---
pipeline_tag: image-to-video
tags:
- image-to-video
- text-to-video
- video-to-video
- image-text-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-video
- ltxv
- lightricks
pinned: true
language:
- en
- de
- es
- fr
- ja
- ko
- zh
- it
- pt
license: other
license_name: ltx-2-community-license-agreement
license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE
library_name: diffusers
demo: https://app.ltx.studio/ltx-2-playground/i2v
---

**Split version of Split LTX-2 checkpoint - Model/VAE/Audio VAE/Text Encoder**

**Original model Link:** [https://huggingface.co/Lightricks/LTX-2](https://huggingface.co/Lightricks/LTX-2)

**Watch us at Youtube:** [@VantageWithAI](https://www.youtube.com/@vantagewithai)

# LTX-2 Model Card
This model card focuses on the LTX-2 model, codebase available [here](https://github.com/Lightricks/LTX-2).

LTX-2 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model. It brings together the core building blocks of modern video generation, with open weights and a focus on practical, local execution. 

[![LTX-2 Open Source](https://img.youtube.com/vi/8fWAJXZJbRA/maxresdefault.jpg)](https://www.youtube.com/watch?v=8fWAJXZJbRA)

# Model Checkpoints

| Name                           | Notes                                                                                                          |
|--------------------------------|----------------------------------------------------------------------------------------------------------------|
| ltx-2-19b-dev                  | The full model, flexible and trainable in bf16                                                                 |
| ltx-2-19b-dev-fp8              | The full model in fp8 quantization                                                                             |
| ltx-2-19b-dev-fp4              | The full model in nvfp4 quantization                                                                           | 
| ltx-2-19b-distilled            | The distilled version of the full model, 8 steps, CFG=1                                                        |
| ltx-2-19b-distilled-lora-384   | A LoRA version of the distilled model applicable to the full model                                             |
| ltx-2-spatial-upscaler-x2-1.0  | An x2 spatial upscaler for the ltx-2 latents, used in multi stage (multiscale) pipelines for higher resolution |
| ltx-2-temporal-upscaler-x2-1.0 | An x2 temporal upscaler for the ltx-2 latents, used in multi stage (multiscale) pipelines for higher FPS       |

## Model Details
- **Developed by:** Lightricks
- **Model type:** Diffusion-based audio-video foundation model
- **Language(s):** English

# Online demo
LTX-2 is accessible right away via the following links:
- [LTX-Studio text-to-video](https://app.ltx.studio/ltx-2-playground/t2v)
- [LTX-Studio image-to-video](https://app.ltx.studio/ltx-2-playground/i2v)

# Run locally

## Direct use license
You can use the models - full, distilled, upscalers and any derivatives of the models - for purposes under the [license](./LICENSE).

## ComfyUI
We recommend you use the built-in LTXVideo nodes that can be found in the ComfyUI Manager. 
For manual installation information, please refer to our [documentation site](https://docs.ltx.video/open-source-model/integration-tools/comfy-ui).

## PyTorch codebase

The [LTX-2 codebase](https://github.com/Lightricks/LTX-2) is a monorepo with several packages. From model definition in 'ltx-core' to pipelines in 'ltx-pipelines' and training capabilities in 'ltx-trainer'.
The codebase was tested with Python >=3.12, CUDA version >12.7, and supports PyTorch ~= 2.7.

## Diffusers 🧨

LTX-2 is supported in the [Diffusers Python library](https://huggingface.co/docs/diffusers/main/en/index) for image-to-video generation.

## General tips:
* Width & height settings must be divisible by 32. Frame count must be divisible by 8 + 1. 
* In case the resolution or number of frames are not divisible by 32 or 8 + 1, the input should be padded with -1 and then cropped to the desired resolution and number of frames.
* For tips on writing effective prompts, please visit our [Prompting guide](https://ltx.video/blog/how-to-prompt-for-ltx-2) 

### 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.
- The model may generate content that is inappropriate or offensive.
- When generating audio without speech, the audio may be of lower quality.

# Train the model

The base (dev) model is fully trainable.

It's extremely easy to reproduce the LoRAs and IC-LoRAs we publish with the model by following the instructions on the [LTX-2 Trainer Readme](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-trainer/README.md).

Training for motion, style or likeness (sound+appearance) can take less than an hour in many settings.