Token Demand Soars a Thousandfold, $2.2B Floods into This Top AGI Infrastructure Player

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2026-05-07 10:46:50 Source: QuantumBit AI

China's Shared Dependency on Large Models

Heng Yu, reporting from Aofeisi

QuantumBit AI | WeChat Official Account QbitAI

At this year’s GTC conference, Jensen Huang declared: NVIDIA is no longer just a chip or GPU company—it has fully transformed into an end-to-end AI infrastructure company.

This has once again placed "AI Infrastructure" at the epicenter of the industry's spotlight.

In fact, long before this wave arrived, Wuxian.silicon—the leading player in China’s AGI Infra space—had already rooted itself in foundational AI infrastructure. Through successive industry waves, it has continuously evolved, setting benchmarks for the development of China’s AI infrastructure.

Today, its token production and related services are deeply embedded within the core systems of top-tier models such as Kimi, GLM, MiniMax, and DeepSeek—meaning nearly every user of Chinese large models has indirectly relied on its platform.

Recently, the company announced it has secured over 700 million yuan (approximately $1 billion USD) in fresh funding.

This financing amount firmly places Wuxian.silicon among the first tier of native AI infrastructure companies in China, making it one of the fastest-growing emerging players in the domestic foundational AI sector.

Yet beyond funding figures, its business growth metrics offer even clearer evidence of its market leadership.

Public data shows that by the end of April 2026, the daily token call volume on Wuxian.silicon’s MaaS (Model-as-a-Service) platform had increased more than 20-fold compared to the end of 2025—growing dozens of times faster than the national average. Since January, the platform’s token usage has doubled every two weeks.

In the era of AI 2.0, Wuxian.silicon has focused exclusively on the AGI infrastructure赛道, raising close to 2.2 billion yuan (~$300 million USD) in funding from top-tier investors within just three years of founding.

But that’s not all. Wuxian.silicon has now become an essential partner for many of China’s most advanced large model developers.

All these developments trace back to the sweeping wave of token economics now reshaping the entire AI industry.

Understanding this industrial transformation reveals the core value of Wuxian.silicon as a central hub in the token economy.

The Token Economy Wave Has Arrived

Capital markets always sense shifts ahead of actual industry adoption.

This round of investment in Wuxian.silicon was jointly led by Hangzhou High-Tech Investment Group and Huiyuan Capital, with participation from Guoxing Capital, Qinhuangdao Data, GF Qianhe, Lianhe Qingtong, Zhongbao Investment, AEF NextGen, Tengrui Capital, Kalatech, CITIC Construction Investment Capital, and Kuande Intelligent Learning Lab (Will). Existing shareholders Legend Capital, Shanghai State-owned Investment Futeng, and Yuanzi Future also added follow-on investments.

Spanning government-backed industrial capital, PE firms, data centers, finance, manufacturing, and other real-economy sectors, this investor lineup is highly diverse and breaks the traditional mold of early-stage AI investments being concentrated solely within the tech ecosystem.

Now, whether industrial capital or physical enterprises, there is broad consensus:

AGI infrastructure is the foundational bedrock of the future AI industry. Early investment in base-layer infrastructure means capturing the core benefits of AI industrialization.

The key backdrop enabling this consensus is the AI industry’s entry into a new phase driven by Agents—where next-generation scenarios are placing disruptive demands on underlying infrastructure.

Legacy architectures designed for traditional conversational models can no longer keep pace. The widespread deployment of Agent applications is imposing revolutionary requirements on infrastructure in terms of compute power, latency, and stability.

With the arrival of the Agent era, the entire industry’s foundational infrastructure faces three fundamental disruptions.

First, Agents transform large models from “chat companions” into “productive digital workers.”

Before the rise of Agents, large models were largely amateur chat partners.

Most public interactions involved simple Q&A, text editing, or basic queries, consuming only hundreds of tokens per session—with negligible pressure on computing resources.

However, the proliferation of Agents like OpenClaw has completely transformed the role of large models.

