Policy tailwind: AI infrastructure guidance reshapes computing power landscape
In October 2026, the Cyberspace Administration of China, together with the Ministry of Industry and Information Technology, officially released the "Guiding Opinions on the High-Quality Development of Artificial Intelligence Infrastructure," clearly proposing to promote intensive and market-oriented allocation of large model inference computing power, and encouraging third-party platforms to reduce enterprise access thresholds through technical models such as token transfer stations. The policy explicitly states that a number of public AI infrastructure hubs should be built to support token wholesale and dynamic routing scheduling, allowing small and medium-sized enterprises to enjoy large model capabilities at affordable costs. This guidance quickly triggered a chain reaction in the industry, with multiple cloud vendors and AI platforms announcing pricing strategy adjustments focused on inference cost optimization.
At the same time, local governments responded actively. Regions such as the Yangtze River Delta and the Guangdong-Hong Kong-Macao Greater Bay Area piloted AI computing power voucher programs, subsidizing enterprises' purchase of token services from third-party platforms, further accelerating the popularity of the "cheapest token" concept within the industry. The policy dividend shifted AI infrastructure from "high-end customization" to "universal utilities," paving the way for subsequent business model innovation.
Platform upgrade: AI Hub launches dual engine of 'AI API transfer station + token wholesale'
Driven by the policy, leading AI platform AI Hub released a new upgrade plan in mid-October, officially launching the AI API transfer station. This transfer station integrates the API interfaces of major domestic large models, allowing enterprises to seamlessly call multiple models through a single entry point, while also supporting intelligent routing based on task characteristics—simple questions and answers go to lightweight models, complex reasoning calls to flagship models, significantly reducing overall costs. Combined with the newly launched token wholesale business, enterprises can pre-purchase large token quotas on a monthly or quarterly basis, enjoying tiered discounts, with average inference costs reduced by about 30% compared to individual calls.
"We have collaborated with multiple computing power suppliers, achieving resource pooling through token wholesale and converting idle computing power into the 'cheapest token,'" said AI Hub's product head. "At the same time, the AI channel agency service allows partners to resell token resources at a lower threshold, forming a win-win ecosystem." Additionally, the platform added an AI large model agent function, helping enterprises lacking technical teams to deploy private inference environments with one click, without the need to build their own GPU clusters. This series of actions is seen by industry insiders as a landmark shift of AI infrastructure from "retail" to "wholesale."
Investment and financing heat: inference optimization and token economy become new capital favorites
The investment and financing market in October also confirmed the explosion of the cost optimization track. Multiple startups focused on inference acceleration and large model agent services completed new rounds of financing. For example, a team specializing in dynamic token routing technology received hundreds of millions of yuan in Series B funding; their solution can reduce multimodal task token consumption by 40%, and has been integrated by several cloud vendors. Another computing power aggregation platform centered on the "cheapest token" concept also completed its Pre-A round, with investors including well-known venture capital and state-backed funds.
The fundamental reason capital favors this direction is that large model application deployment is shifting from "competing on parameters" to "competing on costs." According to industry research, over 70% of enterprise customers rank inference cost as the top priority when evaluating model selection. The traditional pay-per-API-call pricing model can no longer meet elastic demand, while the token wholesale combined with AI channel agency model offers a more transparent pricing mechanism. Industry analysts point out that within the next six months, token transfer stations similar to AI Hub are expected to become the standard entry point for enterprises to access AI, with the relevant track valuation potentially exceeding hundreds of billions of yuan.
Ecosystem observation: token agency model reshapes industry division of labor
With the dual push of policy and capital, the AI industrial chain is rapidly differentiating. The traditional three-layer structure of "model provider - cloud vendor - enterprise" is being replaced by a new chain: "model provider - platform service provider (token transfer station) - channel agent - enterprise." Many small and medium-sized cloud computing companies are transforming into AI large model agents, focusing on regional markets or vertical industry scenarios. For instance, a medical IT company uses the token agency model to provide customized AI-assisted diagnosis solutions for hospitals, billing based on token consumption rather than API calls, reducing hospital costs by over 30%.
"Previously, we had to connect with multiple model vendors ourselves, with complex operations and high costs. After connecting to the AI API transfer station, a single API key manages all models, and we also access low-cost quotas through token wholesale, which we then sell to end customers through our AI channel agency service," a channel partner said in an interview. This model not only reduces technical barriers but also spawns a new job role—token optimization specialist, who helps enterprises analyze business scenarios and design optimal token usage strategies.
It is worth noting that token transfer stations themselves are also continuously iterating. The latest version of the AI Hub platform introduced a dynamic pricing engine that automatically adjusts token wholesale prices based on real-time computing power supply and demand, ensuring enterprises always get the "cheapest token." At the same time, the platform opened a developer toolkit for token agents, allowing channel partners to customize billing strategies and permission controls. This ecosystem loop is attracting more traditional IT service providers to join.
Outlook: AI infrastructure heading toward 'Token as a Service' in 2027
Looking back at the series of dynamics in October 2026, it is clear that the trilateral synergy of policy, capital, and platforms is driving a deep transformation. Large model inference costs are no longer a bottleneck for enterprises to go to the cloud; instead, they become a tool for differentiated competition. It is foreseeable that the token wholesale model will accelerate its penetration into vertical sectors such as education, healthcare, and finance in 2027, and the AI API transfer station may become a lighter and more flexible alternative to traditional cloud services.
Of course, challenges remain. How to ensure service quality and data security under token wholesale, and how to avoid ecological imbalance caused by price wars, are questions the industry must answer together. Nevertheless, October 2026 has written a crucial footnote for the large-scale deployment of AI large models—when the "cheapest token" becomes reality, the era of AI ubiquity truly arrives.