The commercialization of artificial intelligence applications has evolved beyond traditional software licensing and membership subscriptions to encompass the sale of token-based access capabilities. In this emerging framework, a token represents the fundamental unit of information processed by large language models, serving as the bedrock for billing, settlement, and consumption regarding model APIs. As the frequency of API calls escalates, tokens are increasingly treated as tradable inventory that can be purchased, routed, split, and resold. Chen Liangdong, an analyst at Huayuan Securities, characterized this shift as the emergence of a new intermediate market layer designed to connect upstream model providers with downstream developers, enterprises, and individuals. This layer functions as global infrastructure facilitating the flow of tokens from wholesale to retail levels. The catalyst for this business model is the explosive growth in token-based call volumes within China, which rose from an average of 100 billion daily calls at the start of 2024 to 100 trillion by the end of 2025, surpassing 140 trillion in March 2026.

Concurrently, domestic large models have advanced significantly, entering the global top tier in both capability rankings and call volume. Despite this growth, transaction friction remains due to payment method limitations, network infrastructure gaps, interface incompatibility, compliance hurdles, and distribution channel constraints. Woofun AI notes that while simple resale of API quotas yields thin margins, substantial profits are generated through inference acceleration, unified interface standards, enterprise-specific prompt development, agent configuration, model selection, and business system integration.

However, the low entry barriers for this market introduce direct risks, including intensified competition, the necessity for upfront capital, bad debt exposure, and potential policy shifts by model providers that could erode intermediary profits.

The architecture of the token distribution ecosystem comprises three distinct tiers of entities. At the upstream level sit the model providers, including ByteDance's Seedance series, Alibaba's Qwen series, Zhipu's GLM series, Moonlit's Kimi series, and DeepSeek's series, which serve as the primary sources of tokens. The middle layer consists of agency platforms that acquire resources from upstream providers and resell them to end-users. These platforms transcend simple quota resale by converting diverse interface protocols into a unified API format, allowing users to access multiple models via a single API key. The downstream tier includes actual consumers such as individual users, developers, corporate clients, and lower-level distributors. The value proposition of this intermediate layer is multifaceted: domestic direct connections mitigate network barriers, a single codebase enables interaction with multiple models, and the platform supports both personal and corporate payment methods. Bulk purchasing capabilities lower costs, while aggregation of models like GPT, Claude, DeepSeek, and Kimi reduces development expenses for integrating multiple systems. Consequently, the capital requirements for token distribution appear relatively low, as there is no need for in-house model training or maintenance of large-scale server clusters. The core assets for this business model instead include API routing and scheduling systems, access to upstream resources, distribution channels, customer relationships, and service capabilities.

For the token operation model to achieve viability, sufficient consumption volume is paramount. In China, the average daily volume of token-based calls expanded from 100 billion to over 140 trillion in just two years, representing a growth factor exceeding 1,000 times. This surge is driven by the widespread adoption of vertical applications and the integration of generative AI into enterprise business processes. Data compiled by Woofun AI shows that IDC projects the number of active intelligent agents in Chinese enterprises will exceed 350 million by 2031, with an annual compound growth rate surpassing 135%. As the complexity and density of agent tasks increase, the annual growth rate of associated token consumption is expected to exceed 30 times. This trajectory is already visible in specific model performance; for instance, OpenClaw's weekly token consumption on the OpenRouter platform climbed from 0.81 trillion on February 2, 2026, to 4.97 trillion on March 16, 2026, with its market share rising from 8.31% to 24.36%. As tokens become large-scale commodities, activities such as procurement, pricing, routing, and settlement naturally become more structured. Model providers do not need to serve every individual customer directly, and end-users prefer not to connect to each model individually, creating a distinct niche for intermediate market players.

The enhancement of domestic large model capabilities has been a pivotal factor enabling token distribution to expand from domestic markets into cross-border scenarios. Data from SuperCLUE indicates that comprehensive scores for domestic models like ByteDance's Beanbag series and DeepSeek's series have exceeded 70 points, narrowing the gap with leading overseas models such as GPT-5.4 and Gemini. Models including Tongyi Qianwen, Kimi, and Zhipu's GLM series have established clear performance tiers. as of the week ending May 10, 2026, Tencent's Hy3 preview (free) ranked first in call volume. Among the top five, ten, and twenty models by call volume, there were 2, 6, and 9 domestic models respectively. A significant shift occurred in the first quarter of 2026; from February 9 to 15, token-based calls by Chinese models on OpenRouter reached 4.12 trillion, surpassing American models at 2.94 trillion for the first time. This figure increased further to 5.16 trillion from February 16 to 22. Among the top five models by call volume, four were from Chinese manufacturers: MiniMax M2.5, Kimi K2.5, Zhipu's GLM-5, and DeepSeek V3.2, contributing a combined 85.7% of the total call volume in the top five rankings.