They have evolved into full-time digital employees capable of autonomous planning, execution, and self-review.

Complex, multi-step tasks and coordinated workflows have become standard, causing token consumption per single Agent task to surge into the tens or even hundreds of thousands.

This explosion in demand directly intensifies the existing shortage in China’s computing supply, worsening the imbalance between supply and demand.

Beyond exponential increases in compute consumption, the accelerated interaction rhythm sharply exposes weaknesses in traditional AI infrastructure.

This marks the second disruption brought by the Agent era.

Traditional human-machine dialogue is slow: users type inputs manually, ask questions turn-by-turn, and tolerate response intervals measured in minutes—making sub-second startup delays negligible.

Agent operations work very differently.

Autonomous agents interact frequently, make real-time decisions, and iterate continuously, compressing interaction cycles down to the millisecond level.

The latency shortcomings of traditional architectures are magnified exponentially, becoming a critical bottleneck for scaling Agent deployments.

An even stricter change—the third disruption of the Agent era—lies in the heightened demands for operational stability.

Traditional model interactions are short-lived and one-off; occasional restarts or errors don’t significantly impact user experience.

Agents, however, specialize in long-duration, continuous operations. Industry-leading models like GLM 5.1 can sustain uninterrupted operation for up to eight hours when supported by professional-grade infrastructure.

Such prolonged, high-load, non-stop operation poses extreme challenges to precision in compute scheduling, system reliability, and fault tolerance—requirements far beyond what legacy infrastructure can support.

The direct result of these three disruptions is an explosive increase in token call volume.

According to publicly available data from China’s National Bureau of Statistics, the country’s average daily token call volume across the internet has surpassed 140 trillion, representing a year-on-year increase of over 40%. The industry has officially entered a high-growth红利cycle.

While overall industry growth is strong, leading platforms are outpacing the rest.

By the end of April 2026, Wuxian.silicon’s daily token call volume had surged more than 20 times compared to the end of 2025—far exceeding the national average—and demonstrating the scalability and adaptability of top-tier infrastructure platforms.

Xia Lixue, co-founder and CEO of Wuxian.silicon, remarked during the Zhongguancun Forum in March that the last time he witnessed such explosive growth was “during the mass mobile data boom of the 3G era.”

That earlier data explosion powered the golden decade of mobile internet.

Now, the exponential rise in token volume signals that the AI industry is moving beyond conceptual stages toward full-scale deployment and mass adoption.

As massive incremental demand floods the market, the industry urgently needs specialized, stable, and efficient foundational platforms to absorb and enable this wave.

For this reason, leading Chinese large model companies are increasingly partnering with third-party infrastructure providers to jointly build new foundational systems tailored for the Agent era.

The Token Economic Hub Behind Top Domestic Models

Why do we need an independent third-party MaaS platform?

By this stage of AI development, the industry has evolved toward extreme specialization and division of labor.

Just as Apple, Qualcomm, and AMD rely on TSMC, all model developers require efficient inference computing—and trustable, independent third-party platforms.

The AI industry follows the same principle: experts focus on their expertise. Model companies concentrate on algorithms and application scenarios; while compute optimization and token production are best handled by dedicated third-party MaaS platforms.

However, the current infrastructure landscape is naturally fragmented into three silos, each with inherent biases.

For example, big-tech infrastructures primarily serve internal needs; chipmakers’ infrastructures are tightly coupled with their hardware ecosystems—neither can offer fair, open access across the industry. Meanwhile, self-built infrastructures by model companies are constrained by competitive relationships and cannot serve as universal foundations.

Under these conditions, only neutrality enables a company to become the common denominator across China’s AI value chain; only by becoming that common denominator can it evolve into the central hub of the token economy.

Wuxian.silicon differentiates itself through an all-in commitment to infrastructure built upon strict neutrality.

