# LTX-2
[](https://ltx.io)
[](https://huggingface.co/Lightricks/LTX-2.3)
[](https://console.ltx.video/playground)
[](https://arxiv.org/abs/2601.03233)
[](https://discord.gg/ltxplatform)
**LTX-2** is the first DiT-based audio-video foundation model that contains all core capabilities of modern video generation in one model: synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access.
## 🚀 Quick Start
```bash
# Clone the repository
git clone https://github.com/Lightricks/LTX-2.git
cd LTX-2
# Set up the environment
uv sync --frozen
source .venv/bin/activate
```
### Required Models
Download the following models from the [LTX-2.3 HuggingFace repository](https://huggingface.co/Lightricks/LTX-2.3):
**LTX-2.3 Model Checkpoint** (choose and download one of the following)
* [`ltx-2.3-22b-dev.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-dev.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-dev.safetensors)
* [`ltx-2.3-22b-distilled.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-distilled.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled.safetensors)
**Spatial Upscaler** - Required for current two-stage pipeline implementations in this repository
* [`ltx-2.3-spatial-upscaler-x2-1.0.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.0.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-spatial-upscaler-x2-1.0.safetensors)
* [`ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors)
**Temporal Upscaler** - Supported by the model and will be required for future pipeline implementations
* [`ltx-2.3-temporal-upscaler-x2-1.0.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-temporal-upscaler-x2-1.0.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-temporal-upscaler-x2-1.0.safetensors)
**Distilled LoRA** - Required for current two-stage pipeline implementations in this repository (except DistilledPipeline and ICLoraPipeline)
* [`ltx-2.3-22b-distilled-lora-384.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-distilled-lora-384.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled-lora-384.safetensors)
**Gemma Text Encoder** (download all assets from the repository)
* [`Gemma 3`](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized/tree/main)
**LoRAs**
* [`LTX-2.3-22b-IC-LoRA-Union-Control`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control) - [Download](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control/resolve/main/ltx-2.3-22b-ic-lora-union-control-ref0.5.safetensors)
* [`LTX-2.3-22b-IC-LoRA-Motion-Track-Control`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Motion-Track-Control) - [Download](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Motion-Track-Control/resolve/main/ltx-2.3-22b-ic-lora-motion-track-control-ref0.5.safetensors)
* [`LTX-2-19b-IC-LoRA-Detailer`](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer/resolve/main/ltx-2-19b-ic-lora-detailer.safetensors)
* [`LTX-2-19b-IC-LoRA-Pose-Control`](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Pose-Control) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Pose-Control/resolve/main/ltx-2-19b-ic-lora-pose-control.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Dolly-In`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-In) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-In/resolve/main/ltx-2-19b-lora-camera-control-dolly-in.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Dolly-Left`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Left) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Left/resolve/main/ltx-2-19b-lora-camera-control-dolly-left.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Dolly-Out`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Out) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Out/resolve/main/ltx-2-19b-lora-camera-control-dolly-out.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Dolly-Right`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Right) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Right/resolve/main/ltx-2-19b-lora-camera-control-dolly-right.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Jib-Down`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down/resolve/main/ltx-2-19b-lora-camera-control-jib-down.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Jib-Up`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up/resolve/main/ltx-2-19b-lora-camera-control-jib-up.safetensors)
* [`LTX-2-19b-LoRA-Camera-Control-Static`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static/resolve/main/ltx-2-19b-lora-camera-control-static.safetensors)
### Available Pipelines
* **[TI2VidTwoStagesPipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_two_stages.py)** - Production-quality text/image-to-video with 2x upsampling (recommended)
* **[TI2VidTwoStagesHQPipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_two_stages_hq.py)** - Same two-stage flow as above but uses the res_2s second-order sampler (fewer steps, better quality)
* **[TI2VidOneStagePipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_one_stage.py)** - Single-stage generation for quick prototyping
* **[DistilledPipeline](packages/ltx-pipelines/src/ltx_pipelines/distilled.py)** - Fastest inference with 8 predefined sigmas
* **[ICLoraPipeline](packages/ltx-pipelines/src/ltx_pipelines/ic_lora.py)** - Video-to-video and image-to-video transformations (uses distilled model.)
* **[KeyframeInterpolationPipeline](packages/ltx-pipelines/src/ltx_pipelines/keyframe_interpolation.py)** - Interpolate between keyframe images
* **[A2VidPipelineTwoStage](packages/ltx-pipelines/src/ltx_pipelines/a2vid_two_stage.py)** - Audio-to-video generation conditioned on an input audio file
* **[RetakePipeline](packages/ltx-pipelines/src/ltx_pipelines/retake.py)** - Regenerate a specific time region of an existing video
### ⚡ Optimization Tips
* **Use DistilledPipeline** - Fastest inference with only 8 predefined sigmas (8 steps stage 1, 4 steps stage 2)
* **Enable FP8 quantization** - Enables lower memory footprint: `--quantization fp8-cast` (CLI) or `quantization=QuantizationPolicy.fp8_cast()` (Python). Fp8-cast should be used with bf16 checkpoints, it shall downcast them on the fly. For Hopper GPUs with TensorRT-LLM, use `--quantization fp8-scaled-mm` for FP8 scaled matrix multiplication. Fp8-scaled-mm should be used with fp8 checkpoints.
* **Install attention optimizations** - Use xFormers (`uv sync --extra xformers`) or [Flash Attention 3](https://github.com/Dao-AILab/flash-attention) for Hopper GPUs
* **Use gradient estimation** - Reduce inference steps from 40 to 20-30 while maintaining quality (see [pipeline documentation](packages/ltx-pipelines/README.md#denoising-loop-optimization))
* **Skip memory cleanup** - If you have sufficient VRAM, disable automatic memory cleanup between stages for faster processing
* **Choose single-stage pipeline** - Use `TI2VidOneStagePipeline` for faster generation when high resolution isn't required
## ✍️ Prompting for LTX-2
When writing prompts, focus on detailed, chronological descriptions of actions and scenes. Include specific movements, appearances, camera angles, and environmental details - all in a single flowing paragraph. Start directly with the action, and keep descriptions literal and precise. Think like a cinematographer describing a shot list. Keep within 200 words. For best results, build your prompts using this structure:
- Start with main action in a single sentence
- Add specific details about movements and gestures
- Describe character/object appearances precisely
- Include background and environment details
- Specify camera angles and movements
- Describe lighting and colors
- Note any changes or sudden events
For additional guidance on writing a prompt please refer to
### Automatic Prompt Enhancement
LTX-2 pipelines support automatic prompt enhancement via an `enhance_prompt` parameter.
## 🔌 ComfyUI Integration
To use our model with ComfyUI, please follow the instructions at .
## 📦 Packages
This repository is organized as a monorepo with three main packages:
* **[ltx-core](packages/ltx-core/)** - Core model implementation, inference stack, and utilities
* **[ltx-pipelines](packages/ltx-pipelines/)** - High-level pipeline implementations for text-to-video, image-to-video, and other generation modes
* **[ltx-trainer](packages/ltx-trainer/)** - Training and fine-tuning tools for LoRA, full fine-tuning, and IC-LoRA
Each package has its own README and documentation. See the [Documentation](#-documentation) section below.
## 📚 Documentation
Each package includes comprehensive documentation:
* **[LTX-Core README](packages/ltx-core/README.md)** - Core model implementation, inference stack, and utilities
* **[LTX-Pipelines README](packages/ltx-pipelines/README.md)** - High-level pipeline implementations and usage guides
* **[LTX-Trainer README](packages/ltx-trainer/README.md)** - Training and fine-tuning documentation with detailed guides