lucataco / ltx-video-0.9.8-distilled

Generate native long-form video, with controllability

  • Public
  • 176 runs
  • Weights
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Run time and cost

This model costs approximately $0.16 to run on Replicate, or 6 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia H100 GPU hardware. Predictions typically complete within 103 seconds. The predict time for this model varies significantly based on the inputs.

Readme

LTX-Video 0.9.8 13B Distilled Model Card

This model card focuses on the model associated with the LTX-Video model, codebase available here.

LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 30 FPS videos at a 1216×704 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content.

Models & Workflows

Name Notes inference.py config ComfyUI workflow (Recommended)
ltxv-13b-0.9.8-dev Highest quality, requires more VRAM ltxv-13b-0.9.8-dev.yaml ltxv-13b-i2v-base.json
ltxv-13b-0.9.8-mix Mix ltxv-13b-dev and ltxv-13b-distilled in the same multi-scale rendering workflow for balanced speed-quality N/A ltxv-13b-i2v-mixed-multiscale.json
ltxv-13b-0.9.8-distilled Faster, less VRAM usage, slight quality reduction compared to 13b. Ideal for rapid iterations ltxv-13b-0.9.8-distilled.yaml ltxv-13b-dist-i2v-base.json
ltxv-2b-0.9.8-distilled Smaller model, slight quality reduction compared to 13b distilled. Ideal for light VRAM usage ltxv-2b-0.9.8-distilled.yaml N/A
ltxv-13b-0.9.8-fp8 Quantized version of ltxv-13b ltxv-13b-0.9.8-dev-fp8.yaml ltxv-13b-i2v-base-fp8.json
ltxv-13b-0.9.8-distilled-fp8 Quantized version of ltxv-13b-distilled ltxv-13b-0.9.8-distilled-fp8.yaml ltxv-13b-dist-i2v-base-fp8.json
ltxv-2b-0.9.8-distilled-fp8 Quantized version of ltxv-2b-distilled ltxv-2b-0.9.8-distilled-fp8.yaml N/A
ltxv-2b-0.9.6 Good quality, lower VRAM requirement than ltxv-13b ltxv-2b-0.9.6-dev.yaml ltxvideo-i2v.json
ltxv-2b-0.9.6-distilled 15× faster, real-time capable, fewer steps needed, no STG/CFG required ltxv-2b-0.9.6-distilled.yaml ltxvideo-i2v-distilled.json

Model Details

  • Developed by: Lightricks
  • Model type: Diffusion-based image-to-video generation model
  • Language(s): English

Usage

Direct use

You can use the model for purposes under the license: - 2B version 0.9: license - 2B version 0.9.1 license - 2B version 0.9.5 license - 2B version 0.9.6-dev license - 2B version 0.9.6-distilled license - 13B version 0.9.7-dev license - 13B version 0.9.7-dev-fp8 license - 13B version 0.9.7-distilled license - 13B version 0.9.7-distilled-fp8 license - 13B version 0.9.7-distilled-lora128 license - 13B version 0.9.7-ICLoRA Depth license - 13B version 0.9.7-ICLoRA Pose license - 13B version 0.9.7-ICLoRA Canny license - Temporal upscaler version 0.9.7 license - Spatial upscaler version 0.9.7 license - 13B version 0.9.8-dev license - 13B version 0.9.8-dev-fp8 license - 13B version 0.9.8-distilled license - 13B version 0.9.8-distilled-fp8 license - 2B version 0.9.8-distilled license - 2B version 0.9.8-distilled-fp8 license - 13B version 0.9.8-ICLoRA detailer license - Temporal upscaler version 0.9.8 license - Spatial upscaler version 0.9.8 license

General tips:

  • The model works on resolutions that are divisible by 32 and number of frames that are divisible by 8 + 1 (e.g. 257). In case the resolution or number of frames are not divisible by 32 or 8 + 1, the input will be padded with -1 and then cropped to the desired resolution and number of frames.
  • The model works best on resolutions under 720 x 1280 and number of frames below 257.
  • Prompts should be in English. The more elaborate the better. Good prompt looks like The turquoise waves crash against the dark, jagged rocks of the shore, sending white foam spraying into the air. The scene is dominated by the stark contrast between the bright blue water and the dark, almost black rocks. The water is a clear, turquoise color, and the waves are capped with white foam. The rocks are dark and jagged, and they are covered in patches of green moss. The shore is lined with lush green vegetation, including trees and bushes. In the background, there are rolling hills covered in dense forest. The sky is cloudy, and the light is dim.

Online demo

The model is accessible right away via the following links: - LTX-Studio image-to-video (13B-mix) - LTX-Studio image-to-video (13B distilled) - Fal.ai image-to-video (13B full) - Fal.ai image-to-video (13B distilled) - Replicate image-to-video

ComfyUI

To use our model with ComfyUI, please follow the instructions at a dedicated ComfyUI repo.

Limitations

  • This model is not intended or able to provide factual information.
  • As a statistical model this checkpoint might amplify existing societal biases.
  • The model may fail to generate videos that matches the prompts perfectly.
  • Prompt following is heavily influenced by the prompting-style.