Currently, leveraging its Agentic MaaS platform, Wuxian.silicon delivers high-performance service optimizations for major domestic open-source models including GLM, Kimi, MiniMax, DeepSeek, and Qwen (Tongyi Qianwen), achieving >99.9% accuracy alignment, 2–3x higher throughput, 50% lower overall latency, sub-500ms first-token latency, and enterprise-grade availability of 99.95%.

This relentless focus has made Wuxian.silicon the default choice for leading model providers during the token explosion—and gradually established it as the core hub for token circulation.

Indeed, the deeper truth of our time is that the focal point of AI competition is shifting from model capability to token production efficiency.

Whoever can produce and schedule tokens at lower cost, higher speed, and greater stability will hold the dominant voice in AI industrialization.

Let’s examine how Wuxian.silicon is preparing for this shift.

First: Dynamic Upgrades.

The company has comprehensively upgraded its Agentic Infra technical architecture, specifically tailored to meet the unique runtime needs of intelligent Agents. It precisely addresses industry pain points such as high latency, poor stability, and insufficient concurrency capacity in traditional systems, perfectly aligning with next-gen use cases requiring millisecond-level interactions, long-running tasks, and high-concurrency calls.

Wuxian.silicon has also proactively anticipated trends in multi-agent collaboration and end-to-end deployment, pioneering an autonomously evolving Agentic Infra powered by proprietary AI technologies. Through its enterprise-level agent service platform, it delivers customized solutions across diverse industry scenarios.

Second: Over 100 plug-and-play large models, deeply optimized for domestic cutting-edge models.

As of April 2026, Wuxian.silicon’s AgenticMaaS platform offers more than 160 large models—all ready for immediate deployment—greatly lowering the barrier to entry for enterprises and developers.

The platform keeps pace with open-source model updates, enabling Day-0 rapid integration of newly released models. It has also performed deep, high-performance optimizations on leading domestic models such as Kimi, Zhipu, DeepSeek, Qwen, and MiniMax, maximizing the core performance potential of each model.

These robust technical capabilities have earned top-tier recognition.

In February 2025, MIT Technology Review published an article titled *“Four Chinese AI Startups to Watch Beyond DeepSeek,”* highlighting that alongside DeepSeek, four Chinese AI companies—Wuxian.silicon, StepFun, Faceswap Intelligence, and Zhipu AI—have demonstrated exceptional technical strength and global competitiveness.

At the March 2026 Zhongguancun Forum, Xia Lixue, co-founder and CEO of Wuxian.silicon, shared the stage with Yang Zhiyun, founder of Kimi, and Zhang Peng, CEO of Zhipu Huazhang, revealing insights into Wuxian.silicon’s role as the infrastructure and token service backbone for leading models like Kimi and Zhipu during this wave of AI transformation.

Kimi excels in deep long-text understanding, while Zhipu’s GLM focuses on general complex task processing—both are benchmark players in the domestic large model arena.

Beyond them, Wuxian.silicon’s partnership network extends to other top-tier Chinese models including DeepSeek, MiniMax, and Qwen, effectively covering the majority of premium domestic model resources.

If we compare each large model to an independent power plant generating intelligence, then Wuxian.silicon is the supergrid connecting them all.

It integrates fragmented computing resources across the network, efficiently producing and dispatching tokens, delivering AI productivity steadily to countless industries and billions of endpoints.

This deep collaboration creates a synchronous growth effect—when usage volumes at MiniMax, Zhipu, and others skyrocket tenfold, Wuxian.silicon’s token call volume grows explosively in parallel.

Without facing end consumers directly, it powers the vast majority of AI applications online.

Wuxian.silicon has already deeply embedded itself into China’s core AI production pipeline, becoming an indispensable node in the token circulation network—an essential utility like “water and electricity” for the AI industry, silently supporting its high-speed operation.

Clearly, it has already become the de facto hub of China’s token economy.

The Water Seller of China’s Token Economy

Following the announcement of its latest round of financing, Wuxian.silicon unveiled a new logic of AI productivity, introducing for the first time the AI Productivity Formula:

AI Productivity = Scale of Intelligence × Token Production Efficiency × Token Value Conversion.

