Installation Guide
Complete setup instructions for LTX Video Generator.
Table of contents
- Download the App
- Configure Python
- First Run - Model Download
- Optional: Gemma Prompt Enhancement
- Verify Installation
- Installing Python
- Troubleshooting
Download the App
- Go to the Releases page
- Download the latest
.dmgfile - Open the DMG and drag LTX Video Generator to your Applications folder
- Right-click the app and select Open (required for first launch of notarized apps)
Configure Python
LTX Video Generator needs Python 3.10+ with MLX and related packages.
Step 1: Open Preferences
- Launch LTX Video Generator
- Open Preferences (⌘,)
- Click Auto Detect to find your Python installation
The app will search common locations including Homebrew, pyenv, conda, and system Python.
Step 2: Validate Setup
Click Validate Setup to check for required packages:
mlx- Apple’s machine learning frameworkmlx-vlm- Vision-language models for MLXmlx-video-with-audio- Unified audio-video generation (LTX-2)transformers- Hugging Face transformerssafetensors- Fast tensor serializationhuggingface_hub- Model downloadingnumpy- Numerical computingopencv-python- Video encodingtqdm- Progress bars
Step 3: Install Missing Packages
If packages are missing, you have two options:
Option A: One-Click Install (Recommended)
Click the Install Missing Packages button in Preferences. The app will run pip install automatically.
Option B: Manual Install
pip install mlx mlx-vlm mlx-video-with-audio transformers safetensors huggingface_hub numpy opencv-python tqdm
If using a virtual environment, make sure to activate it first, or point the app to the venv’s Python executable.
First Run - Model Download
Important: On your first generation, the app will download the LTX-2 Unified model (~42GB) from Hugging Face. This is a one-time download.
What to Expect
- Start a generation with any prompt
- Progress shows “Downloading model…” with percentage
- Download takes 30-60 minutes depending on connection speed
- Model is cached in
~/.cache/huggingface/hub/ - Subsequent runs skip the download
Download Progress
The app shows real-time download progress:
Downloading: 8.4GB / 42GB (20%)
If download is interrupted, it will resume from where it left off.
Storage Location
Models are cached by Hugging Face in:
~/.cache/huggingface/hub/models--notapalindrome--ltx2-mlx-av/
To free up space later, you can delete this folder (the model will re-download on next use).
Optional: Gemma Prompt Enhancement
For better results, enable Settings > Generation > Enable Gemma Prompt Enhancement. Gemma rewrites your prompts with vivid details before generation.
If prompts with certain words (e.g. medical terms) return empty enhancement, enable Use uncensored enhancer. First run downloads ~7GB (TheCluster/amoral-gemma-3-12B-v2-mlx-4bit).
Verify Installation
To verify everything is working:
- Enter a simple prompt:
"A river flowing through a forest" - Use the Quick Preview preset (512x320, 49 frames)
- Click Generate
- Watch progress in the Queue sidebar
- Your video should appear when complete
Installing Python
If you don’t have Python installed, here are your options:
Homebrew (Recommended)
brew install python@3.12
Python will be at /opt/homebrew/bin/python3.12
pyenv
# Install pyenv
brew install pyenv
# Install Python
pyenv install 3.12
# Set as default
pyenv global 3.12
System Python
macOS includes Python, but you may need to install Xcode Command Line Tools:
xcode-select --install
Troubleshooting
“Python not found”
- Click Auto Detect in Preferences
- Or manually enter the path to your Python executable
- Verify it exists:
which python3
“Missing packages” after install
- Make sure you’re using the same Python the app is configured to use
- Try:
/path/to/your/python3 -m pip install mlx mlx-vlm mlx-video-with-audio transformers safetensors huggingface_hub numpy opencv-python tqdm
“Out of memory” during generation
- Use smaller resolution (512x320)
- Reduce frame count
- Close other applications
- 32GB RAM minimum required
See the Troubleshooting Guide for more solutions.