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

Set llm_model → none
Set no_llm_mode → ai_upscale
Choose upscale_model (e.g. hat_x4 for best quality)
Choose upscale_scale (4 or 2)
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

Real-ESRGAN: xinntao/Real-ESRGAN — BSD-3-Clause
HAT: XPixelGroup/HAT — MIT
SwinIR: JingyunLiang/SwinIR — Apache 2.0

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