AI Video Upscaler uses AI to improve the resolution and visual quality of low-resolution or blurry video clips. It offers 2× or 4× resolution upscaling, as well as diffusion-model enhancement with frame-level temporal consistency. Processing is limited to 30 seconds per clip; input resolution cannot exceed 7680×4320.
Which model type to use
Multiplier upscaling models
- Choose 2× or 4× scale factor
- Preserves sharp edges and detail texture
- Faster processing
- Good for marketing videos and e-commerce product shots
- Maximum output: 8K
Diffusion enhancement models
- Deep-learning photorealistic enhancement
- Target resolution: HD (up to 1080p) or 4K (up to 2160p)
- Adjustable target frame rate (15–60 fps)
- Frame-to-frame temporal consistency — smoother motion
- Best for cinematic footage and archival material restoration
Frame rate: when to raise it and when not to
Diffusion enhancement models support a target frame rate (default 30 fps, range 15–60 fps). Raising the frame rate makes motion smoother, but significantly increases processing time and credit cost. The target frame rate should not be lower than the source video's frame rate, or the output may drop frames. Common choices: social short-form video — 30 fps; smooth slow-motion effect — 60 fps; cinematic footage — keep the original 24 fps.
When 4K upscaling actually helps
4K output is not always meaningful. If the final display is a phone screen or a standard monitor, HD (1080p) is usually sufficient. The 4K advantage becomes visible on large screens, LED walls, and projected output. For source video at very low resolutions (240p or 360p), 4× upscaling may introduce unnatural texture artifacts — test with 2× first.
Output quality slider
The quality parameter ranges from 20 to 99 and controls compression rate. Higher values mean better quality and larger file size. 95 is a sensible default that balances quality with size. Set it to 99 if the output will go into further editing. For social platform uploads, 85–90 is usually sufficient.
Before you submit
After uploading, the interface displays the source resolution, duration, and expected output resolution. Verify these values before starting the task to avoid wasting credits on an incorrect configuration. The task runs asynchronously — results appear in the history panel when complete.