Vidu Q4 AI Video Model with Native Audio
Shengshu has launched Vidu Q4, a new iteration of its AI video generation model that introduces native audio as a core capability rather than a post-processing add-on. Earlier versions of Vidu focused primarily on visual output, so the integration of audio directly into the generation pipeline marks a meaningful shift in scope for the model.
Native audio in video generation means the model can produce synchronized sound - whether ambient noise, effects, or other audio elements - as part of the same generation pass that produces the video frames. This approach can result in better temporal alignment between what is seen and what is heard, compared to workflows that stitch audio onto video after the fact using separate models.
Beyond audio, Vidu Q4 also brings improvements to motion quality and prompt control. Stronger prompt adherence is a recurring focus across the video generation field, as models have historically struggled to faithfully translate detailed text descriptions into consistent on-screen motion and composition. Better motion quality, meanwhile, suggests refinements to how the model handles movement over time - reducing common artifacts like unnatural warping or inconsistent subject motion across frames.
Vidu Q4 is available through the Vidu platform at vidu.com. Shengshu, the Beijing-based AI company behind Vidu, has been developing the model as a competitive offering in a market that includes tools from Runway, Kling, and others. The addition of native audio gives Vidu Q4 a feature that remains relatively uncommon among publicly available video generation models, making it a notable option for creators looking to produce video content with cohesive sound from a single generation tool.
