivery layer between models and end users. In other words, tokens may be just the gateway; the real prize is the AI service orchestration and industry customer service rights behind the tokens.

Three Hurdles to Mature Commercialization

The boom in AI development has provided a clear demand foundation for the token economy. More importantly, token consumption is expanding from C-end chat and Q&A to more complex industry scenarios such as enterprise office work, software development, and industrial production.

The MIIT has explicitly called for deepening "AI + Manufacturing," promoting the integration of large models into R&D, production, marketing, and operations management. This suggests that as enterprise AI applications gradually enter production systems, token demand is expected to shift from sporadic calls to sustained, stable industrial loads.

However, the path from rapid growth to mature commercialization for the token industry faces significant challenges:

1. Metering Standards: Although tokens inherently possess metering attributes, the computational cost and ultimate value of a token vary across different models, tasks, and context lengths. Wei Kai, Director of the CAICT AI Research Institute, previously noted that the industry should not focus solely on token unit prices. Standards for measuring "high-quality tokens" are needed. This aligns closely with the White Paper's emphasis on "effective tokens": future price competition will likely shift from "cost per million tokens" to "how many tokens and how much computing power are needed to complete a specific task, and what is the final outcome."

1. Cost and Profitability: Token factories are capital-intensive, requiring substantial upfront investment in hardware and infrastructure, but with relatively low marginal costs. Consequently, if utilization rates are insufficient, the unit cost of effective tokens can rise rapidly. The White Paper specifically notes that the utilization rate of a token factory has a greater impact on unit costs and project profitability than hardware procurement prices. The same hardware can yield significantly different profitability when handling different business loads. In other words, future computing projects will not only compete on "who builds bigger" but also on "who can keep the computing power fully utilized over the long term."

1. Value Realization: For enterprise clients, purchasing tokens is not the end goal. The true business outcome is reducing R&D costs, improving customer service efficiency, optimizing production processes, or enabling agents to complete tasks. Therefore, token operations may eventually evolve from "pay-per-call" to "pay-per-task, pay-per-outcome, or pay-per-service-level."

Huang Wei, Deputy Director of CAICT, publicly noted that tokens have, for the first time, given AI services a metering foundation similar to electricity or data traffic. However, moving from "meterable" to "tradable" and "scalable" still requires improvements in standards, service quality, and business rules.

Thus, in the near future, the token industry is likely to remain in a phase of "rapid growth" alongside "model experimentation." Token factories will address large-scale production; operators and cloud service providers will handle supply, scheduling, and delivery; and model and agent companies will continue to expand along the application value chain. As the various links in the industry chain gradually form unified metering standards, tokens may truly evolve from a mere number on a large model API bill into a fundamental commercial unit connecting computing power, data, models, and the physical economy.

(Source: China Business Network)