Image-to-Video
LTX-2
GGUF
ltx-2
comfyui
comfy
ltx-video
ltx-2-3
ltx-2.5
ltxv
text-to-video
audio-to-video
video-to-video
Instructions to use RuneXX/LTX-2.3-Workflows with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX-2
How to use RuneXX/LTX-2.3-Workflows with LTX-2:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --extra natten
# Download weights from this repo # Substitute filenames from this repo's "Files and versions" if they differ hf download RuneXX/LTX-2.3-Workflows \ diffusion_models/<distilled-transformer>.safetensors \ text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \ vae/<video-vae>.safetensors \ vae/<audio-vae>.safetensors \ latent_upscale_models/<spatial-upsampler>.safetensors \ latent_upscale_models/<temporal-upsampler>.safetensors \ --local-dir models/LTX-2.3-Workflows # DFR requires the detailing IC-LoRA (separate repo; strength is fixed at 0.5) hf download Lightricks/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler --local-dir models/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler# Distilled LTX-2.5 pipeline (fast) uv run python -m ltx_pipelines.distilled \ --transformer-path models/LTX-2.3-Workflows/diffusion_models/<distilled-transformer>.safetensors \ --text-encoder-path models/LTX-2.3-Workflows/text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \ --video-vae-path models/LTX-2.3-Workflows/vae/<video-vae>.safetensors \ --audio-vae-path models/LTX-2.3-Workflows/vae/<audio-vae>.safetensors \ --spatial-upsampler-path models/LTX-2.3-Workflows/latent_upscale_models/<spatial-upsampler>.safetensors \ --num-frames 121 \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# DFR pipeline (higher detail fidelity; optional temporal 2x/4x) uv run python -m ltx_pipelines.dfr_pipeline \ --transformer-path models/LTX-2.3-Workflows/diffusion_models/<distilled-transformer>.safetensors \ --text-encoder-path models/LTX-2.3-Workflows/text_encoders/gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \ --video-vae-path models/LTX-2.3-Workflows/vae/<video-vae>.safetensors \ --audio-vae-path models/LTX-2.3-Workflows/vae/<audio-vae>.safetensors \ --spatial-upsampler-path models/LTX-2.3-Workflows/latent_upscale_models/<spatial-upsampler>.safetensors \ --temporal-upsampler-path models/LTX-2.3-Workflows/latent_upscale_models/<temporal-upsampler>.safetensors \ --detailing-lora models/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler/ltx-2.5-22b-ic-lora-pixel-spatial-upscaler-x2-1.0.safetensors \ --spatial-upscalings 1 \ --temporal-upscalings 1 \ --height 1088 \ --width 1920 \ --num-frames 121 \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For 4K: --spatial-upscalings 2 --width 3840 --height 2176 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
nvfp4 ?
#25
by lanranjun - opened
Have you ever used the LTX-2.3 NVFP4 version large model? How effective is it?
ltx-2.4 nvfp4 + gemma 12b fp4
Havent used the NVFP4 myself, since my GPU is a bit too old to benefit from that.
But if you have RTX 4xxx or 5xxx it can run well with a much smaller file size.
And Kijai made some input_scaled modes as well that also are for newer graphic cards (Blackwell, RTX 4xxx, 5xxx etc), that can run a lot faster.
https://huggingface.co/Kijai/LTX2.3_comfy/tree/main/diffusion_models
They all do the same thing, so its more about size, and speed.
And if you have the GPU for it worth trying out, specially the input_scaled i saw had some good feedback
RuneXX changed discussion status to closed