Best local AI video generator with sound is here!
LTX 2.3 offers open-source filmmakers a significant boost in motion consistency, prompt understanding, and native audio generation running locally.
What this lesson covers
This video provides a detailed installation tutorial and personal test review of LTX 2.3, the latest open-source video generator with built-in audio. The creator compares version 2.3 against its predecessor across multiple prompts, including action scenes, anime, and camera tracking.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:05 ↗
LTX 2.3 is an open-source video generator that runs locally, supports low VRAM, and can generate up to 20 seconds of video at 4K resolution with built-in audio.
- 00:49 ↗
Version 2.3 brings significant upgrades over LTX 2, including better motion consistency, improved prompt understanding, and cleaner audio quality.
- 00:58 ↗
New features introduced in LTX 2.3 include first-frame and last-frame control as well as vertical format support.
- 13:15 ↗
The video details a full local installation workflow using tools like Git and Miniconda to run LTX 2.3 locally.
Workflow outlined in the video
- Download and install Git and Miniconda on your local machine to prepare your environment.
- Clone the LTX 2.3 repository or access the model via supported tools like Wan2GP.
- Set up the required dependencies and allocate local VRAM to run the model offline.
- Test image-to-video and text-to-video prompts using first-frame and last-frame conditioning.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
How to interpret the numbers
215,373 views captured 23 October 2026. ReelStack recommendation score: 57/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 2.06× views vs 13 other channel videos observed at a similar age. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 137 views/day vs 5 channel baseline (7 comparable uploads), with the same view-evidence factor
- 10% engagement: 75/100; likes + 4× comments, smoothed with a 500-view neutral prior