The Spring Festival, a time traditionally associated with leisurely travel and unrestrained spending, has transformed into the most intense battleground for China's big model industry this year.

Historically, model releases adhered to a technical cadence: papers, rankings, evaluations, and iterations all progressed according to the logic of the laboratory. However, in 2025, the rules underwent a subtle yet significant shift. DeepSeek's "surprise attack" during the Spring Festival, leveraging minimal marketing expenditure to spark maximum discussion and user growth, redefined model releases as precision-targeted traffic ambushes.

This year, the entire industry followed suit. ByteDance, Alibaba, Zhipu, MiniMax, and DeepSeek all launched their flagship models nearly simultaneously, vying for the coveted Spring Festival window.

The competition over model capabilities has evolved from a mere "who is stronger" contest to a race of "who gets adopted faster," and further into a harsher reality: who can directly occupy the gateway that Chinese users frequent most during the seven-day holiday?

As inference costs plummet and agents become more sophisticated, AI is no longer confined to standalone applications; it is beginning to permeate chat boxes, search bars, and transaction pages. The arms race among model companies is inadvertently paving the way for a different kind of victor.

An unexpected answer emerges: in this round of model wars, the biggest beneficiaries may not be the model vendors themselves but Tencent. The Spring Festival is evolving into the first nationwide stress test for consumer-grade AI.

The Spring Festival is no longer just a launch event; it has become the "survival traffic pool" for big models.

If 2023 was the "catch-up phase" and 2024 the "fundraising phase" for China's big models, then post-2025, the industry has rapidly entered a more pragmatic stage: validation. What is being validated is not the scale of parameters but user retention.

DeepSeek's Spring Festival surprise last year did not pioneer a new technical path but demonstrated something far more crucial: big models can adhere to traffic scheduling logic, akin to games, short videos, or films, by concentrating exposure during holidays when users have the most leisure time and fragmented attention spans, using short-term bursts to secure long-term mindshare.

This approach swiftly altered the industry's rhythm. Consequently, the 2026 Spring Festival witnessed unprecedented "model congestion."

ByteDance unveiled a multimodal matrix, simultaneously updating video, image, and dialogue models; Alibaba tied its new-generation Tongyi model to substantial subsidies, competing for developers with real money; Zhipu doubled its parameter scale and bolstered agent capabilities; MiniMax bet on platformization, aiming to meet enterprise demands through unified interfaces; DeepSeek doubled down on efficiency and long contexts, attempting to sustain its "low-cost, high-performance" differentiation.

On the surface, this appeared to be a technological renaissance; commercially, it resembled a crowded race. There is only one Spring Festival window, and developers and ordinary users have only a finite amount of attention to spare.

When multiple flagship models launch simultaneously, the dynamic is simple: compare horizontally and swiftly eliminate. This means, for the first time, big models face true "winner-takes-all" scenarios.

In the laboratory era, falling behind meant having time to catch up; in the traffic era, one absence could mean complete oblivion. The gap in model capabilities can widen infinitely in just one week. Deeper changes are also afoot: the competition's focus has shifted.

Previously, everyone competed on "bigger": hundred-billion parameters, trillion-token training, SOTA rankings. But as capabilities converge, "bigger" no longer equates to "more useful." What truly determines commercialization limits is another metric: the cost per inference.

If complex reasoning remains expensive, big models will remain niche tools; only when costs drop to search/recommendation levels can they become ubiquitous infrastructure.

DeepSeek's emphasis on conditional memory and retrieval-based computing is essentially a cost revolution: shifting some dense computing to cheaper "lookup" operations. This path may not be the most glamorous but is pragmatic enough. For consumer products, speed and price often outweigh peak performance.

The industry is gradually recognizing a stark reality: no matter how powerful a model is, if it is not financially viable, it remains a laboratory luxury. This intense Spring Festival release wave, seemingly a technical climax, is actually the opening salvo of a cost competition. Once costs plummet, the rules will be rewritten entirely.

When AI becomes a "feature collection," who are the real winners?

A frequently overlooked fact: chatbots are not AI's ultimate form. Standalone apps, while seemingly complete, are inherently low-frequency. Users won't open a dialogue robot ten times daily but will open chat tools, search bars, and e-commerce platforms dozens of times.

This explains why, despite global AI traffic surging last year, stable daily active users remained elusive. Many products' hype faded quickly.

The issue is not the models but the gateways. As inference costs decline, AI's optimal form is not "please open me" but "you won't even notice I'm here."

It should seamlessly integrate into WeChat's input box, rewriting your sentences; in search results, providing direct answers; in e-commerce customer service, completing transactions. It should be a default feature, not a standalone destination.

Following this logic, the biggest beneficiaries are not model companies but platforms with high-frequency scenarios. This is why Tencent's position becomes particularly intriguing.

WeChat and QQ remain China's two most frequently used gateway-level products. They control not model capabilities but time—billions of daily clicks, dialogues, and dwell times.

With plug-and-play third-party model capabilities, Tencent need not build the strongest model itself; it can integrate the best ones. If inference is cheap enough, it could even enable AI by default.

What does this mean? Every chat, search, and transaction consumes inference tokens; demand naturally scales exponentially.

Model companies sell APIs; Tencent sells "scenario density." The former competes on price; the latter harvests traffic. In this structure, the more mature the technology, the more valuable the gateway; the more homogeneous models become, the stronger platforms grow.

For Alibaba and Baidu, the situation is more nuanced. Stronger models do enhance Taobao Q&A and search experiences; but if the industry plunges into price wars, APIs will face pressure. They are both beneficiaries and squeezed players.

Ironically, numerous vertical platforms emerge as potential winners. Travel, real estate, local services, and content communities can fine-tune open-source models at low cost, building proprietary agents with specialized data. This "plug-and-play" dividend was unimaginable before.

Thus, the industry faces a paradox: model companies frantically race in arms buildups, yet the real money may go to companies that never build models. This makes the Spring Festival battle even more critical.

Because all demos can be faked; only real users don't lie. When tens of millions or even a billion users engage during holidays, models' latency, stability, and tool-calling success rates will be fully exposed.

If agents still frequently err, consumer-grade AI needs more time; but if they become as smooth as search, the tipping point will arrive unnoticed—not at a launch event but one day when people suddenly find themselves indispensable to it.

Capital markets already price with longer time horizons, ignoring short-term profits and losses to bet directly on 2030's inference demand scale. Because once AI becomes a default feature, demand won't grow linearly but explode embeddedly.

In retrospect, this Spring Festival may just be the beginning. 2025 was the technical year for big models; 2026 might be the true product year for consumer-grade AI. And the final outcome may hinge not on who has the strongest model but who owns the gateway opened dozens of times daily.