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Transform degraded videos into stunning 4K quality with one-step AI restoration powered by ByteDance's diffusion transformer. 10x faster than traditional methods with state-of-the-art quality.
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SeedVR2 is an online AI video and image upscaling workspace that restores low-resolution media to stunning 4K quality using ByteDance's one-step diffusion transformer, available at seedvr2.net.
SeedVR2 is a browser-based AI upscaling platform developed by ByteDance that uses a one-step diffusion transformer model to restore and enhance both images and videos. It accepts JPEG, PNG, WebP images and MP4, WebM videos via drag-and-drop or URL upload, and outputs upscaled, high-quality versions—up to 4K for video and 8K for images. The service is hosted at seedvr2.net, with open-source model weights available under Apache 2.0 on Hugging Face.
The service operates through a web interface: sign in, drag and drop files (or paste a URL), and the platform automatically classifies them into image or video queues. Jobs are processed on ByteDance's servers using the one-step diffusion transformer, producing upscaled outputs that can be downloaded directly. The entire process requires no local GPU or software installation.
SeedVR2 operates on a freemium credit model. New accounts start with 5 credits. Image upscaling costs 10 credits per job, while video upscaling typically requires 165+ credits depending on length and resolution. Additional credits can be purchased via the pricing page.
New accounts receive 5 free credits to try the service. Image upscaling costs 10 credits, video upscaling starts at 165+ credits. There is no free daily credit refresh mentioned on the site; credits are purchased.
It supports JPEG, PNG, and WebP for images, and MP4 and WebM for videos.
You can upload up to 1000 images or 100 videos per batch, with a total file size limit of 2 GB.
The model is open-source under Apache 2.0 and available on GitHub and Hugging Face. You can run it locally with sufficient GPU resources, or use the web service for convenience.
It performs restoration in a single forward pass, making it approximately 10x faster than multi-step diffusion methods while maintaining comparable or better quality.