Practical

AI Image Upscaling: From 512px to 4K

Methods and tools for upscaling AI-generated images to print-ready quality.

8 min readUpdated: January 24, 2026
UpscalingESRGANQuality4KResolution

Table of Contents

01Why Upscaling?

Most AI models generate images at relatively low resolution (512x512 to 1024x1024 pixels). For prints, wallpapers, or professional use, you need higher resolutions. Upscaling models can intelligently enlarge images and add details, instead of simply stretching them.

02Upscaling Methods

The most common upscaling approaches:

  • Real-ESRGAN: AI-based upscaling, excellent for photorealistic images. Standard choice for most applications.
  • ESRGAN 4x+: Older but proven model. Many specialized variants for anime, photos, etc.
  • Latent Upscale + KSampler: Upscaling in latent space with re-sampling. Best quality but slower and more VRAM-intensive.
  • Ultimate SD Upscale: Tile-based upscaling with AI post-processing. Good for very high resolutions.
  • Tiled Diffusion: Similar to Ultimate SD but with multidiffusion for more seamless results.

03Upscaling in ComfyUI

In ComfyUI, there are several ways to upscale. The simplest: Add an 'Upscale Image (using Model)' node after the VAE Decode and load an upscale model. For better results: Upscale in latent space, then a second KSampler pass with low denoise (0.3–0.5) for additional details.

04Recommended Upscalers

Depending on image content, we recommend:

  • Photorealistic: RealESRGAN x4plus or 4x-UltraSharp
  • Anime/Illustration: RealESRGAN x4plus-anime or 4x-AnimeSharp
  • General purpose: 4x-NMKD-Superscale – good all-rounder
  • Video frames: RIFE for frame interpolation + Real-ESRGAN for resolution

05Quality Tips

Tip

Generate the base image at the highest possible quality before upscaling. A good 1024x1024 image will always upscale better than a mediocre 512x512. Use the latent upscale workflow for the best quality when VRAM and time allow.

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