3 steps Diffusion steps at full resolution
4 K Native output, from 768P to 4K
5–15 s Supported refine length
5.0 × Faster than the official API · single B200
Abstract
Open-H3-Regenerate-2K keeps the H3 transformer and video VAE frozen and adds one refiner LoRA, trained like Stage I of SoL-Refiner on real high-resolution clips paired with degraded copies of themselves. At inference the draft is encoded once; H3-Latent-Upscaler, a community 3D-convolutional network, enlarges the latent straight onto the target grid, with no decode and re-encode; the enlarged latent is re-noised to σ = 0.909 and denoised in three Euler steps (0.909 → 0.857 → 0.667 → 0) with classifier-free guidance off, so each step is one transformer call at full resolution. For these few steps the refiner is merged with LightX2V ’s FL2VA Turbo and the LMS Sharp adapter into a single LoRA.