Vidu: Vidu Q2 Pro Fast Start-End to Video API

Vidu Q2 Pro Fast Start-End to Video is a professional accelerated start-end frame-driven video generation model of the Q2 series developed by Shengshu Technology. This model introduces a Fast accelerated inference mechanism on top of the Q2 Pro professional-grade generation capability, aiming to find the optimal balance between professional-level output quality and fast generation speed, providing a differentiated solution for users who pursue both higher video quality and have certain requirements for generation timeliness. Compared to the Q2 Pro standard version, the Fast version significantly reduces generation waiting time through inference acceleration optimization; compared to the pure speed-oriented Turbo version of the same series, the Fast version retains more Pro-level quality characteristics while maintaining relatively fast generation. The model accepts simultaneously provided starting frame and ending frame images, automatically inferring and generating transition video content between the two frames that balances quality and speed. Key capabilities include: Quality-Speed Balanced Start-End Frame Transition Generation: Using the starting and ending frames as dual visual anchor points, generates transition video content that balances visual quality and generation efficiency under an accelerated inference framework. The Fast version introduces inference acceleration optimization on the quality basis of Q2 Pro, significantly improving generation response speed while maintaining acceptable Pro-level visual fidelity, achieving an effective balance between quality and speed. Pro-Level Visual Feature Fidelity in Accelerated Mode: Inherits Q2 Pro's strong fidelity to the visual features of starting and ending frames, still effectively maintaining the consistency of major visual elements in the input dual frames in Fast acceleration mode, including subject features, scene composition, and color style, reducing inter-frame visual drift and ensuring basic visual coherence between generated videos and input frames. Motion Inference Quality in Accelerated Mode: Under the Fast inference acceleration framework, quickly and reasonably infers motion trajectories between starting and ending frames, generating transition dynamic content with acceptable levels of motion fluidity and physical rationality, retaining sufficient motion quality to meet professional application needs under the premise of speed improvement. Text-Assisted Guidance Support: Supports optional text prompt input, using text descriptions to guide transition motion style, content evolution direction, and scene atmosphere between start and end frames, providing basic text controllability within the quality-speed balanced generation framework. Moderate Resource Consumption and Cost-Effectiveness: The Fast version falls between the Q2 Pro standard version and the Turbo version in terms of inference resource consumption and generation cost, suitable for mid-to-high-end commercial application scenarios with certain requirements for both quality and cost that need to balance the two, representing the most prominent value-for-money option among Q2 series start-end frame video generation choices. Typical use cases include professional video content creation with certain timeliness requirements, medium-to-high frequency batch start-end frame animation processing, rapid brand content production and iteration, accelerated storyboard dynamic pre-visualization production, commercial video content production requiring a balance between quality and speed, and professional content creation workflows with moderate budgets.