LTX-2 Open-Source Cinematic AI Video Model Showcase & Breakdown

🔧 WORKFLOW & SETUP (FREE ON MODAL)

All examples in this video were generated using the official Python workflow hosted here:

👉 LTX-2 Modal Workflow (.py)
https://github.com/bewizsky/ltx2

This repository includes:
Modal setup instructions
Python workflow for running LTX-2
Easy cloud GPU execution
No local high-end GPU required

🎥 LTX-2 WORKFLOWS SHOWN
🔹 Text-to-Video (T2V) & Image-to-Video (I2V)

Generate cinematic video sequences directly from text prompts.

🔹 Image-to-Video (I2V)

Animate still images into dynamic scenes with camera motion, atmosphere, and continuity.

Both workflows are demonstrated and explained using the same Modal-based setup.

🚀 WHY LTX-2 MATTERS

LTX-2 is a strong open-source competitor in the AI video space, especially for:

Image-to-video animation
Cinematic trailers and short films
Concept art and world-building
Storyboarding and pre-visualization
While pure text-to-video still benefits from guidance, the model excels when creators bring visual direction into the process.

🔗 LINKS

🔹 LTX-2 Modal Workflow & Setup
https://github.com/bewizsky/ltx2

🔹 Modal (Cloud GPUs)
https://modal.com

If this breakdown helped you, like the video, subscribe for more AI model testing, and let me know in the comments what model or workflow you want to see next.

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