Klarity
Ranked in AI Video Restoration Software ·Free plan
About
Klarity is a free local tool for restoring images and videos on Linux and Windows. Its modes include denoising, deblurring, upscaling, cleaning, and full restoration, along with frame generation and clean-frame and full-frame generation. It supports JPG, JPEG, PNG, BMP, TIFF, TIF, and WebP images, plus MP4, AVI, MOV, MKV, WebM, FLV, WMV, and M4V videos; video processing requires FFmpeg. Users can work through a graphical interface or interactive and direct command-line modes. Heavy mode downloads about 888 MB of models, while Lite downloads about 204 MB and is described as 20x faster. CPU processing works without a GPU, and the listed minimum requirements are a 2-core CPU, 4 GB RAM, and 2 GB storage. AI models download on first use. Klarity uses NAFNet for denoising and deblurring, Real-HAT-GAN or Real-ESRGAN for upscaling, and RIFE for frame generation. The repository lists an MIT license for Klarity and separate licenses for model components. CPU-only desktop binaries are listed for Linux x86_64 and Windows x86_64.
Who it is for
It suits creators and editors who want local, offline image or video restoration without subscription fees. Both graphical and command-line workflows are available on Linux and Windows.
What is good
- Local and offline processing.
- CPU processing works without a GPU.
- Includes graphical and command-line modes.
- Supports multiple image and video formats.
What to know first
- Video processing requires FFmpeg.
- Heavy mode downloads about 888 MB of models.
- Minimum requirements include 4 GB RAM and 2 GB storage.
- Model components have separate licenses.
Verdict
Klarity offers a broad set of local restoration modes and supports CPU-only processing. Check the FFmpeg requirement for video work and the model downloads and system requirements before choosing it.
Compared on AI video restoration software
- Free plan
- Yesgithub.com
- Platform
- desktopgithub.com
- Maximum upscale
- 4xgithub.com
- Denoising
- Yesgithub.com
- Deblurring
- Yesgithub.com
- Frame interpolation
- Yesgithub.com
Facts
- Purpose
- Klarity is a local, offline AI tool for restoring images and videos through denoising, deblurring, upscaling, and frame generation.github.com · 2 Oct 2026
- Processing modes
- It offers denoise, deblur, upscale, clean, full, frame generation, clean-frame generation, and full-frame generation modes.github.com · 2 Oct 2026
- Model modes
- Heavy mode downloads about 888 MB of models for best quality, while Lite downloads about 204 MB and is described as 20x faster.github.com · 2 Oct 2026
- Interface
- The tool provides a graphical interface and command-line modes, including interactive and direct CLI commands.github.com · 2 Oct 2026
- Supported formats
- It supports JPG, JPEG, PNG, BMP, TIFF, TIF, and WebP images, plus MP4, AVI, MOV, MKV, WebM, FLV, WMV, and M4V videos.github.com · 2 Oct 2026
- Video requirement
- FFmpeg is required for video processing.github.com · 2 Oct 2026
- System requirements
- The README lists minimum requirements of a 2-core CPU, 4 GB RAM, and 2 GB storage; CPU processing works without a GPU.github.com · 2 Oct 2026
- Integrations
- It uses NAFNet for denoising and deblurring, Real-HAT-GAN or Real-ESRGAN for upscaling, and RIFE for frame generation.github.com · 2 Oct 2026
- Offline use
- The maker describes Klarity as local and offline; its release notes say AI models are downloaded on first use.github.com · 2 Oct 2026
- License
- The repository lists Klarity under the MIT license and gives separate licenses for its model components.github.com · 2 Oct 2026
- Download availability
- The latest release page lists CPU-only desktop binaries for Linux x86_64 and Windows x86_64.github.com · 2 Oct 2026
- Support and audience
- The README says Klarity is built for creators, editors, and anyone who needs to enhance visual content without subscription fees.github.com · 2 Oct 2026
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Where it ranks on Inferse
Sources
- github.com/HAKORADev/Klarity· checked 2 Oct 2026
- github.com/HAKORADev/Klarity/releases/tag/v0.7.5.1· checked 2 Oct 2026