Token wholesale pricing becomes new battlefield, industry races for 'cheapest token'
In October 2026, domestic mainstream large model platforms successively adjusted API billing strategies, transitioning from traditional per-token usage billing to token wholesale models. Multiple vendors introduced tiered wholesale packages, allowing enterprises to purchase large token quotas at a fixed monthly fee, with unit prices reduced by 30% to 50% compared to pay-per-use. This change is directly driven by the shift of enterprise-level reasoning needs from experimental calls to large-scale production, with monthly token consumption commonly exceeding tens of billions, making the traditional pay-per-use model unable to support enterprise cost control demands.
It is worth noting that a group of emerging platforms have adopted the "cheapest token" label, reducing model inference costs through middle-layer optimizations (such as cache reuse and sparse scheduling). For example, an AI hub platform built specifically for enterprises claimed its wholesale price is only 60% of leading platforms, and completed a new round of financing this month, with investors including multiple industrial funds. Meanwhile, some cloud vendors also followed up with "Token annual card" services, using prepaid models to lock in long-term customers.
Channel agency model matures, AI channel agency and AI large model agency ecosystem expands
With the popularization of token wholesale pricing, the AI channel agency model experienced explosive growth in October. In the past, large enterprises directly connected with model vendors, while small and medium enterprises, due to technical barriers and weak bargaining power, were often excluded from discounts. This month, multiple third-party service providers launched AI large model agency solutions, aggregating multiple model capabilities, unified billing and scheduling, helping enterprises achieve "one-time access, multiple model switching".
For example, some AI channel agency platforms began offering "multi-model routing + token wholesale" packaged services. Users do not need to deploy SDKs from different vendors separately; they can call mainstream models such as GPT-4o, Claude 4, and Ernie Bot through a single API, and automatically select the current cheapest token source. This model has been quickly implemented in high-frequency scenarios such as e-commerce customer service and content generation. According to industry media statistics, the number of new enterprise customers on channel agency platforms in October increased by more than 40% month-on-month.
At the same time, some technical teams have built token relay stations and AI API relay stations, specializing in optimizations such as request queuing, error retries, and result caching for original model APIs, and earning service fees from them. This type of middle-layer service not only reduces the operational pressure on enterprises but also obtains lower token wholesale prices through bulk procurement, further lowering end-user costs.
AI API relay stations and token relay stations: technology dividends and business closed loop
Behind token wholesale and channel agency is an increasingly refined delivery chain. In October, several startups focused on API optimization released a new generation of token relay station products, with core capabilities including dynamic request throttling, intelligent cache hit improvement (up to 70% or more), and token compression for long-context scenarios. These optimizations enable enterprises to save 15% to 25% on actual token costs compared to original API calls.
A typical case is that an e-commerce platform, by connecting to an AI API relay station, used large models for product description generation and automated customer service replies. Its monthly average token consumption dropped from 12 billion to 9 billion, while output quality was almost unaffected. The platform's CTO said: "The relay station helped us automatically avoid duplicate generation and invalid requests, essentially buying more effective capability with less money."
It is worth noting that AI hub-type platforms have also begun to integrate these relay station capabilities, forming a one-stop "wholesale-scheduling-optimization" service. This month, news came that an open-source token proxy software has gained widespread attention from the community, supporting users to build private token proxies, further reducing enterprise dependence on commercial platforms.
Policy and investment financing step up simultaneously, industry standardization accelerates
Alongside rapid industry iteration, regulatory policies also saw new developments in October. An eastern province issued the "Compliance Guidelines for Artificial Intelligence Large Model Services," clearly requiring platforms offering token wholesale and channel agency services to conduct security reviews of model outputs and establish data privacy protection mechanisms. This policy is believed to push the AI channel agency industry from chaotic growth toward compliant operations.
In terms of investment and financing, among the disclosed financing events in the AI infrastructure field in October, more than half were related to token optimization and channel agency. For example, a startup focused on "large model cost optimization" completed a Series B round, with its core product being an enterprise-level token relay station. In addition, several established cloud computing vendors are actively investing in or acquiring small and medium-sized AI API relay station teams to fill gaps in their own AI service ecosystems.
Industry analysts believe that as token wholesale and channel agency models mature, large model services will transition from "selling model capabilities" to "selling cost efficiency." Whoever can provide enterprises with the cheapest tokens and the most stable token proxies will gain an advantage in the second half of the competition. It is foreseeable that innovation and integration in this field will continue to accelerate in the fourth quarter of 2026 and into 2027.