ModelTC

    ModelTC/LightX2V

    Lightweight Image Video Action Generation Inference Framework

    backend
    auto-regressive-diffusion-model
    diffusion-models
    dreamzero
    hunyuan-video
    lingbot-world
    Python
    Apache-2.0
    3.0K stars
    303 forks
    3.0K GitHub watchers
    Updated Nov 3, 2026
    View on GitHub

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    Where it stands

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

    2 releases in the last 90 days, the latest 22 days ago, with 63 contributors on GitHub.

    Peaked at #9 in the weekly ranking the week of Dec 21, its best in the past year.

    Use Cases & Benefits

    • Provides a lightweight, high-performance inference framework for generating videos from text or images using advanced diffusion models.
    • Delivers ultra-fast video synthesis with up to 20x acceleration via step distillation and efficient multi-GPU parallelism while supporting low VRAM deployment.
    • Use for building efficient text-to-video or image-to-video generation pipelines on consumer GPUs with limited memory resources.
    • Use for deploying scalable video generation services with intelligent offloading and caching to optimize resource usage in production environments.
    • Use for experimenting with state-of-the-art video generation models and operators, including quantized and distilled models, for research and prototyping.

    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

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    From the README

    LightX2V is an advanced lightweight video generation inference framework engineered to deliver efficient, high-performance video synthesis solutions. This unified platform integrates multiple state-of-the-art video generation techniques, supporting diverse generation tasks including text-to-video (T2V) and image-to-video (I2V). X2V represents the transformation of different input modalities (X, such as text or images) into video output (V).

    Excerpt from the ModelTC/LightX2V 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

    Forks

    303+56

    Open issues

    234+59

    Compared with peers in Backend

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

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