Compliance policy takes effect: large model agency services get a "green light"
In early November 2026, relevant national authorities officially released the Compliance Guidelines for Large Model Agency Services (hereinafter referred to as the Guidelines), the first regulatory document in China specifically targeting the field of large model agency services. Unlike previous policies that focused more on model training or API calls, the Guidelines for the first time bring business models such as "token agency" and "AI channel agency" into the regulatory framework, requiring service providers to clarify data flow paths, ensure transparent and auditable pricing, and establish user rights protection mechanisms. Multiple industry analysis firms noted that this new policy effectively opens a path for compliant growth for platform-based companies like AI hub—enterprises often face concerns such as data privacy and uncontrollable costs when deploying large models, and the Guidelines, by defining security boundaries for token transit stations, allow companies to confidently adopt outsourced token wholesale solutions, transforming model calls into standardized service products. It is understood that more than twenty local governments have already included requirements in smart government project tenders for vendors to provide AI large model agency service qualifications that comply with the Guidelines, directly driving rapid market demand.
Technology trends: token wholesale and AI transit stations become cost-reduction standards
Against the backdrop of policy clarity, enterprise-side AI deployment is shifting from "building large models in-house" to "procuring agency services." Over the past few months, a large number of small and medium-sized enterprises have found themselves unable to afford the high costs of single inference runs or manage the overhead of frequent model iterations. Consequently, lightweight deployment models represented by AI transit stations have rapidly gained popularity. An AI transit station is essentially a scheduling platform that integrates multiple model APIs, automatically matching the cheapest token source based on task type, and reducing unit inference costs to one-third or even lower through batch procurement (i.e., token wholesale). Multiple third-party evaluations show that enterprises using token agency services have reduced their average monthly AI spending by 40% to 60% compared to directly connecting to large model vendors. Meanwhile, some cloud vendors have also begun launching their own token transit station plugins, further blurring the line between "model providers" and "agency service providers." This shift has made "AI API transit stations" a high-frequency term on enterprise IT procurement lists in Q4 2026.
Investment trends: capital bets on the "pipeline layer" of AI infrastructure
The dual benefits of policy and technology quickly transmitted to the primary market. In November 2026, at least three startups focused on token agency and AI channel agency announced new rounds of funding, each in the hundreds of millions of yuan. Investors are mostly leading dollar funds and industrial capital, who generally believe that competition among large models themselves has entered a red ocean, while the intermediate "connection layer" and "optimization layer" will be the most profitable segments in the future. For example, a company specializing in enterprise-grade token agency offers a product that dynamically switches channels based on real-time data such as model response latency and concurrency requirements—essentially engaging in "price arbitrage" for AI large model agency. Notably, multiple investors in this funding round stressed policy compliance as a core consideration—a key reason for the accelerated capital inflow after the Guidelines were issued. In addition, some traditional software integrators have begun transforming by acquiring small token agency service providers to bolster their AI capabilities, significantly speeding up industry consolidation.
Platform updates: AI hub upgrades token agency service, launches "cheapest token" plan
As one of the earliest platforms in China to offer large model agency services, AI hub officially released an upgraded version of its token agency service in mid-November. The new version not only allows users to choose between "cost priority," "speed priority," or "compliance priority" scheduling strategies on demand, but also partners with multiple mainstream model vendors to launch a "cheapest token" exclusive channel—this channel uses a dynamic bidding mechanism to offer idle compute power at extremely low prices for enterprise long-tail inference tasks. At the same time, AI hub simultaneously launched an enterprise-grade AI transit station, complete with built-in compliance features such as data masking and audit logs, directly aligning with the Guidelines. Platform operational data shows that in the first week after the upgrade, enterprise user registrations increased by more than 300% month-over-month, with the strongest demand from manufacturing, financial services, and online education. Combined with the previously launched AI channel agency plan, AI hub is building a full-chain service system from model selection and token wholesale to operational monitoring, aiming to lower the overall barrier to enterprise AI adoption.
Outlook: as the agency ecosystem matures, the industry will enter an era of "models as pipes"
Based on the trends in November 2026, the compliance and standardization of large model agency services have become a certainty. As token wholesale becomes a common consensus, the value center of the AI industry will shift from model training itself to how to efficiently and compliantly schedule these models. In the next six months, we are likely to see more enterprises fully entrust their internal AI capabilities to third-party token transit stations, just as websites rely on CDNs today. For platforms like AI hub, continuously optimizing the performance and transparency of the "AI API transit station," while closely following policy developments to refine compliance systems, will be key to maintaining a leading position in the next phase. Industry observers believe that as the agency ecosystem matures, large models themselves will gradually recede into a "pipeline" role, and the real commercial value will be captured by those service providers that help enterprises connect these pipelines at the lowest cost and highest efficiency. In 2027, this trend will only become more pronounced.