Quick Start

Let’s get started generating video with LTX-2.5.

Choose Your Workflow

There are two ways to run LTX-2.5 locally. We recommend ComfyUI for the fastest way to go from zero to a generated clip using the ready-made LTX-2.5 templates. If you’re integrating LTX into code or an automated pipeline, use the Python pipelines instead.

ComfyUI Quick Start

ComfyUI provides an intuitive node-based interface with ready-made LTX-2.5 templates. If you haven’t installed ComfyUI yet, download it from comfy.org/download.

1. Install the LTX nodes

Recommended: ComfyUI Manager

1. Launch ComfyUI and open ComfyUI Manager
2. Search for “LTXVideo”
3. Click Install on the ComfyUI-LTXVideo node pack
4. Restart ComfyUI

Alternative: Manual installation

$
git clone https://github.com/Lightricks/ComfyUI-LTXVideo.git
$
cd ComfyUI-LTXVideo
$
uv sync --frozen
$
source .venv/bin/activate

For portable/embedded installations:

$
.\python_embeded\python.exe -m pip install -r .\ComfyUI\custom_nodes\ComfyUI-LTXVideo\requirements.txt

2. Generate your first video

1. Open ComfyUI’s template browser and pick an LTX-2.5 template (start with Text-to-Video if you’re new):
   • Text-to-Video — generate from a text prompt.
   • Image-to-Video — animate from a starting image.
   • First-Frame / Last-Frame — generate the motion between a start and end frame.
2. When prompted, download the model files the template needs. The Workflow Overview panel (or ComfyUI Manager) fetches anything missing.
3. Enter your prompt or add your references image(s).
4. Click Queue Prompt to generate.

Generation time depends on your GPU and VRAM.

Pipeline Quick Start

For programmatic use, run LTX-2.5 through the native ltx-pipelines package.

1. Install

$
git clone https://github.com/Lightricks/LTX-2.git
$
cd LTX-2
$
uv sync
$
source .venv/bin/activate

2. Download the models

LTX-2.5 ships as a split pack — one file per component. Grab the files needed; click Agree and Access on the model page on first download:

$
hf auth login
$
$
hf download Lightricks/LTX-2.5 \
>
  diffusion_models/ltx-2.5-22b-distilled-transformer-bf16.safetensors \
>
  text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \
>
  vae/ltx-2.5-video-vae-bf16.safetensors \
>
  vae/ltx-2.5-audio-vae-bf16.safetensors \
>
  model_patches/ltx-2.5-duration-head-bf16.safetensors \
>
  --local-dir models/ltx-2.5
$
$
hf download Lightricks/LTX-2.3 \
>
  ltx-2.3-spatial-upscaler-x2-1.1.safetensors \
>
  --local-dir models/ltx-2.3

3. Generate

$
uv run python -m ltx_pipelines.distilled \
>
    --transformer-path       models/ltx-2.5/diffusion_models/ltx-2.5-22b-distilled-transformer-bf16.safetensors \
>
    --text-encoder-path      models/ltx-2.5/text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \
>
    --video-vae-path         models/ltx-2.5/vae/ltx-2.5-video-vae-bf16.safetensors \
>
    --audio-vae-path         models/ltx-2.5/vae/ltx-2.5-audio-vae-bf16.safetensors \
>
    --duration-head-path     models/ltx-2.5/model_patches/ltx-2.5-duration-head-bf16.safetensors \
>
    --spatial-upsampler-path models/ltx-2.3/ltx-2.3-spatial-upscaler-x2-1.1.safetensors \
>
    --prompt "A golden retriever running through a sunlit meadow" \
>
    --seed 42 \
>
    --output-path output.mp4

Every pipeline runs the same way from the command line — add --help to any module to see its options.

What’s Next?

Now that you have LTX-2.5 running, explore these guides to get the most out of the model:

Getting Help