AIAny
AI Video2024
GitHub

ComfyUI-LTXVideo

Custom ComfyUI nodes that run Lightricks' LTX-Video diffusion-transformer models for text-to-video and image-to-video, adding IC-LoRA control over depth, pose, edges, and motion plus distilled and low-VRAM variants for node-based workflows.

Introduction

Most open-source video generators make you trade controllability for speed, then bolt control on afterward. Lightricks designed LTX-Video as a diffusion transformer fast enough to iterate on, and these nodes expose that pipeline as a graph where every conditioning signal — a depth map, a pose track, a keyframe — is just another wire.

What Sets It Apart
  • Control as a first-class input, not an afterthought. IC-LoRAs route depth, pose, edge, and motion-tracking signals straight into generation, so you direct a shot instead of rolling the dice on a prompt.
  • A speed/quality dial built into the graph. Distilled model variants and downsampled latent processing trade fidelity for turnaround — rough out a shot cheaply, then re-run the same graph on the full model.
  • Beyond plain text-to-video. The same node set handles two-stage refinement, lipdub/rephrasing, joint audio-video synthesis, and camera-move LoRAs (dolly, jib, static) — production tasks most ComfyUI video packs skip.
  • Memory has an escape hatch. Low-VRAM loader nodes and --reserve-vram keep large models runnable on constrained cards instead of OOM-ing the graph.
Who Should Use It

Great fit if you already live in ComfyUI and want directable, repeatable video — keyframed shots, controlled motion, or audio-synced output you can wire into a larger pipeline. Look elsewhere if you want a one-click app: this assumes comfort with node graphs, and the full LTX-2 models expect a 32GB+ CUDA GPU and 100GB+ of disk, so a managed hosted service is simpler for casual or low-VRAM use.

Information

  • Websitegithub.com
  • AuthorsLightricks
  • Published date2024/11/22

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