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+# 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 (GAN) | 4× | 170 MB | ~4 GB | **SOTA** — highest quality |
+| `003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth` | SwinIR-Large | 4× | 142 MB | ~3 GB | Classical SR, clean images |
+
+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