Side by side
Krea Enhancer vs Real-ESRGAN
Both stand on image upscaling software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan APIiPhoneSelf-hosted+1
Choose Krea Enhancer if you need AI image sharpening and upscaling with batch processing, several supported formats, or API access. The free plan has limited enhancements and a 2K basic-upscaling ceiling; paid plans raise the listed resolution support and provide larger compute allowances.
Visit Krea Enhancer Free plan Open source LinuxMacSelf-hosted+2
Real-ESRGAN offers restoration models, portable executables and a Python implementation with broader scaling options. Choose the implementation with its feature limits and runtime requirements in mind.
Visit Real-ESRGANThe facts
| Krea Enhancer | Real-ESRGAN | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Yes |
| Runs on | API, iPhone, Self-hosted, Web | Linux, Mac, Self-hosted, Web, Windows |
| Lowest paid plan | See the plans | Not published |
| Plans published | 7 | None |
| Maker | Not published | Not published |
| Website | krea.ai | github.com |
| On image upscaling software | #4 of 99 | #1 of 99 |
Krea Enhancer: what it does well
- Accepts PNG, JPEG, WebP, HEIC, and HEIF.
- Supports batch processing and API access.
- Free online enhancements do not require sign-up or a card.
- Paid upscaling plans list support up to 22K.
- Enhanced images may be used commercially.
What to know first
- Free plan basic upscaling is limited to 2K resolution.
- Free use is limited to a number of enhancements.
- Business is limited to up to 50 included seats.
Real-ESRGAN: what it does well
- Models cover general images, anime images and animation video.
- Portable inference offers 2×, 3× and 4× scaling.
- Supports alpha-channel, grayscale and 16-bit images.
- Portable builds include binaries and models.
- Training code supports fine-tuning on user or paired data.
What to know first
- Portable builds omit some Python inference features.
- Python implementation requires Python 3.7 or newer.
- Python implementation requires PyTorch 1.7 or newer.
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