Premium tools still have polish, but if you just want to prompt a scene and riff quickly, local is faster to loop and cheaper to keep. I set up LTX on my MacBook and a 4070 box. Here is the exact path so you can do the same without hunting through issues.
You have two parts to care about: a working Python environment with PyTorch, and the LTX-Video repo. GPU on Linux or Windows gives you speed. Apple Silicon runs too using MPS, slower but still useful for drafts.
First grab the code.
bash
git clone https://github.com/Lightricks/LTX-Video && cd LTX-Video
Create a virtual env and install PyTorch that matches your hardware. On an NVIDIA box use CUDA 12.1 wheels, then install the repo deps. If you are on Apple Silicon, install the latest PyTorch build with MPS support and skip CUDA.
Quick verify before you go further. Activate your venv and run a GPU check. If this prints True on NVIDIA, or does not crash on Apple with MPS, you are set for the full steps.
bash
python -c "import torch; print(torch.cuda.is_available())"
Stop here if you only needed proof your box is ready. The full guide covers per-OS setup, expected outputs, config tips like VRAM budgets and frame counts, and fixes for CUDA mismatches, OOM, and missing ffmpeg.
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