Media.io AI Video Upscaler vs Real-CUGAN
Media.io AI Video Upscaler
media.ioReal-CUGAN
github.comSide by side
| Figure | Media.io AI Video Upscaler | Real-CUGAN |
|---|---|---|
| Price from | $13.99/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | Yes | — |
| Android | Yes | Yes |
| API | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 7 | 1 |
| Spec score · Video Upscaling Software | 9.2 (#1) | 8.0 (#17) |
| Spec score · AI Video Upscalers | 9.2 (#2) | 8.1 (#12) |
| Support | Media.io says advisors provide live-chat or email support within 24 hours. | The maker invites users to leave suggestions and requests in the repository issues. |
Plans
Media.io AI Video Upscaler
- Free TrialFree
- PremiumFree
- Premium monthly introductory$14 a month
- Premium annual$167.88 a year
- Monthly Credit PlanPrice not published
- Pay As You GoPrice not published
- StandardPrice not published
In their own words
Media.io AI Video Upscaler
Media.io AI Video Upscaler has no write-up on Specifiction yet; its figures are above.
Real-CUGAN
Real-CUGAN is a free AI super-resolution model designed for anime images. It enlarges images by 2×, 3×, or 4× and offers denoising strengths, a conservative mode, and adjustable alpha. The 1× model is still in training. The English README describes five model weights for 2× and three each for 3× and 4×, covering different enhancement strengths. The Windows configuration processes both images and video, and the repository includes a video inference script. A linked NCNN implementation provides Windows, Linux, and macOS executables for Intel, AMD, Nvidia, and Apple-Silicon GPUs using Vulkan; its portable package includes binaries and models and states that it needs no CUDA or PyTorch runtime. Browser options include a demo and a Web-CPU version, though the README says the CPU demo is slow and recommends smaller images. Windows cache and tile settings can trade speed for lower GPU-memory use, including modes intended for very large images. The project also lists PyTorch and VapourSynth use paths and describes its architecture as compatible with Waifu2x-CUNet. The maker invites suggestions and requests through repository issues.