A VAE for Wan2.1 and Krea2...Inspired by JoeyGambino and his Z-Image + H3/LTX merge/grafting process. Using one of the highest benchmarked VAE currently available as the mathematical basis for modifications to the existing WAN VAE and it's 2x Upscale variant.For the Krea2 Upscale version use this node pack to run it: <a target="_blank" rel="ugc" href="https://github.com/spacepxl/ComfyUI-VAE-Utils">https://github.com/spacepxl/ComfyUI-VAE-Utils</a>minimax version 1 is just a pixel shift modification to the existing VAE. Version 2 adds additional detail and also more accurately matches start-frame input images in detail, colour and lighting.I will work on adding additional details to it if possible.For minimax use this nodepacks vae decode: <a target="_blank" rel="ugc" href="https://github.com/TripleHeadedMonkey/ComfyUI-MiniMaxH3_LatentUpscaler">https://github.com/TripleHeadedMonkey/ComfyUI-MiniMaxH3_LatentUpscaler</a>If the VAE still doesn't work for you (size mismatch error) then download the optional zipfile included and add that to "\ComfyUI\comfy\ldm\minimax\" replace the file <a target="_blank" rel="ugc" href="http://vae.py">vae.py" in this folder.</a>

Hyper_VAE_(Krea2+Minimax)

No additional details added with this version, just upscales the output 2x without needing additional models. Perfect for a resampling workflow.

hyperVAEKrea2Minimax_v10X2UpscaleMinimax.zip

hyperVAEKrea2Minimax_v10X2UpscaleMinimax.safetensors

v1.0_x2_(upscale)_Minimax

v2.0_Minimax_x2_(upscale)

v1.0_x2_(upscale)(krea2)

v1.0(krea2)

This version adds details compared to the original 2x variant I released.

Files with SHA256: 14abf8205a57a6958eb45ef2e2a00cb2642ea821d97ffeb5c0dcd3cbec332106