ltx2-mps
run LTX-2 video generation on mac using MPS (metal).
what's this about
LTX-2 uses float64 for rotary position embeddings, but MPS doesn't support float64. you get this error:
TypeError: Cannot convert a MPS Tensor to float64 dtype as the MPS framework doesn't support float64
this repo patches diffusers to use float32 instead. works fine, no noticeable quality loss.
requirements
- mac with apple silicon (m1/m2/m3/m4)
- python 3.11+
- 64GB+ ram recommended (model is ~40GB)
setup
git clone https://github.com/Pocket-science/ltx2-mps.git
cd ltx2-mps
python3 -m venv venv
source venv/bin/activate
pip install torch torchvision torchaudio
pip install git+https://github.com/huggingface/diffusers.git
pip install transformers accelerate safetensors sentencepiece
pip install imageio imageio-ffmpeg
python patch_mps.py
usage
python generate.py "a cat walking through grass" -o output.mp4
options
| flag | default | description |
|---|---|---|
--width |
512 | video width (divisible by 32) |
--height |
320 | video height (divisible by 32) |
--frames |
25 | frame count (must be 8n+1: 9, 17, 25, 33...) |
--steps |
20 | inference steps |
--guidance |
5.0 | guidance scale |
--fps |
24 | output fps |
--seed |
random | seed for reproducibility |
-n |
"" | negative prompt |
examples
# quick test
python generate.py "sunset over mountains" -o test.mp4 --steps 10
# higher quality
python generate.py "dog running on beach" -o video.mp4 --frames 49 --steps 20 --width 768 --height 448
# max quality (needs 128GB ram, takes ~30 min)
python generate.py "cinematic forest shot" -o hq.mp4 --frames 97 --steps 30 --width 1024 --height 576
performance
tested on m3 ultra:
| resolution | frames | steps | time |
|---|---|---|---|
| 512x320 | 25 | 10 | ~1 min |
| 768x448 | 49 | 20 | ~10 min |
| 1024x576 | 97 | 30 | ~30 min |
how the patch works
two files get patched in diffusers:
diffusers/pipelines/ltx2/connectors.py
# before
freqs_dtype = torch.float64 if self.double_precision else torch.float32
# after
freqs_dtype = torch.float32
diffusers/models/transformers/transformer_ltx2.py
# same change
freqs_dtype = torch.float32
troubleshooting
out of memory - reduce resolution/frames or close other apps
model download fails - it's ~40GB, first run takes a while
import errors - make sure you installed diffusers from git, not pip
credits
- lightricks for ltx-2
- @ivanfioravanti for the mps fix approach
- huggingface for diffusers
license
MIT