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AEmotionStudio
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ai-upscale-models

Image-to-Image
spandrel
image-super-resolution
super-resolution
upscaling
real-esrgan
hat
swinir
comfyui
ffmpega
video-processing
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metadata 
library_name: spandrel
license: other
license_name: mixed
license_link: LICENSE
tags:
  - image-super-resolution
  - super-resolution
  - upscaling
  - real-esrgan
  - hat
  - swinir
  - comfyui
  - ffmpega
  - video-processing
pipeline_tag: image-to-image

AI Upscale Models for FFMPEGA

Pre-trained super-resolution models for use with ComfyUI-FFMPEGA's AI Upscale feature.

Models are automatically downloaded on first use — no manual setup required.

Models

File Architecture Scale Size VRAM Best For
RealESRGAN_x4plus.pth RRDBNet (GAN) 4× 67 MB ~2 GB General real-world photos
RealESRGAN_x4plus_anime_6B.pth RRDBNet (compact) 4× 18 MB ~1 GB Anime, cartoon, illustration
Real_HAT_GAN_SRx4.pth HAT (hybrid attention) 4× 170 MB ~4 GB SOTA quality, fine detail
003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth SwinIR-Large 4× 48 MB ~3 GB Clean images, classical SR

All models output 4× resolution. For 2× output, the upscaler runs at 4× then applies high-quality Lanczos downscaling.

Usage in FFMPEGA

  1. Set llm_model → none
  2. Set no_llm_mode → ai_upscale
  3. Choose upscale_model (e.g. hat_x4 for best quality)
  4. Choose upscale_scale (4 or 2)
  5. Connect an image or video input and run

Model Loading

Models are loaded via spandrel, which auto-detects the architecture from the checkpoint file. No additional dependencies are needed beyond what ComfyUI already provides.

Credits