Wan2.2 is a fully open‑source video foundation model suite with leapfrog performance upgrades. It outperforms its predecessors and remains SOTA. Compatible with consumer‑grade GPUs, it lowers the hardware threshold for high‑end video generation. Strong in both text‑to‑video and image‑to‑video.

Jointly created by Black Forest Labs and Krea, the generated images are as realistic as real shots, with exquisite details, avoiding traditional AI rigidity. As an open‑source model, it's strong and compatible with the Flux.1 ecosystem.

Cross‑turn detail connections and seamless responses. Especially impressive image editing: integrates conversation context to precisely grasp subtle needs. Understands both text and images to bridge creativity and implementation.

A dimension‑reducing strike for video acceleration. Excels at dynamic logic recognition and smoothing transitions with natural light/shadow. Maintains quality for short videos or long materials after acceleration.

Leader in multilingual translation across dozens of languages. Conveys literal meanings, emotions, and cultural memes with rigorous terminology while preserving the original style. Supports mainstream and minority languages.

Benchmark for ultra‑realistic multi‑person digital humans. Handles multi‑person conversation nuances like tone, eye contact, micro‑expressions, and coherent logic — aligned with real social interactions.

Audio‑conditional latent diffusion with TREPA technology for lip‑movement syncing: natural, precise, and high‑resolution. Reduces blurriness, enhances immersion, and outperforms similar tools.

Unbeatable for super‑resolution and high‑definition facial restoration in videos. Kalman filtering leverages previous frames to guide restoration, improving facial detail accuracy and textures.