LTX-2.3 Examples Video
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Real-time AI

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Open world model for real-time AI experiences

Build responsive AI experiences across avatars, gaming, and live streaming. Generate with low latency, on infrastructure you control.

33M+

Downloads on HuggingFace

12GB+

Runs locally on 12GB VRAM

1 GPU

Near real-time generation

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Why LTX

**Every interaction** happens in real time

Low latency is just the beginning. LTX provides the control, consistency, and flexibility needed to build responsive AI experiences.

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Capabilities

Built for **real-time AI**

AI avatars

Create expressive virtual characters that maintain identity across long conversations, with synchronized video and audio.

Interactive gaming

Power dynamic NPCs, player interactions, and world transformations that respond instantly to gameplay.

Live streaming

Transform appearances, environments, characters, and visual effects while content is streamed live.

Interactive applications

Build AI-powered products on one open world model instead of stitching together multiple AI systems.

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Security & IP

**Keep your IP** protected

Deploy real-time AI on infrastructure you control, keeping your characters, branded assets, and proprietary IP private.

  • Deploy on-prem or in a private cloud.

  • Open weights for transparency and customization.

  • Self-host so your assets never train shared models.

  • No vendor lock-in.

Real-time by design

LTX compresses more information into every token, reducing compute and enabling real-time interactive experiences.

More compression

Each latent token holds more pixels.

Fewer tokens

Same video, fewer tokens needed.

Less compute

Fewer tokens reduce the compute per generation.

Lower latency

Faster generation enables real-time experiences.

8,192

Pixels represented per latent token in LTX.

1,024

Pixels represented per latent token in typical architectures.

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Resources

**Learn more about** interactive AI

Discover how developers are building interactive AI with LTX, from AI avatars and gaming to live streaming experiences.

How to Maintain Character Consistency in AI Video Production

Learn how to keep characters consistent across AI video scenes using LTX-2.5 image conditioning, IC-LoRA, and LoRA training for multi-shot productions.

Training Your First LoRA on LTX

A practical guide to training your first LoRA on LTX-2.3, covering dataset prep, LoRA type selection, baseline settings, validation, and common debugging steps.

IC-LoRA In LTX-2.5: ComfyUI Workflow For AI Character Consistency

Master motion control in AI video generation with IC-LoRA. Learn how to transfer camera movement, scene structure, and human performance from reference videos into LTX-2 workflows.

LTX-2.3 Fast vs Pro: Guide & Comparison

LTX-2.3 Fast vs Pro — when to use each tier, how speed and quality differ, and how to combine both in a production workflow.

Using LoRA Adapters with LTX-2.5: A Developer Guide

Use LoRA adapters with the LTX-2.5 open-source pipeline for custom AI video generation. Covers standard, audio-video, and IC-LoRA types with setup instructions.

How to Run LTX-2 on Consumer GPUs: VRAM Tiers, Settings, and OOM Fixes

Run LTX-2 efficiently on consumer GPUs with practical settings, VRAM tips, and troubleshooting insights to unlock local high-quality AI video generation

Build the next generation of interactive AI

See how LTX fits your product, your infrastructure, and your roadmap.