The price advantage of domestic models remains a critical competitive edge. Input prices for MiniMax M2.5 and GLM-5 stand at $0.3 per million tokens, whereas Claude Opus 4.6 costs $5 per million tokens. Output prices show an even starker contrast: MiniMax M2.5 is priced at $1.1 per million tokens, GLM-5 at $2.55 per million tokens, and Claude Opus 4.6 at $25 per million tokens. In high-consumption scenarios like AI agent development, the cost-effectiveness of domestic models becomes pronounced. Token distribution addresses not only pricing but also resource allocation mismatches. Overseas leading models face geographical access limitations, compliance regulations, and payment barriers, restricting their reach to users in mainland China. Conversely, domestic high-quality models encounter challenges in overseas markets regarding local adaptation, channel establishment, and customer acquisition. These imbalances have spurred demand for cross-border token flows, aggregated routing services, and tiered distribution models. OpenRouter exemplifies this trend, with weekly token processing volumes rising from 5 to 7 trillion in 2025 to over 20 trillion in April 2026. Its annual revenue in 2026 exceeded $50 million, approximately five times the $10 million reported in October 2025.

Similar platforms are emerging in China, such as SiliconFlow, a one-stop cloud service platform for large models. Utilizing self-developed inference engines, it provides efficient inference acceleration and enterprise-level solutions. As of December 2025, the platform boasted over 9 million registered users, more than 10,000 enterprise customers, and over 150 launched models. Even US-based political-linked investors have entered the sector; on May 5, 2026, WLFI, a cryptocurrency company with ties to the Trump family, collaborated with WorldClaw to launch WorldRouter. This platform integrates over 300 models, including Claude, GPT, and Gemini, offering USD settlements at prices approximately 30% lower than official rates. Profit generation in token distribution occurs through three primary mechanisms. The first is resale at a higher price, where platforms buy bulk API quotas and sell them at a premium; OpenRouter charges an additional 5.5% on supplier costs. The second leverages technical advantages, using inference acceleration engines to reduce per-token costs. SiliconFlow's SiliconLLM and OneDiff technologies increase language model inference speed by 10 times and text-to-image generation efficiency by 3 times, reducing API call costs to 1/10 of the industry average. The third involves providing enterprise value-added services, where hidden costs like prompt development, model selection, and system integration become significant revenue sources as basic token prices drop. SiliconFlow's enterprise MaaS platform delivers these services, covering data processing, model fine-tuning, and RAG techniques to industries like energy, finance, and government.

For token distribution to remain profitable, application in real-world scenarios is essential. Generative AI is increasingly deployed in healthcare, transportation, and industrial manufacturing, supporting corporate decision-making and strategic management.

However, many enterprises lack the digital transformation foundation, data assets, and computing resources to deploy AI solutions directly. In contrast, marketing and advertising companies possess existing customers and use cases in short-form videos, web comics, games, and e-commerce, creating direct and sustainable token demand. Their opportunity lies in integrating tokens into content generation, delivery, material production, and video production processes. Investment opportunities in this field fall into two categories: companies with high-quality model capabilities like Alibaba, Tencent Holdings, Kuaishou, Kunlun Wanwei, Zhipu, and MiniMax; and companies with strong token use cases and large customer bases, particularly those with overseas channels willing to invest in AI marketing and video production, such as Yidian Tianxia and BlueFocus. Woofun AI analysis suggests that while the token distribution business model is lightweight, its competitive advantages are not inherently robust. The primary risk stems from industry competition, as low technical barriers allow well-funded distributors to replicate successful models and squeeze out intermediaries. Additional risks include the need for upfront funding and bad debt exposure, given that distributors often settle with downstream customers monthly or quarterly while paying upstream providers in advance. Finally, policy changes by large model providers regarding API pricing and access rules pose a significant threat to the stability of intermediate market players.