关于 AI Video Generator 模型
It brings together the world's best video generation models, including text-to-video, image-to-video, and video editing capabilities.
全部 AI Video Generator 模型
kling/kling-v3-i2v
[Core Function] Kling V3 I2V is the next-generation image-to-video model. [Strengths] It transforms static images into video with support for 4K resolution, 15-second durations, and native audio, providing superior motion and character expressiveness. [Best For] Highly recommended for: animating concept art, bringing portraits to life in 4K, and generating long 15s scenes from a single frame. [Limitations] Do NOT use this model if you need multimodal reference elements (like character consistency across shots) or multi-shot generation; use V3 Omni instead. [Routing] Use this model by default for high-quality single-image-to-video tasks.
kling/kling-v3-t2v
[Core Function] Kling V3 T2V is the next-generation text-to-video base model. [Strengths] It natively supports generating ultra-long 15-second videos, 4K resolution, and synchronized native audio directly from text. [Best For] Highly recommended for: high-end cinematic creation, 4K video generation, and creating long-form scenes with integrated sound. [Limitations] Do NOT use this model if you need complex multi-shot narratives or deep physics reasoning; use V3 Omni or Video O1 respectively. [Routing] Use this model by default for high-quality text-to-video tasks that require up to 15 seconds, 4K resolution, or native audio without reference images.
alibaba/wan2.7-videoedit
[Core Function] Wan 2.7 Video Editing is an instruction-based video modification model. [Strengths] It supports complex video editing tasks like content replacement using reference images, and replicating actions, effects, and camera movements. [Best For] Highly recommended for: modifying existing video footage, style transfer on videos, and targeted element replacement. [Limitations] Do NOT use this model to generate a brand new video from scratch; it requires an input video. [Routing] Use this model by default whenever a user wants to edit, alter, or restyle an existing video.
alibaba/wan2.7-r2v
[Core Function] Wan 2.7 Reference-to-Video is a highly capable character/entity reference video model. [Strengths] It natively supports entity reference, voice customization, and playbook-based video generation from a single storyboard. [Best For] Highly recommended for: creating consistent video series, brand mascot animation, and storyboard-driven storytelling. [Limitations] Do NOT use this model for simple, single-image direct animation (use I2V instead). [Routing] Use this by default for complex character consistency and storyboard generation tasks on Alibaba.
bytedance/seedance-2.0-v2v
[Core Function] Seedance 2.0 V2V is ByteDance's flagship multimodal video-to-video model. [Strengths] It allows powerful editing and stylization of input videos by supporting mixed references (text, images, video, and audio) and producing multi-shot 15s outputs. [Best For] Highly recommended for: complex video-to-video transformations, restyling existing footage, and creating dynamic multi-shot edits. [Limitations] Do NOT use this model for simple still-image generation (use Seedream instead). [Routing] Use this model by default for any video editing or video-to-video generation tasks.
bytedance/seedance-2.0-i2v
[Core Function] Seedance 2.0 I2V is ByteDance's flagship unified multimodal video generation model. [Strengths] It supports complex mixed references (multiple images, audio clips) and generates up to 15s of multi-shot audio-video output with dual-channel audio. [Best For] Highly recommended for: high-end complex video generation, multi-shot narratives, and mixed-reference cinematic production. [Limitations] Do NOT use this model if you only need a very basic legacy generation without complex references. [Routing] Use this model by default for any complex, multi-reference, or high-fidelity image-to-video tasks.
