LearningStory

Wan 2.2 is a multimodal video generation model developed by Alibaba's Tongyi Laboratory and released in July 2025 under the Apache 2.0 license. It is the first video diffusion model to apply a Mixture-of-Experts (MoE) architecture, which splits processing between high-noise expert networks that handle overall layout and composition and low-noise expert networks that refine fine details. The model supports both text-to-video and image-to-video generation, with native bilingual prompting in English and Chinese. It is available in a 5B parameter variant suited for consumer hardware and a 14B parameter variant for higher-quality output.

Wan 2.5 is an open-source AI video generation model developed by Alibaba's DAMO Academy. It generates videos up to 10 seconds long at resolutions ranging from 480p to 1080p HD, with native 4K available in preview, all rendered at 24 frames per second. The model's defining characteristic is its ability to generate audio and video simultaneously in a single step — producing character dialogue with lip-sync, environmental ambient sounds, and background music directly from a text or image prompt, without requiring separate post-production audio work. It supports multiple input modes including text-to-video, image-to-video, audio-to-video, and video-to-video refinement.

Wan 2.6 is a video generation model developed by Alibaba that produces 1080p video at 24 frames per second for clips up to 15 seconds in length. It accepts text, image, or video as input and generates complete video output — including synchronized audio, dialogue, sound effects, and lip movements — in a single generation pass, without requiring a separate audio pipeline. The model was trained with a cutoff of December 2025 and is available as an open-source release.

Seedance 2.0 generates Hollywood-grade cinematic videos from text prompts with native audio-visual synchronization, director-level camera and lighting control, and exceptional motion stability. Built on Seed's unified multimodal architecture, it leads on instruction adherence, motion quality, and visual aesthetics.