| tags: | |
| - minimax-h3 | |
| - video | |
| - latent-upscaler | |
| - comfyui | |
| # MiniMax H3 clean-latent 2× upscaler | |
| > [!IMPORTANT] | |
| > **This is not a conventional image or video upscaler.** It is not intended to make a finished render sharper or better-looking, and a direct decode of its output can look softer than the original. Its purpose is to move a clean MiniMax H3 video latent to a 2× larger spatial latent grid very quickly and efficiently, so an H3 workflow can stay in latent space instead of doing a VAE decode → pixel resize → VAE re-encode round trip. Use a conventional pixel-space upscaler when the goal is to enhance a finished video. | |
| The model accepts a fully denoised MiniMax H3 video latent and doubles only its spatial latent dimensions. Temporal length is unchanged; when used through the companion ComfyUI node, the audio latent is preserved unchanged. | |
| ## How it was trained | |
| Training pairs were built from clean H3 latents: each low-resolution latent was decoded with the H3 VAE, enlarged 2× in pixel space with Lanczos, then deterministically re-encoded to provide the teacher latent. The lightweight network learned a correction on top of bilinear latent interpolation using latent and decoder-aware reconstruction, SSIM, spatial-consistency and temporal-consistency losses; the H3 generator itself was not trained or modified. | |
| ## ComfyUI | |
| Use the model with [ComfyUI-H3-Latent-Upscaler-Mamad8](https://github.com/mamad8c/ComfyUI-H3-Latent-Upscaler-Mamad8). Place `h3_clean_latent_upscaler_v1_mamad8.safetensors` in: | |
| ```text | |
| ComfyUI/models/h3_latent_upscalers/ | |
| ``` | |
| The checkpoint supports clean H3 latents only. Do not apply it to intermediate noisy latents. Continuing H3 generation after the resize requires an explicit re-noising and high-resolution continuation workflow. | |