⚡ LightVAE

Towards Compact and Efficient Video Autoencoders

Wan2.1 · Wan2.2 · MiniMax-H3

📄 Paper · 💻 Code · 🧩 ComfyUI · ⚡ LightX2V

LightVAE compresses video autoencoders while preserving their original latent interfaces, allowing compressed components to be paired with the corresponding original components.

• Wan2.1 / Wan2.2: Pro and Lite decoders, paired with the original encoder. Pro retains the original decoder depth with temporal low-rank compression; Lite adds block pruning.
• MiniMax-H3: independently block-pruned Lite encoder and decoder, with native ComfyUI integration.
• Optional ConvRot-INT8: a quantized H3 Lite decoder for ComfyUI.

Download the components you need from Files and versions. Keep checkpoints matched to their backbone.

Wan2.2 model selection: 14B models use the Wan2.1 VAE; TI2V-5B uses the Wan2.2 VAE.

🧩 ComfyUI · MiniMax-H3

The Load H3 LightVAE node reuses ComfyUI’s native H3 VAE. No separate LightVAE package installation, TLR or custom Triton kernels are needed. The current node supports H3 only.

1. Install

Use a ComfyUI version with native MiniMax-H3 support. Run these commands in the Python environment that starts ComfyUI:

cd /path/to/ComfyUI

git clone https://github.com/ModelTC/LightVAE.git LightVAE
python LightVAE/comfyui/install.py --comfy-root .

python -m pip install huggingface_hub
hf download lightx2v/LightVAE \
  lightvae-lite-h3-decoder.safetensors \
  lightvae-lite-h3-encoder.safetensors \
  --local-dir models/vae/LightVAE

Already cloned? Run git -C LightVAE pull, then rerun the installer.

The installer creates custom_nodes/ComfyUI-LightVAE/ automatically. Do not clone the entire repository directly into custom_nodes.

The original H3 video VAE is required. Download it if needed:

hf download Comfy-Org/MiniMax-H3 \
  vae/minimax_h3_video_vae_fp16.safetensors \
  --local-dir models

2. Connect

Restart ComfyUI and search for Load H3 LightVAE.

Load the original H3 video VAE with the standard Load VAE node and connect it to base_vae. Select Lite components in Load H3 LightVAE, not in the standard Load VAE node.

• FL2V: replace only the decoder. Leave encoder = none, keep the original VAE connected to first/last-frame encoding, and use LightVAE for VAE Decode.
• REF2V: replace the encoder, decoder, or both. Connect LightVAE to reference encoding and VAE Decode.
• none: use the corresponding original component.

The audio VAE stays unchanged.

Standard H3 checkpoints and our previous *-h3-*-comfy.safetensors exports are both accepted; downloading both formats is unnecessary.

3. Load a workflow

Download a workflow JSON and drag it into ComfyUI:

🎞️ First + last frame · 🖼️ Image references · 🎬 Video reference

Select your model files, upload the inputs and run. These are base-model workflows, not 4-/8-step turbo-LoRA workflows.

See the workflow guide for required diffusion models, text encoders and input preparation.

Optional · ConvRot-INT8 decoder

Update LightVAE, rerun the installer and download the quantized decoder:

hf download lightx2v/LightVAE \
  lightvae-lite-h3-decoder-int8-convrot.safetensors \
  --local-dir /path/to/ComfyUI/models/vae/LightVAE

Restart ComfyUI and select this file in Load H3 LightVAE → decoder. Keep base_vae, encoder selection and audio VAE unchanged.

Native NVIDIA CUDA acceleration requires a CUDA 13.0+ PyTorch build and a compatible driver. Backend support and performance depend on your environment.

This INT8 checkpoint is ComfyUI-only. Use standard, non-INT8 checkpoints with the standalone Python scripts.

🐍 Python · Video Reconstruction

Example: original Wan2.1 encoder + LightVAE-Lite decoder.

git clone https://github.com/ModelTC/LightVAE.git
cd LightVAE
python -m pip install -r requirements.txt

hf download lightx2v/LightVAE \
  lightvae-lite-wan21-decoder.safetensors \
  --local-dir weights/LightVAE

hf download Wan-AI/Wan2.1-T2V-1.3B \
  Wan2.1_VAE.pth --local-dir weights/Wan2.1

python infer.py \
  --model wan21 --variant lite \
  --encoder weights/Wan2.1/Wan2.1_VAE.pth \
  --decoder weights/LightVAE/lightvae-lite-wan21-decoder.safetensors \
  --input demo.mp4 --frames 81 --height 480 --width 832 \
  --output outputs/wan21_lite_recon.mp4

infer.py accepts independent encoder and decoder checkpoints and saves a reconstructed video with a JSON report.

Find Wan2.2 and H3 examples, benchmarks and visual comparisons in LightVAE. For video generation with LightVAE, see LightX2V.

⭐ Support

If LightVAE helps your work, please give LightVAE and LightX2V a star!