Vidu Q3 AI Video Model with Native Audio
Shengshu has launched Vidu Q3, an updated AI video generation model that introduces native audio as a core capability rather than a post-processing add-on. Previous versions of Vidu focused primarily on visual output, so the integration of audio directly into the generation pipeline is a meaningful shift in the model's scope. Creators working on short-form content, social media clips, or early-stage production work can now generate video and sound together in a single pass.
Beyond audio, the Q3 release brings improvements to motion quality - addressing a persistent challenge in AI video where movement can appear unnatural or stuttered. Stronger prompt control is also highlighted, meaning the model is better at translating detailed text descriptions into accurate visual results. Both of these areas have been active pain points across the broader AI video landscape, and incremental gains here have practical consequences for how usable the output is without manual correction.
Vidu is developed by Shengshu Technology, a Beijing-based AI company that has been building in the video generation space for several years. The model competes in a field that includes tools like Runway, Kling, and Hailuo, all of which are also iterating rapidly on motion fidelity and creative control. Native audio generation, however, remains less common across the field, giving Vidu Q3 a degree of differentiation at this moment.
For users, the practical appeal of native audio is the reduction of pipeline complexity - fewer tools needed to arrive at a shareable video. Whether the audio quality holds up for professional use cases will depend on how well the model handles synchronization, sound design variety, and consistency across different prompt types. Vidu Q3 is available through the Vidu platform at vidu.com, where users can test the model's capabilities directly.
