ComfyUI Extension: ComfyUI-FL-LTXTools
Run ComfyUI workflows without the setup
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Experimental tools and motion controls for LTX-Video in ComfyUI
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Custom Nodes (0)
README
FL LTX Tools
Experimental tools and motion controls for LTX-Video in ComfyUI. Designed to drop into existing LTX workflows with minimal wiring.
Features
- Single-knob motion control — one
motion_intensityslider that drives multiple underlying LTX motion levers - VAE decoder noise control — exposes
decode_noise_scaleanddecode_timestepfor per-frame stochasticity - Drop-in replacement for the built-in
LTXVConditioningnode — same conditioning pattern, with motion boost on top - Self-contained — no dependency on other LTX custom node packs
Nodes
| Node | Description | |------|-------------| | FL LTX Motion Boost | Drives motion via conditioning frame_rate (RoPE temporal scale) + VAE decoder noise. Inputs: positive/negative cond + VAE. Outputs: patched cond + VAE. |
Installation
ComfyUI Manager
Search for "FL LTX Tools" and install.
Manual
cd ComfyUI/custom_nodes
git clone https://github.com/filliptm/ComfyUI-FL-LTXTools.git
cd ComfyUI-FL-LTXTools
pip install -r requirements.txt
Quick Start
- Build a normal LTX-Video workflow (model loader, text encode, empty latent, sampler, VAE decode)
- Insert FL LTX Motion Boost between your text encoders and the sampler
- Wire
positive,negative, andvaethrough it - Adjust
motion_intensity(0.0 = static, 0.5 = balanced, 1.0 = chaotic)
How It Works
LTX-Video has no single "motion intensity" knob — motion behavior emerges from the interaction of multiple parameters. This node consolidates the most reliable motion lever (conditioning frame_rate via RoPE temporal embeddings) with VAE-side stochasticity into a single intuitive control.
motion_intensity
Maps to the conditioning frame_rate value:
0.0→ usesbase_frame_rate(default 25 fps) — no motion boost0.5→ ~17 fps — moderate boost (LTX interprets each frame as a larger temporal step)1.0→ ~10 fps — heavy boost, dramatic motion per frame
Lower frame_rate values widen the gaps between RoPE temporal positions, so the model "thinks" each output frame represents a longer time slice. Result: more motion happens between frames.
decode_noise + decode_timestep
VAE decoder noise injection. Adds Gaussian stochasticity at decode time:
- Higher noise → smoother, more organic motion textures
- Lower noise → crisper but potentially jittery output
- LTX defaults:
decode_noise = 0.025,decode_timestep = 0.05
Inputs
| Name | Type | Range | Default | Description |
|------|------|-------|---------|-------------|
| positive | CONDITIONING | — | — | Positive conditioning |
| negative | CONDITIONING | — | — | Negative conditioning |
| vae | VAE | — | — | LTX VAE |
| motion_intensity | FLOAT | 0.0–1.0 | 0.5 | Motion boost amount |
| decode_noise | FLOAT | 0.0–0.5 | 0.025 | VAE decode noise scale |
| decode_timestep | FLOAT | 0.0–0.5 | 0.05 | VAE decode noise timestep |
| base_frame_rate | INT (optional) | 6–60 | 25 | Reference fps before scaling |
| override_frame_rate | INT (optional) | -1, 6–60 | -1 | Set explicit fps, ignore motion_intensity |
Outputs
(positive, negative, vae) — drop into your sampler / VAE decode chain.
Roadmap
More LTX experiments planned. Potential additions:
- STG (Spatiotemporal Skip Guidance) helper
- Motion preset library (cinematic, action, dialogue, etc.)
- Latent noise manipulation utilities
License
Apache-2.0 — Built on top of Lightricks LTX-Video.
Run ComfyUI workflows without the setup
No installs, no CUDA version roulette, no GPU sitting idle on your bill. Bring a workflow and run it in the browser.