The Great Shift in Computing Power: As Chinese Tokens Dominate the Charts, Who Is Redefining the Value of AI?

February 2026 will go down as a landmark month for the global artificial intelligence industry. It was a month of stark contrasts: on one hand, chip giant Nvidia saw its stock price take an inexplicable nosedive after reporting its strongest-ever earnings, wiping out ¥1.77 trillion in market cap in a single night. On the other hand, A-share markets in China saw a surge in sectors like computing power leasing and cloud computing, with a flurry of limit-up trades and capital pouring in.

This striking "ice and fire" phenomenon can be traced back to a single explosive dataset from OpenRouter.

China's AI Moment: More Than a Win—It's a Landslide

According to OpenRouter, the world's largest API aggregation platform for AI models, the global balance of AI computing power saw a historic shift in February 2026. During the week of February 9–15, Chinese models recorded 4.12 trillion tokens in weekly invocations, surpassing the U.S. figure of 2.94 trillion for the first time. Just one week later, that number surged to 5.16 trillion tokens—a 127% jump in three weeks, widening the lead even further.

Even more striking was the shakeup in the global large model rankings. For the week of February 16–22, four of the top five most-called models worldwide were Chinese: MiniMax's M2.5, Moonshot AI's Kimi K2.5, Zhipu AI's GLM-5, and DeepSeek's V3.2. Together, these four accounted for 85.7% of the total calls among the top five. This wasn't a one-hit wonder—it was a collective rise of China's AI ecosystem.

What gives this achievement extra weight is its global traction. U.S. users made up 47.17% of OpenRouter's user base, while Chinese developers accounted for just 6.01%. That means Chinese models are winning over discerning overseas developers through sheer performance and cost efficiency. As one a16z partner noted, among AI startups currently fundraising in Silicon Valley, an estimated 80% are building their core demos around Chinese open-source models.

The Capital Markets' "Fire and Ice": A Reassessment of Computing Power's Value

Capital markets never miss a signal.

On February 26 Eastern Time, Nvidia posted a 73% revenue beat—yet its stock plunged 5.5%. Meanwhile, in the overnight A-share market, sectors tied to computing power leasing, cloud services, and data centers saw a sharp rally, with many stocks hitting their daily upside limits.

On the surface, this divergence might look like a classic "sell the news" reaction. But beneath it lies a deeper shift: the market is rethinking who captures value in the AI computing stack.

The old narrative was simple: stronger models require more GPUs. Nvidia was synonymous with compute. But the rise of Chinese models has broken that linear logic. Models like DeepSeek and Alibaba's Qwen widely use Mixture-of-Experts (MoE) architectures, which activate only relevant sub-networks rather than the whole model. This reduces inference memory usage by up to 60% and boosts throughput by as much as 19x. In other words, generating massive token volumes no longer requires equally massive clusters of high-end GPUs.

Jensen Huang once said, "The more you compute, the more you earn." But when Chinese models can produce tokens comparable to U.S. models at one-tenth the cost, the market starts to ask: where does the real value accrue? The answer: the profit pool is shifting from scarce chip manufacturing to compute operations and applications. Nvidia's dip reflects anxiety over the "pick-and-shovel seller's" pricing power. China's rally reflects a repricing of those who operate the mines—and those providing the tools for the gold rush.

From Traffic to Fuel: The Token Economy Takes Off

China's explosion in AI inference volume is, at its core, the rise of the token economy.

Tokens are no longer just "traffic" with near-zero marginal cost—they are becoming the fuel of the AI-driven economy. This shift is driven by a fundamental change in how users interact with AI: from asking questions to getting things done.

With the spread of agent-capable models like Kimi K2.5, AI is now being used for code refactoring, document generation, and complex reasoning. Kimi, for instance, can coordinate up to 100 agent instances in parallel, boosting productivity on complex tasks by 3 to 10 times. This kind of deep integration into workflows leads to exponential growth in token consumption.

JPMorgan Chase projects that from 2025 to 2030, China's token consumption will grow at a compound annual rate of 330%, resulting in a 370-fold increase in just five years. This isn't just about scale—it's about making intelligence accessible and affordable.

Looking Ahead

As Chinese AI models take center stage globally, and as the value of computing power shifts from chip manufacturing to application enablement, a golden age for computing power operators has begun. In this wave of revaluation, the challenge for every AI company is clear: how to turn surging token demand into stable, efficient, and low-cost productivity.

In this new landscape, domestic service providers are stepping up as the "power suppliers" of the AI era. Platforms like omniyq.com, with their extensive high-performance GPU clusters (including 4090, A100, H800, etc.) and flexible leasing models, are providing the essential infrastructure for China's booming AI applications. As the flames of innovation are lit by Chinese large models, platforms like omniyq.com are feeding those flames with a steady stream of "computing fuel"—empowering developers everywhere to build the intelligent future at scale and at cost.