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Ai Upscale Models

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KindOtherVersionRevision 01165a1Cgrade

Model source

Kind
Other
File size
17.1–162 MB
Version
vRevision 01165a1
Updated
Oct 20, 2026
Downloads
0
Source
Hugging Face

Source description

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

FileArchitectureScaleSizeVRAMBest For
RealESRGAN_x4plus.pthRRDBNet (GAN)4×67 MB~2 GBGeneral real-world photos
RealESRGAN_x4plus_anime_6B.pthRRDBNet (compact)4×18 MB~1 GBAnime, cartoon, illustration
Real_HAT_GAN_SRx4.pthHAT (hybrid attention)4×170 MB~4 GBSOTA quality, fine detail
003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pthSwinIR-Large4×48 MB~3 GBClean 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

Sources

1 source
Hugging FacePrimaryVersion 01165a13e7472e44e45dbe752653e583cc7f7928
huggingface.co/AEmotionStudio/ai-upscale-models/tree/01165a13e7472e44e45dbe752653e583cc7f7928

Verified Oct 20

Model artifacts

4 artifacts

003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth

pth · 136 MB · SHA-256 99adfa91350a…8c0a · Hugging Face

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Real_HAT_GAN_SRx4.pth

pth · 162 MB · SHA-256 f5b1e3bbbb05…fcc7 · Hugging Face

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RealESRGAN_x4plus_anime_6B.pth

pth · 17.1 MB · SHA-256 f872d837d3c9…99da · Hugging Face

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RealESRGAN_x4plus.pth

pth · 63.9 MB · SHA-256 4fa0d38905f7…82f1 · Hugging Face

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Source excerpts

3 excerpts

--- 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](https://github.com/AEmotionStudio/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](https://github.com/chaiNNer-org/spandrel), which auto-detects the architecture from the checkpoint file. No additional dependencies are needed beyond what ComfyUI already provides. ## Credits - **Real-ESRGAN**: [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) — BSD-3-Clause - **HAT**: [XPixelGroup/HAT](https://github.com/XPixelGroup/HAT) — MIT - **SwinIR**: [JingyunLiang/SwinIR](https://github.com/JingyunLiang/SwinIR) — Apache 2.0

Source context: 0 downloads · 2 likes · Pipeline image-to-image · Library spandrel · Repo AEmotionStudio/ai-upscale-models

Source context: 0 downloads · 1 likes · Pipeline image-to-image · Library spandrel · Repo AEmotionStudio/ai-upscale-models