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SPECIFICTION
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NextGenUp vs SeedVR2

NextGenUp

matily.org

SeedVR2

github.com

Side by side

FigureNextGenUpSeedVR2
Price fromFreeFree
Free planYesYes
Free trialYes—
Open source——
WebYes—
WindowsYesYes
macOSYesYes
LinuxYesYes
Self-hostedYesYes
Plans published21
Spec score · AI Video Upscalers8.4 (#8)8.3 (#11)

Plans

NextGenUp

  • FreeFree
  • NextGenUp FreeFree

NextGenUp pricing →

SeedVR2

  • SeedVR2Free

SeedVR2 pricing →

In their own words

NextGenUp

NextGenUp is a free tool for enlarging images and video, available as desktop software for macOS, Windows 10/11 and Linux, or as a self-hosted web app. Processing runs on the user's hardware: its models, FFmpeg and server run locally, and files are not sent to cloud processing. Images can be enlarged to 8K using Quick, Quality, Enhance or Ultra modes; video upscaling reaches 4K through basic and professional AI modes. Enhance reduces noise and blur without enlarging the image, while GFPGAN v1.4 detects faces and restores detail. Real-ESRGAN handles super-resolution. Processing uses the CPU by default and accelerates with a GPU when available. The browser app can use WebGPU on Chrome or Edge 113 and later. The software is MIT licensed and needs no subscription, watermark or account. There is no trial limit. Web files are limited to 2 GB, and older processed files are automatically removed after 24 hours. PNG is the listed output format.

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SeedVR2

SeedVR2 is an open-source model for restoring video at arbitrary resolutions, with a one-step diffusion-transformer approach that does not add a separate diffusion prior. Its official ComfyUI release can upscale both video and images and provides four nodes to control the pipeline. A standalone command-line interface supports batch and multi-GPU workflows. Inputs may be RGB or RGBA images and video; the documented model choices are 3B and 7B, with FP16, FP8, and quantized GGUF options. Model offloading, VAE tiling, and BlockSwap are available to manage memory during inference. The research describes adaptive window attention, which adjusts window size to output resolution, and adversarial post-training for high-resolution restoration. Standalone installation instructions cover Windows, macOS, and Linux, including Apple Silicon MPS support. Input height and width must be multiples of 32, and the demo crops resized inputs to meet that constraint. SeedVR2 is licensed under Apache 2.0, and released inference code and model weights are linked from the repository. The plan is free.

Visit github.com