jingyaogong

    jingyaogong/minimind-v

    #477 this week

    👀 Train a 65M-parameter VLM from scratch in just 2h!

    ai
    artificial-intelligence
    chatgpt
    vision-language-model
    Python
    Apache-2.0
    8.8K stars
    983 forks
    8.8K GitHub watchers
    Updated Oct 20, 2026
    View on GitHub

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    Where it stands

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

    Ranks #477 of 2,794 repositories GStars tracks this week (top 17%).

    No releases in the last 90 days; the most recent was 364 days ago, with 5 contributors on GitHub.

    Gained 44% fewer stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Trains a compact vision-language model (VLM) from scratch efficiently using minimal cost and time on personal GPUs.
    • Enables rapid training and inference of multi-modal models with very small parameter sizes, suitable for resource-limited environments.
    • Use for developing lightweight VLMs that integrate visual and textual data for image understanding and dialogue.
    • Use for researchers or hobbyists seeking a minimal, end-to-end open-source tutorial on training vision-language models.
    • Use for deploying fast, low-memory multi-modal AI applications on single GPUs or edge devices with constrained resources.

    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
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

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

    From the README

    "大道至简"

    中文 | English

    为防止误解,“1小时” 基于NVIDIA 3090硬件设备(单卡)测试1 epoch,“1.3块钱” 指GPU服务器租用成本。

    “用乐高拼出一架飞机,远比坐在头等舱里飞行更让人兴奋!” 构建VLM范式的多模态大模型是否真的如想象中那样复杂?它的代码实现到底如何? 训练过程究竟难不难?那么现在,探索它们的答案,一起感受创造的乐趣吧!

    Excerpt from the jingyaogong/minimind-v 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

    983+66

    Open issues

    22+1

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth

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    jingyaogong/minimind-v8.8K+075364 days ago
    Category median70.0K+4.4K75—

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