Best ESRGAN Alternatives ranked by AI · updated Aug 2026

ESRGAN is an open-source deep-learning model for enhancing low-resolution images, especially photographs and textures. It is aimed at developers and technical users who want high-quality image super-resolution through code or custom pipelines.

Developer: Xintao Wang and contributors Price: Free 🎯 github.com/xinntao/ESRGAN

🤖 AI 🔓 Open Source image upscaling super resolution

Top 6 ESRGAN alternatives

Real-ESRGAN

Xintao Wang and contributors

💡 Pick it for a more practical and robust successor to ESRGAN on real-world images.

Real-ESRGAN is an open-source image restoration and upscaling model that can enhance anime frames, artwork, and general photographs. It is primarily a...

Pros

Usually recovers more apparent detail than real-time Anime4K shaders
Works well for anime frames, illustrations, and low-resolution images
Open-source and available for local GPU or CPU processing

Cons

Not designed for low-latency real-time video playback
Can hallucinate or alter details in heavily compressed footage
Command-line use is less approachable without a front end

Free

Alternatives to Real-ESRGAN → Visit site

Upscayl

💡 Choose it when you want ESRGAN-like local upscaling without command-line setup.

Upscayl is a free, open-source desktop application for enlarging and enhancing images with AI models. It is intended for artwork, screenshots, textures,...

Pros

Much easier to use for still images than configuring Anime4K shaders
Free, open-source, and available for major desktop platforms
Includes several models for different image types

Cons

Does not provide real-time video playback upscaling
Video users must extract and recombine frames separately
Requires a compatible GPU for the best performance

Free

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Topaz Gigapixel

Topaz Labs

💡 Pick it for a polished commercial workflow, stronger controls, and support for professional photo enlargement.

Topaz Gigapixel is a desktop AI upscaling application for photographers, artists, and professionals who need high-quality enlargements. It provides dedicated models and...

Pros

Generally stronger detail recovery than simple web resizers
Processes images locally for better privacy and large files
Offers dedicated models for different image characteristics

Cons

Costs more than free browser-based tools
Requires a compatible desktop computer and substantial processing time
More complex than Big Photo for occasional resizing

Paid; pricing varies

Alternatives to Topaz Gigapixel → Visit site

waifu2x

💡 Choose it for anime, manga, and line art where clean edges matter more than photographic texture.

waifu2x is an image scaling and noise reduction software using deep convolutional neural networks.

Free

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SwinIR

Jingyun Liang and contributors

💡 Pick it for transformer-based restoration, denoising, and research flexibility instead of ESRGAN's GAN approach.

SwinIR is an open-source transformer-based image restoration framework supporting super-resolution, denoising, and JPEG artifact reduction. It is aimed at researchers and developers...

Pros

Supports multiple restoration tasks beyond upscaling
Can produce cleaner results on structured and photographic images
Research code and pretrained models are publicly available

Cons

More complex to configure than user-focused upscaling applications
Inference can be slower and more memory intensive
Model selection is less straightforward for casual users

Free

Alternatives to SwinIR → Visit site

Bigjpg

💡 Use it when you want quick browser-based upscaling without installing models or managing GPU dependencies.

Bigjpg is a browser-based AI image upscaler designed for enlarging photos, illustrations, and artwork. It offers specialized processing modes and higher-resolution output...