Breaking down this formula helps clarify its meaning:

• Scale of Intelligence = Optimized scale of heterogeneous computing resources achievable through technological excellence
• Token Production Efficiency = Ability to efficiently convert electricity into tokens (Tokens/s)
• Token Value Conversion = Ability to transform tokens into societal productivity (Productivity/Token)

This formula redefines the conventional perception of tokens.

Previously, tokens were merely technical units measuring model interaction consumption.

This new framework elevates tokens into core economic variables driving AI industry development, clearly outlining a closed-loop logic for AI industrialization and value realization.

Prior to this, Wuxian.silicon had already proposed a clear value conversion pathway: Input → Electricity → Tokens → Productivity → Value.

The key breakthroughs in this industrial loop lie in two areas.

First, the efficiency of converting electricity into tokens—testing the hard capabilities in infrastructure scheduling, energy utilization, and cost control.

Second, the efficiency of transforming tokens into real-world productivity—achieved through model adaptation, scenario implementation, and industrial empowerment.

China possesses unique advantages for developing a token economy.

A stable and abundant energy structure provides a solid foundation for large-scale computing operations. Combined with the world’s most complete AI industrial chain and largest AI application consumer market, these factors position China’s AI sector to replicate the “Made in China” ascent path.

Over the past decades, Chinese manufacturing leveraged its comprehensive industrial system to become the global center of goods supply, fueling rapid economic growth.

In the future era of AI, AI empowering the real economy will become a brand-new growth engine. "AI-Made in China," leveraging technological and industrial advantages, will participate in global AI industry competition through the novel form of token output.

If the export of "AI-Made in China" tokens is seen as a new engine, then the long-term goal of Wumen Xinqiong—as a hub of the token economy—becomes both clear and logical.

Wumen Xinqiong’s long-term vision is to build a high-efficiency domestic token-powered intelligent factory.

By fully mobilizing China's energy and industrial strengths, it aims to transform high-quality computing power into standardized, premium token products, delivering stable and efficient foundational services to global developers and enterprises, thus helping China’s AI industry advance from practical applications to a new phase of value-driven globalization.

Recently, market valuations in the capital markets have indirectly confirmed the immense potential of the token infrastructure sector.

After completing its IPO, CoreWeave—an overseas leading AI computing service provider—saw its market cap surge from an initial $23 billion to $66 billion, a staggering 189% increase.

The company's core business revolves around providing computing power and token services for top-tier overseas AI models—a model and positioning highly aligned with Wumen Xinqiong.

This valuation surge in overseas capital markets signifies that global investors have recognized the core value of token infrastructure, and the entire industry’s valuation framework has already been reshaped.

Domestic capital trends are also shifting in parallel.

In this latest funding round, Wumen Xinqiong’s investors are no longer limited to traditional tech investment firms—government-led industrial funds, financial institutions, and physical manufacturing enterprises have all joined the ecosystem.

This cross-sector expansion among investors indicates that the value of the token economy has transcended the tech community, earning broad recognition from the real economy and industrial capital.

Overall, Wumen Xinqiong occupies what is arguably the golden lane in China’s AI industry—calling it the hub of the token economy is no exaggeration.

Its unique position as a neutral third party creates irreplaceable industrial value; the exponential explosion in token demand endows the company with strong long-term growth potential; and its mature production formula and complete industrial loop provide a clear path for continuous evolution.

Amid the sweeping wave of full-scale AI industrialization, Wumen Xinqiong firmly plays the pivotal role of a “water seller” in the industry, safeguarding intelligent transformation across sectors.

Looking back at the development of mobile internet, the traffic boom in the 3G era gave rise to mass-market applications such as short videos, mobile payments, and local life services, completely reshaping daily life and industrial structures.

Today, the token explosion in the AI industry is replicating that same traffic miracle.

Wumen Xinqiong, having raised 2.2 billion yuan over three funding rounds, stands out as a quintessential example of this transformative era.

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