As of early 2026, China is leading in AI video generation, especially production-ready, high-quality text-to-video and image-to-video models. This stems from a combination of aggressive engineering focus, large-scale domestic adoption, cost efficiency, and a wave of rapid iterations by leading companies.
Key Chinese models that dominate benchmarking and user adoption include: Kuaishou’s Kling — Versions such as Kling 3.0 and earlier 2.x versions excel in realistic physics, natural human movement, character consistency, and photorealistic output. It is often praised for its excellent image-to-video realism and handling of complex scenes.
Seadance by ByteDance
Seedance 2.0 went viral in February 2026, even impressing celebrities like Elon Musk. Process multimodal input. Use text, images, audio, and video to create cinematic storylines, coherent narratives, camera logic, and professional content for movies, advertising, and e-commerce at low cost.
Contributions from Hailuo/MiniMax, Vidu, and Alibaba are also contributing to the ecosystem. Rather than pursuing purely fundamental breakthroughs like some US efforts, Chinese labs are treating video generation as an engineering-focused problem.
This will lead to faster practical progress. Rapidly Iterate and Deploy — China creates models that solve real-world problems. Get consistent long clips, accurate physics, lip sync, and multimodal control faster. Domestic models are often 10 times cheaper than their US counterparts at approximately 0.3 RMB per second, allowing for massive expansion of advertising, short-form content, e-commerce, and animation.
platform like TikTok (ByteDance), Kuaishoetc. provide vast amounts of video data for training, as well as a large user base for rapid feedback and adoption. China leads in the number of AI patents, publications, and STEM graduates. Policies drive scale, speed, and real-world integration, creating a “race to the top” among companies.
Following DeepSeek’s success in 2025, China has aggressively adopted an open weight model to foster global adoption and developer innovation (the open model has surged to ~30% market share by late 2025). Kling often hits Runway or Sora Motion realism and its equivalent in physics. Seedance stands out for its consistent, story-driven deliverables that feel “production-ready” faster than many Western counterparts.
US models such as Runway Gen-4.5, Google Veo, and OpenAI Sora updates lead in creative control and ecosystem features, but in certain use cases, Chinese models often win on raw video quality, cost, and speed. Game engines aren’t obsolete. It probably won’t become obsolete anytime soon. Recent hype has led to market speculation that generative “world models” could bypass traditional engines and generate interactive environments on the fly, causing gaming stocks such as Unity to plummet by up to 35%.
But experts and industry leaders counter that game engines provide a deterministic and stable system for the physics, rendering, networking, input processing, and real-time interactivity that are essential for playable games.
AI video/world models are still probabilistic and probabilistic (random/unpredictable output), great for cutscenes, trailers, asset prototyping, or passive generation, but less reliable for core gameplay loops that require consistency and control.
The AI acts as your co-pilot. It generates assets, behaviors, tests, and localizations, and is not a replacement. Tim Sweeney and others emphasize that the engine processes the “skeleton” (rules, structure) and the AI adds the “meat” (the variety of content). From 2025 to 2026, AI will increase efficiency in China, similar to anime mass production, but instead of engine obsolescence, it will create a shift in employment.
Games require determinism for fairness, performance, and player agency. AI video is transforming content production (advertisements, films, short-forms), and China has a clear lead in this field through its engineering pragmatism. But for interactive games, traditional engines are still the foundation, and AI enhances them rather than making them obsolete. In the future, hybrid workflows may be introduced.
