Summary
ByteDance’s SeeDance 2.0 is positioned in this Veteran AI review as the most controllable AI video model currently available, supporting up to 12 simultaneous file inputs — a capability that sets it apart from Sora 2 (praised for physical realism but criticized for cost) and Kling (noted for quality but poor instruction-following). The video argues that SeeDance is fundamentally a reference-driven director’s tool rather than a prompt-to-video generator, and that users who approach it without prepared reference assets will struggle regardless of prompt quality.
Five practical test cases demonstrate the model’s range: a physics simulation test checking whether horse hoof sounds change between terrain types (land, grass, swamp); a Coca-Cola advertisement faithfully executing a 200-word shot-by-shot prompt; a fight scene built from character reference images plus a movement reference video rather than detailed motion prompts; a character replacement task that swaps the person in an existing video with a reference image subject; and a storyboard-to-video conversion from an 8-shot script image. All five cases are shown with outputs.
A key syntax detail covered is SeeDance’s @ symbol, which lets users explicitly reference specific uploaded files within prompts — critical for controlling which asset drives which element in multi-input generations. The presenter also outlines two asset-building strategies: using a platform like RunningHub to accumulate generated images over time, and actively saving high-quality video and image references from other platforms for use as SeeDance inputs.
📺 Source: Veteran AI · Published February 11, 2026
🏷️ Format: Review
