How Chinese AI Models Conquered 2025?

In the spring of 2025, something quietly shattered that no one in Palo Alto heard: the sound of Silicon Valley’s monopoly on artificial intelligence cracking wide open. Chinese AI models have achieved record-breaking global adoption, with systems originating from mainland China, Taiwan, and Hong Kong now representing nearly 30% of worldwide artificial intelligence usage—a remarkable leap from just 13% at the year’s outset.

This surge is documented in OpenRouter’s newly published State of AI report, which examined more than 100 trillion tokens of real-world large language model (LLM) activity across over 300 models supplied by 60+ providers.

One moment the leaderboard was American; the next, DeepSeek, Qwen, and Moonshot’s Kimi were processing more tokens than LLaMA, Claude, and Gemini combined on the largest open routing platforms. This was not a fluke. It was the moment the center of gravity in AI left California for good.

OpenRouter’s end-of-year dispatch called it the “Summer Inflexion.” In June, a single model still owned 40 % of open-source traffic. By September, nothing held more than 25 %. The monopoly dissolved not with a bang but with a thousand small migrations—developers switching prompts, startups rewriting wrappers, entire Discord communities quietly moving their bots from one endpoint to another.

No press release announced the coup. It just happened, one API key at a time. DeepSeek alone swallowed 14.37 trillion tokens in the measured period. That is more raw intelligence throughput than the entire open-source West managed collectively. The West did not lose because it got slower; it lost because it stopped being the default.

When Chinese Became the Second Language of Intelligence

English still rules—82.87 % of all tokens—but Simplified Chinese is now a clear second at 4.98 %, having tripled in twelve months. That number understates the earthquake. Billions of people live in linguistic overlap zones where code-switching between English and Chinese is everyday life. For the first time, an AI that thinks natively in Chinese idioms, Classical allusions, and modern Internet slang is not a curiosity—it is a requirement.

An AI that reasons in Chinese does not merely translate; it reasons differently. It carries a different theory of hierarchy, a different sense of face, a different intuition for when to be direct and when to circle the point for three paragraphs before landing. As agentic systems—those multi-turn, tool-calling, memory-keeping intelligences—take over real work, these subtle divergences will compound into entirely different civilizations of software.

Asia Didn’t Join the Game; It Changed the Board

Singapore now sits second only to the United States in token volume. China itself is fourth, but its AI models punch far above domestic weight. The story is no longer “Can Chinese AI models work at home?” It is “Why are developers in Jakarta, São Paulo, and Lagos choosing Qwen over Claude?” Export-grade usefulness has arrived. The old assumption—that only Western labs could produce globally palatable intelligence—lies in ruins.

The Real Killer Apps Were Never Spreadsheets

Everyone predicted the breakout use case would be email drafting or slide decks. They were wrong by an order of magnitude. More than half of all open-source tokens now go to creative roleplay. Another half (yes, the numbers overlap because humans multitask) go to programming. The median session is no longer “summarize this article.”

It is a three-hour conversation in which a human and an AI co-write a novel, debug a compiler, or simulate an entire startup pitch—often switching between Mandarin slang and Rust syntax without missing a beat. AI stopped being a better Google. It became a better collaborator, confidant, and co-conspirator.

The 30 % Equilibrium That No One Predicted

Open-source AI models have settled into a stable one-third of total inference spend. The age of proprietary supermodels owning 80–90 % is over. We have reached what physicists would call a mixed-phase equilibrium: liquid and vapor coexisting at the same temperature. Corporate giants still extract massive rents at the premium tier—Claude 3.5 and GPT-4o still cost $15–$35 per million tokens and people happily pay—but the substrate of intelligence, the everyday oxygen, is now open and increasingly Chinese.

The Cinderella Timing Advantage

The report coins a delicious phrase: the Glass Slipper effect. The team that first perfectly fits a workload—programming at scale, long-context roleplay, bilingual reasoning—gains a retention moat that later, slightly better AI models cannot dislodge. DeepSeek nailed programming so early and so hard that even when superior alternatives appeared, developers refused to leave. First-mover advantage in AI is not about being the best; it is about being the first to feel like home.

The price spectrum has split cleanly in two. Luxury intelligence—Anthropic, OpenAI, Google—charges luxury prices and keeps its users. Utility intelligence—DeepSeek V3, Qwen2.5, Gemini Flash—delivers 90 % of the performance at 1/50th the cost and powers everything else. The race to zero never happened. Instead we got a barbell: couture and commodity living side by side.

The Next War Will Be Fought in Culture

Raw parameter count is dead. The new battleground is cultural operating range. Can your AI models write a polite Vietnamese business email that still closes the deal? Can it roleplay a Tokyo salaryman with perfect keigo and then switch to leading a Brazilian gaming guild in Portuguese slang? Can it understand why a joke works in Weibo comments but falls flat on Reddit?

The Chinese AI models that grew up in the chaotic, multilingual, meme-drenched Internet of East Asia have an unfair advantage here. They were forged in a crucible where cultural code-switching is the baseline, not the edge case.

2025 did not mark the triumph of China over America. It marked the end of any single region’s right to define what intelligence looks or sounds like. The future will not be decided in Mountain View or Shenzhen alone. It will be decided in the overlap zones—Singaporean trading floors running on Qwen, Indian startups fine-tuning DeepSeek, Eastern European indie game studios living inside Kimi roleplay sessions that last for days.

The monoculture is over. The age of plural intelligence has begun. And the most astonishing part? Almost no one in the old guard saw it coming—because they were still measuring progress in billions of parameters instead of billions of human lives quietly, happily, irrevocably switching sides.

Naorem Mohen

Naorem Mohen is the Editor of Signpost News. Explore his views and opinion on X: @laimacha.