Lightricks

    Lightricks/LTX-2

    Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.

    ai
    generative-ai
    ltx
    ltx-2
    Python
    Apache-2.0
    10.1K stars
    1.6K forks
    10.1K GitHub watchers
    Updated Nov 5, 2026
    View on GitHub

    Build with Backblaze B2

    SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.

    Explore Backblaze Labs

    Loading star history...

    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest today, with 6 contributors on GitHub.

    Gained 21% fewer stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Provides Python tools for inference and LoRA training of the LTX-2 audio-video generative model.
    • Combines synchronized audio-video generation, high fidelity, multiple performance modes, and production-ready outputs in a single model.
    • Use for generating high-quality text-to-video content with synchronized audio for creative media production.
    • Use for fine-tuning and customizing video generation models using LoRA training techniques.
    • Use for video-to-video transformations and keyframe interpolation to enhance or modify existing video footage.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    LTX-2 is the first DiT-based audio-video foundation model that contains all core capabilities of modern video generation in one model: synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access.

    Download the following models from the LTX-2.3 HuggingFace repository:

    LTX-2.3 Model Checkpoint (choose and download one of the following)

    Spatial Upscaler - Required for current two-stage pipeline implementations in this repository

    Temporal Upscaler - Supported by the model and will be required for future pipeline implementations

    Distilled LoRA - Required for current two-stage pipeline implementations in this repository (except DistilledPipeline and ICLoraPipeline)

    Gemma Text Encoder (download all assets from the repository)

    Excerpt from the Lightricks/LTX-2 README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 13: +217Aug 14: +133Aug 15: +13Aug 16: +32Aug 17: +39Aug 18: +31Aug 19: +41Aug 20: +9

    +1,539 stars over 88 days across 15 snapshot days; best day +217 on Aug 13.

    Forks

    1.6K+214

    Open issues

    35-78

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

    Lightricks/LTX-2 compared with AI repositories by stars, 7-day star growth, health score and last release
    RepositoryStars+7dHealthLast release
    thedotmack/claude-mem113.6K+8.8K35today
    D4Vinci/Scrapling98.1K+6.9K651 day ago
    Leonxlnx/taste-skill110.7K+5.2K551 day ago
    calesthio/OpenMontage77.2K+4.2K40—
    heygen-com/hyperframes79.6K+4.1K45today
    Lightricks/LTX-210.1K—9today
    Category median98.1K+5.2K45—

    Also by Lightricks

    Other repositories from this maintainer that GStars tracks

    Discover Repositories

    Search across tracked repositories by name or description