1. Favorable policies blow in, large model industry enters the fast lane
In October 2026, the National Development and Reform Commission and the Ministry of Industry and Information Technology jointly issued the "Guiding Opinions on Promoting Large-Scale Application of Artificial Intelligence Large Models," explicitly encouraging the establishment of third-party model aggregation platforms, promoting API interface standardization, and providing tax incentives for enterprises adopting the token wholesale model. This policy directly stimulated a wave of investment in smart computing centers and AI industrial parks across regions. According to incomplete statistics from industry associations, in the first three weeks of October alone, domestic large model-related investment and financing events exceeded 40, involving over 15 billion yuan, with 90% flowing to startups with vertical industry deployment capabilities. Multiple local governments simultaneously launched "AI computing vouchers," allowing enterprises to receive subsidies of up to 30% when calling models through aggregation platforms such as AI中转站, pushing the call cost under the token wholesale model even closer to the "cheapest token" threshold.
2. Investment and financing picks up, capital focuses on the "low-cost inference" track
In mid-month, a leading fund led an investment in a startup specializing in sparse attention inference optimization, claiming technology that reduces token consumption for long-context inference by over 60%. Meanwhile, multiple model vendors announced API price cuts, bringing single inference costs down to half those of the same period last year. The logic of the capital market is shifting: instead of blindly chasing parameter scale, it now values "per-token output efficiency." Against this backdrop, token agency service providers have risen rapidly, bulk-purchasing API quotas from model manufacturers and reselling them to small and medium-sized enterprises in a token wholesale format, forming a stable profit margin. Notably, the AI hub launched a "pass-style" subscription plan allowing enterprises to pay a fixed monthly fee to freely switch between multiple base models, with actual per-token costs 40% lower than individual calls. This model is regarded within the industry as "cloud service distribution for the AI era."
3. Platform announcement: AI中转站 officially launches "intelligent routing" and "token agency" capabilities
As the core of this industry development, a mainstream AI aggregation platform (hereinafter referred to as "the platform") issued an announcement on October 25, stating that its AI中转站 service has undergone a major upgrade. The new version supports intelligent routing: users no longer need to manually select models—the system automatically assigns the optimal model based on task type, latency requirements, and budget, dynamically switching to the lowest-cost token agency channel. At the same time, the platform opened a token中转站 interface, allowing third-party developers to build their own inference pipelines. The announcement emphasized that the platform has signed token wholesale agreements with over 20 model vendors, including domestic billion-parameter large models and international open-source model variants. Enterprise users can obtain the "cheapest token" combination plan through the AI API中转站. Additionally, the platform revealed that it is internally testing a layered "AI channel agency" mechanism, offering exclusive discounts to partners with stable traffic, further lowering the operational threshold for secondary agencies.
4. Technology deployment cases: From "benchmark competition" to "real-world cost reduction"
Taking an e-commerce customer service scenario as an example, an enterprise piloting AI中转站 reported that after switching from a traditional large model to intelligent routing, average token consumption per interaction dropped by 35% within one month, while the response error rate increased by only 2%—within an acceptable range. This was attributed to the platform's underlying integration of sparse attention and KV cache optimization, as well as inference nodes deployed across multiple regions. Another financial risk control company, after adopting a token wholesale annual plan, reduced its annual API call budget from RMB 1.2 million to RMB 700,000, with no significant drop in model quality. These cases show that when the token wholesale model is combined with algorithmic optimization, the "usage barrier" of large models is shifting from a technical issue to a purely business one, and the role of AI large model agents is correspondingly upgrading from resellers to solution consultants.
5. Outlook: Aggregation ecosystem moves toward standardization
With the intensive rollout of policies and sustained capital inflows, the "infrastructuralization" trend of the AI industry has become irreversible. It is foreseeable that in the coming months, more aggregation platforms similar to AI hub will emerge, forming a layered structure resembling the cloud computing market through components such as token中转站 and AI API中转站. At the same time, regulators are preparing the "Guidelines for Transparency of AI Service Costs," requiring model vendors and agency platforms to clearly mark the difference between token wholesale and retail prices to prevent information asymmetry. For small and medium-sized developers, seizing the window for the "cheapest tokens" and leveraging mature AI channel agency networks to quickly deploy products will be the most pragmatic competitive strategy over the next six months. The platform announcement also revealed that it will launch a "zero-barrier developer program" in November, providing 500 million tokens of free quota and opening a secondary pricing interface for token agency, further reducing the trial-and-error costs for ecosystem participants.