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NextGenUp vs REAL Video Enhancer

NextGenUp

matily.org

REAL Video Enhancer

github.com

Side by side

FigureNextGenUpREAL Video Enhancer
Price fromFreeFree
Free planYesYes
Free trialYes—
Open source——
WebYes—
WindowsYesYes
macOSYesYes
LinuxYesYes
Self-hostedYes—
Plans published22
Spec score · AI Video Upscalers8.4 (#8)8.0 (#16)
Spec score · Video Upscaling Software8.4 (#11)8.0 (#18)

Plans

NextGenUp

  • FreeFree
  • NextGenUp FreeFree

NextGenUp pricing →

REAL Video Enhancer

  • REAL Video EnhancerFree
  • Steam donation DLC$2.99, paid once

REAL Video Enhancer 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.

Visit matily.org

REAL Video Enhancer

REAL Video Enhancer is a free application for video interpolation, upscaling, decompression, and denoising on Linux, macOS, and Windows. Interpolation models include RIFE, GMFSS, and IFRNet; the project gives 24-to-48-FPS conversion as an example. Upscaling options include SPAN, OpenProteus, AnimeJaNai, AniSD, and AnimeSR, while DeH264 is listed for decompression and DRUnet and DnCNN for denoising. Scene-change detection helps preserve sharp transitions, and the app previews the latest rendered frame. Compute options include TensorRT for NVIDIA RTX GPUs, PyTorch for CUDA 12.6- or ROCm 6.2-capable GPUs, and NCNN for Vulkan 1.3-capable GPUs. Listed minimums include a dual-core x64 CPU, Vulkan 1.3-capable GPU, and 16 GB RAM; NCNN also requires 4 GB VRAM and 1 GB free storage. TensorRT optimization can fail with limited VRAM; CUDA or NCNN are suggested alternatives. The project is AGPL-3.0 licensed. A Steam donation DLC costs $2.99, paid once and contains no content.

Visit github.com