Kling AI

Wan2.1 is an open-source suite of advanced video foundation models designed to push the boundaries of video generation. This cutting-edge model excels in various tasks, including Text-to-Video, Image-to-Video, Video Editing, and Text-to-Image, offering state-of-the-art performance across multiple benchmarks. Wan2.1 is compatible with consumer-grade GPUs, making it accessible to a broader audience, and supports multiple languages, including both Chinese and English for text generation. The model's powerful video VAE (Variational Autoencoder) ensures high efficiency and excellent temporal information preservation, making it ideal for generating high-quality video content. Its applications span across entertainment, marketing, and more.

Wan2.2 is a major upgrade to the Wan suite of open video foundation models, introducing a Mixture‑of‑Experts (MoE) architecture that splits the diffusion denoising process across high‑noise and low‑noise expert paths to dramatically increase model capacity without raising inference cost. It harnesses meticulously labeled aesthetic data, covering lighting, composition, contrast, and color tone, to enable precise, controllable cinematic‑style video generation. Trained on over 65 % more images and 83 % more videos than its predecessor, Wan2.2 delivers top performance in motion, semantic, and aesthetic generalization. The release includes a compact, high‑compression TI2V‑5B model built on an advanced VAE with a 16×16×4 compression ratio, capable of text‑to‑video and image‑to‑video synthesis at 720p/24 fps on consumer GPUs such as the RTX 4090. Prebuilt checkpoints for T2V‑A14B, I2V‑A14B, and TI2V‑5B stack enable seamless integration.