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Why China Is Winning the AI Video Race

Seedance and MiniMax are succeeding for a reason that has little to do with benchmarks: China built an economy around generating video.

Two weeks ago, ByteDance released Seedance 2.5 on the same day MiniMax unveiled H3, setting off another round of excitement around AI video. H3 emphasized visual effects and post-production workflows. Seedance 2.5 pushed further into editing, letting creators make precise changes to existing clips instead of generating everything from scratch.

In the U.S., the category feels much quieter. OpenAI has retreated from Sora as a standalone video business, while the biggest American AI companies have not produced anything that has matched the momentum around Seedance. On Artificial Analysis' text-to-video leaderboard, nine of the top 10 systems are now made in China.

When OpenAI began stepping back from Sora, some Chinese technology publications concluded that generative video was simply a bad business. Instead, American retrenchment created more room for Chinese companies.

AI-generated shorts are increasingly accepted on Chinese video platforms. Creators use them for memes, fictional stories, short dramas and advertising, then pay for more credits or API calls to make the next one. Those payments keep the video models alive.

That is the part of China's success that is easy to miss. This is not just a story about model performance. It is a story about operations, distribution and, ultimately, the business environment around the model.

Sora Had a Model. It Never Had an Economy.

This helps explain what went wrong with Sora.

OpenAI is excellent at building AI products, but it has never been a content-platform company. ChatGPT is fundamentally private: you ask something, it answers you. Your output is not automatically placed in front of millions of other users.

Sora inherited that weakness.

A creator could generate a video and post it to YouTube, TikTok or X. But OpenAI did not own the audience on the other side. There was no built-in economic loop that paid creators for producing more Sora videos, and therefore little reason for an independent studio to keep buying enormous volumes of Sora inference.

OpenAI experimented with a more social Sora experience, but building a new video destination is very different from adding video generation to an existing AI product. People already have TikTok, YouTube and Instagram. They do not necessarily need another app whose defining feature is that everything inside it is synthetic.

That is particularly painful because video inference is brutally expensive. SemiAnalysis at one point estimated Sora's operating cost at roughly $15 million per day, equivalent to an annualized burn rate of around $5.4 billion. Even if that estimate is only directionally correct, the economics illustrate the problem: a video model needs a very large amount of paid usage to justify its compute bill.

ByteDance can subsidize that loop because the model strengthens businesses it already owns. It can build the model, help creators make the video, distribute the video, monetize the traffic and then sell the creator more tokens.

OpenAI cannot reproduce that chain.

The U.S. has another obstacle: copyright.

Video models inevitably collide with recognizable actors, characters and visual styles. Soon after Sora's rollout, copyrighted characters from major Hollywood studios began appearing in generated clips, prompting objections from studios, talent representatives and rights holders.

The legal objections are understandable. The commercial consequence is still awkward. Stronger guardrails mean more prompts get rejected or constrained, making the tool less predictable for creators who want to work with familiar cultural references.

Seedance faces copyright pressure too. Rights holders including Disney have challenged the use of protected material in generative video, and ByteDance has responded by restricting some capabilities involving real people, faces and copyrighted characters.

But ByteDance has one advantage OpenAI does not: Seedance does not need the American market to survive.

China alone can provide creators, audiences and paying customers.

Google theoretically has the closest American equivalent. It has video models and it owns YouTube. But YouTube has little reason to aggressively subsidize a flood of cheap AI video when the platform is already trying to manage audience frustration with low-quality synthetic content.

The technology may be similar. The incentives are not.

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Seedance Has Something Sora Never Had: Douyin

When Seedance 2.0 broke out earlier this year, Western coverage mostly treated it as another sign that China had caught up in AI video.

The more important question was where all that AI slop was going.

The answer was Douyin, ByteDance's Chinese version of TikTok.

AI-generated content has faced less cultural resistance in China than it has in parts of the U.S. Before Seedance, Chinese creators were already using Sora, Google's video models and MiniMax's Hailuo AI to make memes. The output was often obviously synthetic: soft depth of field, strange faces and physics that did not quite make sense. But it created an early generation of users who learned how to make AI videos entertaining.

Then Seedance became much more usable.

Its early viral examples did not simply show beautiful random scenes generated from text. Creators demonstrated familiar cinematic styles-old Hong Kong martial-arts films, Japanese tokusatsu and tightly choreographed fight scenes-while keeping characters, costumes and environments unusually consistent.

That matters more than prettier demos.

For creators, a video model becomes useful when the same character can survive from one shot to the next. A tool that produces one spectacular clip and then loses the character's face is a lottery ticket. A model that can preserve the visual asset is production software.

ByteDance also has an enormous structural advantage through Douyin, one of the world's largest short-video platforms. It gives the company access to an immense ecosystem of short-form visual content, creator behavior and immediate distribution. Exactly how user content feeds model training is not publicly disclosed, but the product advantage is obvious: ByteDance understands what people make, what they watch and what they remix.

That created a loop. Seedance users made videos. They uploaded them to Douyin. Viral examples attracted more people to Seedance, who created their own variations and pushed the model into new meme formats.

Then ByteDance added another layer: short dramas.

The company owns TomatoFiction(番茄小说) an enormous source of serialized web fiction, and Hongguo(红果短剧,another name is Melolo), its short-drama platform. The novels provide ready-made plots filled with romance, betrayal, revenge and endless cliffhangers. Hongguo provides somewhere to monetize the resulting videos.

ByteDance's familiar strategy is to subsidize creators first, then make traffic the performance metric. In AI video, that strategy worked almost too well.

By early 2026, AI-generated animated dramas had become one of China's hottest content businesses. According to 36Kr, some production companies began buying the highest-tier Seedance 2.0 API packages through ByteDance's Volcano Engine. One reported top-up reached $7.4 million.

Seedance 2.0's 720p generation reportedly cost about $6.82, per million tokens, translating to roughly 15 cents, per second of video in one common configuration. Kling AI from Kuaishou Technology could be cheaper, at roughly 9 cents per second, while Vidu from ShengShu Technology could come in near 10 cents.

But reliability changes the calculation. Saving a few cents does not matter if a generation has to be thrown away.

Bilibili is moving in the same direction with its AI creation tools, allowing users to build a story, supply images and other assets, and then generate the video through models including Seedance.

Seedance therefore has something more valuable than a benchmark score: inputs, creators, distribution and a reason to keep generating.

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