Breaking the Dilemma of Increasing Volume Without Revenue Growth for Chinese Large Models Going Global, B.AI Builds a Value Repatriation Super Hub via 'Direct Manufacturer Integration + Global Aggregated Payments'

Author: Tron Eco News

In 2026, Chinese large language models will usher in their “first year of going global”. Relying on open weights and high cost-effectiveness, their call volumes frequently top the rankings on various aggregation platforms. “Usable and affordable” Chinese LLMs are becoming a practical choice for overseas developers and enterprises.

However, beneath the bustling charts, a more industry-critical issue is emerging. Survey data shows that while the overall call volume of Chinese LLMs on the overseas aggregation platform OpenRouter is growing, the share of tokens for the original manufacturers themselves is significantly declining.

The reason is that when the same model is handled simultaneously by numerous third-party hosting providers, calls are layered and diverted, diluting the original manufacturer’s call volume and revenue. Furthermore, the default “automatic routing” mechanism on such platforms further amplifies this effect: if users do not make manual settings, requests are routed based on the lowest price or latency, flowing toward cheaper service providers.

"Increasing volume without increasing revenue" has thus become the most pragmatic challenge for Chinese LLMs going global. When traffic no longer equals revenue, what Chinese LLMs truly need is a channel that returns value directly to the original manufacturers.

B.AI, as a next-generation global AI infrastructure, offers a different answer. Distinct from traditional "automatic routing" mechanisms, B.AI treats official APIs as independent, transparent, user-choice-direct lines, preventing the original manufacturer's token share from being quietly diluted. Additionally, through deep ecological cooperation with major models, B.AI releases token subsidies, keeping the prices on official channels highly competitive.

Combined with a multi-currency aggregate payment engine, friction in cross-border transactions is cleared. More profoundly, backed by solid user accumulation, B.AI has successfully captured massive user volume, officially entering an era of daily trillion-token throughput. B.AI is no longer merely an outbound distribution channel, but a super hub connecting global enterprise demand with the age of Agents.

Beneath the Ranking Dominance: The "Volume Growth Without Revenue Growth" Dilemma of Chinese LLMs

The commercial monetization dilemma of "volume growth without revenue growth" for Chinese LLMs going global has been intuitively confirmed by recent industry survey data.

A tracking report published by the well-known AI think tank Epoch AI shows that the overall call volume of Chinese LLMs on the overseas API aggregation platform OpenRouter is experiencing exponential growth. However, this massive "increment" has not been converted into "revenue" for the model manufacturers at the same proportion. This is not an isolated case, but a common phenomenon faced by leading Chinese LLMs during their global expansion.

Taking Zhipu's GLM-5.3 Flash as an example, the diversion caused by homogeneous competition is extremely severe. The report points out that within just one day of releasing its weights, the number of third-party hosting providers increased to 12, reaching 26 after 20 days, 8 of which offered quotes lower than Zhipu's.

During this period, while the overall usage of GLM-5.3 Flash on OpenRouter grew by 17%, Zhipu's own daily average token volume dropped by 70%, and its share of processed model tokens fell from 88% to 22%. Although total calls for GLM were increasing, more calls were being handled by other service providers.

Epoch AI's macro-level projected data further validates this structural pain point. Referring to the provided data chart, this statistic covers estimated customer expenditure on OpenRouter between August 27 and September 19, 2026 (annualized calculation).

Data shows that the vast majority of consumption expenditure directed at Chinese LLMs flows to third-party hosting providers rather than model developers (original manufacturers), meaning the actual revenue share obtained by original manufacturers constitutes only a tiny fraction of total expenditure.

This implies that Chinese LLM companies shoulder the core costs of model training and computing power iteration, yet fail to adequately capture commercial returns matching their technological contributions along the monetization chain. This situation stems from a combination of several structural factors.

The first is supply homogenization: when model weights are open and the same model can be deployed by multiple service providers, inference services themselves become highly standardized, naturally shifting the focus of competition to price and latency. Epoch AI's research also finds that the higher the premium set by the original manufacturer for open-weight models, the smaller the share of their own tokens hosted on OpenRouter.

The second is the further catalysis by the "default routing" mechanism: aggregation platforms typically distribute requests based on the lowest price or lowest latency principles. If users do not make additional settings, traffic will flow to the provider with the lowest quote rather than the model's original manufacturer.

The third is the barrier to access and payment: facing frictions such as cross-border payments, currency differences, and account systems, overseas users often prefer more convenient aggregation channels, making it difficult for direct connections from original manufacturers to scale up.

For large model manufacturers, the key to breaking through lies not in stopping the wide distribution of models across multiple channels, as openness and sharing are inherently the "boosters" for Chinese LLMs going global. What truly allows value to return to the original manufacturers is establishing a clear, transparent, low-cost official channel that users can actively choose, while simultaneously lowering usage and payment barriers for global users.

In other words, the industry does not need another "cheaper transit station," but rather a set of infrastructure that respects user choice while ensuring value flows back to the original manufacturers.

Returning Choice to Users: B.AI Makes "Official Direct Connection" a Visible Channel

To break through the industry's "volume growth without revenue growth" dilemma, reshaping the connection method between users and models is the first step toward rebuilding commercial order. To make commercial value clearly visible, B.AI's solution starts from the very bottom layer of product architecture, completely returning the "final routing selection right" to the users.

Within B.AI's system, the "official direct connection" serves as an independent, transparent channel left to user discretion. For scenarios with specific requirements for model performance and stability, users can directly choose a direct connection to the original manufacturer's API, guaranteeing ultra-low latency under high concurrency while meeting stringent data security and compliance requirements.

