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Pricing: Free
Verified: Yes
Editor rating: 4.1/5
Updated: July 2026

Real-time 24 FPS video generation at 768x512 from text or images using multimodal open-source foundation model.

Editor's take: AI video generation with competitive quality output — Sohail Akhtar

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Independent & reader-supported

Editor's note

4.1 / 5.0

AI video generation with competitive quality output

Pricing

Completely free open-source model. No licensing fees for commercial use.

What is LTX-2?

LTX-2 by Lightricks generates realistic video scenes at 24 FPS in real-time using fully open-source architecture. Developers, researchers, and AI enthusiasts deploy locally without API dependencies. Multimodal inputs enable precise character, setting, and style control. 24 FPS smooth motion handles natural human movements and environmental interactions. 768x512 resolution balances quality and performance across hardware. Text-to-video creates scenes from detailed prompts; image-to-video animates references contextually. Open weights enable fine-tuning for custom domains and styles. Multiple LoRA support accelerates specialized training. Commercially licensed for production use. Runs efficiently on consumer GPUs without cloud costs. Completely free open-source model. Local deployment eliminates usage limits. Processing speed depends on hardware with real-time capability on high-end systems. Discover more tools.

Associated Tags

open source video ai, ltx-2 lightricks, 24 fps video ai, real-time video generation, multimodal video model, local gpu video ai

Key Features

Real-time 24 FPS video generation
768x512 multimodal outputs
Fully open-source weights
Local GPU deployment
Character and style control
Commercial license included
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Frequently Asked Questions

Is LTX-2 completely free?
Fully open-source with commercial licensing included.
What hardware runs LTX-2?
Efficient on consumer GPUs with real-time on high-end systems.
Does LTX-2 run locally?
Complete local deployment without internet or API dependency.
Can developers fine-tune LTX-2?
Full open weights with LoRA support for custom domains.