Image-Text-to-Video
Diffusers
image-to-video
text-to-video
video-to-video
audio-to-video
text-to-audio
video-to-audio
audio-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
ltx-2
ltx-2-3
ltx-video
ltxv
lightricks
Instructions to use rzgar/LTX-2.3-Cinematic-VAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rzgar/LTX-2.3-Cinematic-VAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rzgar/LTX-2.3-Cinematic-VAE", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
A custom VAE for LTX-Video 2.3 that bakes a cinematic color grade directly into the decoder. It applies a subtle, darker greenish-teal tint to the output, evoking a soft, cinematic "The Matrix" like aesthetic. Because the color grade is baked into the VAE weights, it eliminates the need for post-processing color correction, giving you the final cinematic look straight out of generation.
Left: Default | Right: This VAE
Files
| File | Direct Link |
|---|---|
| LTX23_video_vae_bf16_cinematic.safetensors | Download |
Usage
- Simply save the VAE in ComfyUI
models/vaefolder. - If you’re using monolithic checkpoints, use the KJ VAE Loader.

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Model tree for rzgar/LTX-2.3-Cinematic-VAE
Base model
Lightricks/LTX-2.3