For scenarios where cost and elasticity are more critical, users can also choose other channels as needed. This user-customizable transparent mechanism brings direct, two-way commercial value to the entire ecosystem.

For original manufacturers, this effectively prevents the diversion of core token shares. When enterprise customers' high-concurrency and high-reliability requests reach the original manufacturer directly through dedicated channels, the token share and profit margins rightfully due to them are firmly protected.

For developers, this means ultimate business certainty. Choosing the official channel independently means bidding farewell to performance fluctuations and "downgraded capability" blind boxes, enabling stable access to model capabilities in their "full-health state."

More worth mentioning is that this transparent direct connection mechanism has already received widespread recognition from China's leading LLM camp. Currently, B.AI has established deep ecological partnerships with many top Chinese LLMs such as Zhipu, MiniMax, Kimi, Xiaomi Mimo, Qwen, and DeepSeek, jointly pushing these high-quality "original manufacturer direct lines" to global developers.

This not only confirms the commercial feasibility of B.AI's model but also marks the evolution of LLM global expansion from "chasing low prices" toward a healthier ecosystem that "values quality and commercial sovereignty."

However, handing over choice to users also requires answering a realistic question: Will the official channels be more expensive? In this regard, relying on the platform's massive economies of scale, B.AI continuously partners with deeply cooperative models to launch a series of limited-time promotional events, continually releasing ecological dividends. Among these promotions, the highest subsidy level has even reached complete free usage.

Through tangible ecological concessions, B.AI has successfully played its "price reduction without capability downgrade" card. Developers no longer need to bear high premiums; they can obtain 100% native full-state official model capabilities at a comprehensive cost that may even be lower than third-party hosting. Users completely bid farewell to the dilemma of compromising between "price and performance."

More importantly, the deep partnership model of "direct connection + subsidies" holds commercial value far beyond short-term user acquisition. In the past, some outbound models were often simply viewed by overseas markets as "cheap computing power alternatives." Now, leveraging its powerful ecological synergy, B.AI is helping domestic large models establish true brand loyalty overseas.

By tying the high-quality service of official manufacturers with extreme cost-effectiveness, B.AI is helping Chinese models shake off the stereotypical label of a "cheap computing power pool," significantly elevating their strategic positioning in the global AI industry chain.

Beyond Just a Channel: Forward-Looking Layout of Global Settlement, Trillion Throughput, and the Agent Era

For overseas developers, whether a channel can be used smoothly depends on payments. Within its overall architecture, B.AI not only connects computing power and models but also positions itself as a "smart global settlement layer," extending ecological carrying capacity outward from this core.

As a smart global settlement layer, B.AI's payment engine achieves high compatibility within a compliant framework. It horizontally integrates localized settlement methods such as Visa, Apple Pay, Alipay, and WeChat Pay, and vertically connects to 7 mainstream blockchain networks, supporting multiple digital assets.

This dual-track parallel design allows traditional Web2 enterprise clients and Web3 native developers to complete top-ups, subscriptions, and calls within the same platform with the lowest access friction. Currently, payments completed through traditional fiat channels like Stripe on the B.AI platform account for over 50%.

This global settlement foundation, combining both breadth and depth, marks that B.AI has completely broken through the limitations of a traditional "technology transit station," leaping into a super hub reshaping the commercial landscape of large models. It not only enables top-tier AI computing power to seamlessly integrate into the global business cycle but, through strong ecological attraction, condenses scattered global enterprise demands into a highly explosive-value network.

Supporting the efficient operation of this massive settlement network is the platform's profound scale foundation. Currently, B.AI's daily throughput has exceeded 1 trillion tokens, with a user base approaching 3 million. Notably, it reached a scale level that early aggregation platform OpenRouter took about two years to touch, achieving this in roughly 100 days post-launch.

Through deep cooperation with large model manufacturers, the B.AI platform now fully supports 70+ mainstream large models, building an advanced multimodal ecological matrix. This massive business volume and comprehensive ecological network mean that B.AI has substantially established its core hub status as a next-generation global AI infrastructure.

When "official direct connections" defend the original manufacturer's computing share, "token ecological subsidies" build ultimate user acquisition advantages, and this is added to a trillion-level underlying throughput network and global settlement system, B.AI weaves a complete ecological loop from "demand touchpoints" to "commercial monetization" for Chinese large models.

Through this mechanism, Chinese LLM manufacturers are able to conquer the war of attrition of "volume growth without revenue growth," maximizing their outbound value within a stable, transparent, and highly explosive commercial soil.

Finally, atop the foundation of payment settlement and scaled throughput, B.AI also directs its vision toward the more frontier Agent economy. The platform's long-term vision is not merely to stay at the model routing layer, but to deeply integrate computing routing, decentralized settlement, and full-stack Agent infrastructure.

Currently, B.AI has deployed toolchains such as Agent Wallet and Skills, comprehensively empowering Agents to autonomously handle complex tasks across environments. At the protocol layer, the platform integrates the x402 payment protocol and the 8004 authentication protocol, providing standardized trust and settlement support for future high-frequency, micro-amount automated calls between machines.

As the calling subjects of APIs gradually evolve from human developers to automated Agents, this smart settlement layer and execution hub strategically laid out by B.AI in advance will become a key node connecting foundational models with the future trillion-scale Agent ecosystem.

In this new era jointly driven by large models and Agents, B.AI will become the most deterministic "super router" in the globalization journey of Chinese large models. It not only safeguards Chinese models in achieving maximum commercial value but also connects global demand, computing power, and Agents, driving the global AI industry toward the next prosperous cycle with a transparent, efficient, and win-win commercial loop.