AIAny
AI Video2024
Icon for item

LTX-Video

Generates video from text or images via a DiT-based latent diffusion model: text-to-video, image-to-video, frame extension, and multi-keyframe conditioning in one model. A distilled 2B variant runs near real-time on one H100; 13B for higher quality.

Introduction

Open video generation has mostly forced a choice: cloud APIs you can't inspect, or local models too slow to iterate with. The bet here is that a DiT-based latent diffusion design can be efficient enough to make local, near-real-time synthesis practical on a single GPU — the distilled 2B variant generates faster than playback on an H100, turning video from a batch job into something you can actually iterate on.

What Sets It Apart
  • One model, many modes. Text-to-video, image-to-video, video extension, and multi-keyframe conditioning live in the same checkpoint, so you steer a shot with start/end frames instead of juggling task-specific models.
  • Distillation that's actually usable. A 2B distilled build chases speed, the 13B build chases quality, and FP8-quantized variants exist for tighter VRAM — meaning your hardware budget, not model availability, decides what you run.
  • A concrete envelope, not vibes. The 13B model runs at 1216x704 / 30 FPS by default and extends sequences toward ~60 seconds; native 4K, 50 FPS, and one-pass synchronized audio+video belong to the separate, newer LTX-2 line, not the 13B. These are stated targets you can plan a pipeline around.
Great Fit / Look Elsewhere

Great fit if you want open weights you can fine-tune and self-host, especially for image-to-video or keyframe-driven shots where control matters more than one-click polish. Look elsewhere if you need top-tier fidelity out of the box — it works best under 720x1280 and 257 frames, and quality degrades past that — or if you lack a recent high-VRAM GPU, since the distilled models visibly trade detail for their speed.

Information

  • Websitegithub.com
  • AuthorsLightricks
  • Published date2024/11/20

Categories

More Items

Hugging Face
AI Video2026

Generates a new camera viewpoint from a reference video: an IC‑LoRA adapter for LTX‑Video 2.3 that re‑renders the same scene from a requested discrete camera angle while preserving subject and content. Trained on synthetic multi‑view data, proof‑of‑concept with limited viewpoint range and best for small, chained angle shifts.

Hugging Face
AI Video2026

Generates minute-scale, temporally coherent dance videos from full music tracks using a hierarchical two-stage approach: global keyframe planning plus local temporal refinement; suitable when long-range musical structure and rhythmic continuity matter.

GitHub
AI Video2026

Cross-platform native video editor with hardware-accelerated processing and frame-accurate multi-track timeline; core editor is open-source and free while optional Pro AI features (natural-language editing, auto-captions, smart reframing) are paid.