AI/TLDR

ComfyUI-LTXVideo

Lightricks' custom ComfyUI nodes and workflows for the LTX-2 video model

Video GenerationOpen source
Language
Python

Overview

ComfyUI-LTXVideo is Lightricks' collection of custom nodes that extends ComfyUI for the LTX-2 video generation model. LTX-2 itself is already built into ComfyUI core, so every ComfyUI user can reach the basic pipeline without this repository; what the node pack adds is the advanced surface — the control adapters, the staged workflows and the example graphs that get more out of the model than the built-in nodes expose.

The headline additions are IC-LoRA control workflows: depth, human pose and edge conditioning, motion tracking on image-to-video, HDR, a Dub-It pass and pixel spatial upscaling, plus a text-to-audio distilled workflow. A Union IC-LoRA combines depth and edge (canny) conditioning into a single adapter, and it operates on a downsampled latent, which cuts memory use and speeds up inference while holding quality. Single-stage and two-stage (upsampling) variants of the text/image-to-video graphs are both shipped.

Everything arrives as example workflow JSON files installed alongside the nodes, so the practical entry point is loading a graph rather than wiring one. The pack is installable from ComfyUI Manager and required model files are fetched on first use. It is hardware-hungry: the project lists a CUDA-compatible GPU with 32GB or more of VRAM and 100GB or more of free disk space for models and cache as prerequisites.

What it does

  • IC-LoRA control workflows for depth, human pose and edge conditioning on LTX-2 generations
  • A Union IC-LoRA that merges depth and canny control into one adapter and runs on a downsampled latent for lower memory use and faster inference
  • Motion-tracking image-to-video, HDR, Dub-It and pixel spatial upscaling workflows
  • Single-stage and two-stage (with upsampling) text/image-to-video graphs for both the full and distilled models
  • A text-to-audio distilled workflow alongside the video graphs
  • Example workflow JSON installed with the nodes, and models downloaded automatically on first use

Getting started

Install from ComfyUI Manager rather than cloning by hand, then load one of the bundled example workflows. Check the hardware requirements first — this is a large-model pipeline, not a laptop node pack.

Check the prerequisites

You need ComfyUI installed, a CUDA-compatible GPU with 32GB+ VRAM, and 100GB+ of free disk space for models and cache.

Install the nodes from ComfyUI Manager

Open ComfyUI, press Ctrl+M for the Manager, choose Install Custom Nodes, search for “LTXVideo”, install, and restart ComfyUI. The nodes then appear in the node menu under the LTXVideo category.

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Manager (Ctrl+M) → Install Custom Nodes → search "LTXVideo" → Install → restart

Load an example workflow

The installation ships several ready-made graphs; the recommended starting point is one of the LTX-2 workflows available through Comfy Manager. Required models download on first use.

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ComfyUI/custom_nodes/ComfyUI-LTXVideo/example_workflows/

Move up to the control workflows

Once text-to-video works, switch to the IC-LoRA graphs for depth, pose and edge control, motion tracking, HDR or spatial upscaling — and use the two-stage distilled workflow when you want the upsampling pass.

Commands and code are distilled from the project's own documentation — always check the official repo for the latest.

When to use it

  • Drive an LTX-2 generation with depth, pose or edge control instead of prompt text alone
  • Add an upsampling second stage to a distilled LTX-2 run when the single-stage output is not sharp enough
  • Use one Union IC-LoRA for depth and canny control to keep VRAM use and inference time down
  • Start from a maintained example graph rather than reverse-engineering the model's node wiring yourself

How ComfyUI-LTXVideo compares

ComfyUI-LTXVideo alongside other open-source video generation tools AI/TLDR tracks, ranked by GitHub stars.

ToolStarsWhat it does
MoneyPrinterTurbo★ 125kA self-hosted WebUI, API and CLI that turns one topic or keyword into a finished short video — script, stock or generated footage, voiceover, subtitles and music.
OpenMontage★ 60.4kAn agentic video production system that gives a coding assistant 12 pipelines and 100+ tools to research, script, generate and render a video end to end.
HyperFrames★ 51.9kHeyGen's HTML-to-video renderer: author a composition in HTML, CSS and JS, preview it in a browser, then render the same input to a deterministic MP4 locally or on AWS Lambda.
Toonflow★ 15.8kInfinite-canvas workbench for AI short-drama production, taking a novel through chapter events, script, storyboards and video nodes.
Palmier Pro★ 14.4kA Swift-native macOS video editor with generative models in the timeline and a built-in MCP server, so Claude, Codex or Cursor can edit the open project alongside you.
Hypit★ 11.8kA markup language and compiler that lets a coding agent rebuild a reference video as an editable workflow — footage, captions, B-roll and effects anchored to words rather than timestamps — and render variants in one command.
LTX-2★ 9.5kLightricks' official inference package for its LTX-2 audio-video model: a dozen pipelines covering text/image-to-video, keyframe interpolation, audio-to-video, retakes, dubbing and HDR/EXR, plus a LoRA trainer.
ComfyUI-LTXVideo★ 4.1kLightricks' custom ComfyUI nodes and workflows for the LTX-2 video model