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mizorewww/laya-mlx

Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.

#LLM inference
Visit GitHub
Python
7.1k
590
1 contributors
Apache License 2.0
website
AchievementsView all →
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Momentum

How fast mizorewww/laya-mlx is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 19 – Nov 5, 2026

Stars +7,066 in 48 days

01K2K3K
2,121

Forks +590 in 48 days

0100200
159

Merged PRs 2 in 48 days

012
2

Trendshift Trendingwhere the repository ranked each day it made the top 25

Top 25 overall

464

Top 25 in Python

333
Sep 19Sep 25Oct 1Oct 7Oct 13Oct 19Oct 25Oct 31
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRsAll languagesPython
Sat, Sep 19, 2026+0+00Not trendingNot trending
Sun, Sep 20, 2026+1,630+820#4#3
Mon, Sep 21, 2026+2,121+1450#6#3
Tue, Sep 22, 2026+1,668+1590#4#3
Wed, Sep 23, 2026+524+610Not trendingNot trending
Thu, Sep 24, 2026+269+330Not trendingNot trending
Fri, Sep 25, 2026+120+180Not trendingNot trending
Sat, Sep 26, 2026+86+80Not trendingNot trending
Sun, Sep 27, 2026+61+110Not trendingNot trending
Mon, Sep 28, 2026+89+50Not trendingNot trending
Tue, Sep 29, 2026+61+70Not trendingNot trending
Wed, Sep 30, 2026+25+00Not trendingNot trending
Thu, Oct 1, 2026+35+90Not trendingNot trending
Fri, Oct 2, 2026+29+20Not trendingNot trending
Sat, Oct 3, 2026+20+20Not trendingNot trending
Sun, Oct 4, 2026+19+60Not trendingNot trending
Mon, Oct 5, 2026+22+20Not trendingNot trending
Tue, Oct 6, 2026+14+30Not trendingNot trending
Wed, Oct 7, 2026+21+30Not trendingNot trending
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Sat, Oct 17, 2026+2+20Not trendingNot trending
Sun, Oct 18, 2026+14+10Not trendingNot trending
Mon, Oct 19, 2026+10+20Not trendingNot trending
Tue, Oct 20, 2026+9+10Not trendingNot trending
Wed, Oct 21, 2026+6+00Not trendingNot trending
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Sat, Oct 24, 2026+3+00Not trendingNot trending
Sun, Oct 25, 2026+6+00Not trendingNot trending
Mon, Oct 26, 2026+2+20Not trendingNot trending
Tue, Oct 27, 2026+2+00Not trendingNot trending
Wed, Oct 28, 2026+6+10Not trendingNot trending
Thu, Oct 29, 2026+2+22Not trendingNot trending
Fri, Oct 30, 2026+8+10Not trendingNot trending
Sat, Oct 31, 2026+8+10Not trendingNot trending
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Wed, Nov 4, 2026+5+00Not trendingNot trending
Thu, Nov 5, 2026+1+00Not trendingNot trending
Total+7,066+5902
  • 1#1 on the list
  • 7Rank that day
  • Not trending

    • Mentions and achievements

    Where people are talking about mizorewww/laya-mlx, and every badge it has earned
    1. Oct 101 post

      • 在苹果电脑上跑 AI，很多框架对苹果芯片支持不好。 Laya MLX 是专门给苹果 MLX 做的运行时，把决策模型重算压到 7–14 毫秒。

        Read full on X, posted by @laogeai

        @laogeai · x.com

    2. 8 days earlier
    3. Oct 21 post

      • • Answers typed questions in milliseconds • Runs fully offline on your Mac • No cloud, PyTorch, or text generation

        Read full on X, posted by @the_osps

        @the_osps · x.com

    4. 9 days earlier
    5. Sep 233 posts

      • 💻 mizorewww/laya-mlx by @mizorewww Runs Laya typed decisions locally in MLX for choice, score, and boolean outputs. Keeps upstream weights, formatting, calibration, and schema. Key points: • 7.39 ms…

        Read full on X, posted by @papersdatacode

        @papersdatacode · x.com

      • 8 open-source projects exploring the Jev idea

        Read full on Reddit

        r/WebAfterAI

      • Jev 发布才 8 天，开源替身已经一堆了，今天诺基亚也来蹭热闹了😅 我在 MacBook 上，让官方 Jev 和 3 个开源方案同跑 20 张中文工单🫱 Laya 25ms，比 Jev 快 50 倍 djev 509ms 官方 Jev 1.3 秒 AnyJev 将近 4 秒 仓库都在这： Laya（Mac 版） djev（Mac 版） AnyJev 但快的，不一定对 👇

        Read full on X, posted by @wquguru

        @wquguru · x.com

    6. Sep 224 posts

      • THIS IS F**KING GOLD I found Laya, which now runs natively on Apple Silicon Not via a cloud API Not via PyTorch Not by generating JSON token by token laya-mlx runs open-weight decision models locally…

        Read full on X, posted by @iamrexei

        @iamrexei · x.com

      • 哇靠，据说还有比jev还快的项目，一台M3 Max，最高1G内存，每秒做60次决策，本地贪吃蛇自己走完一整局。 大一开发者把Laya移植到MLX，做成开源的laya-mlx。 它是基于文本输出概率的分类决策系统，一次前向就能给出方向、风险、可达性这些结构化结果。 视频里模型在本机实时选上下左右，延迟多在十几毫秒，安全层零次干预。 后续还有CoreML版本，功耗再降六成。

        Read full on X, posted by @hank_aibtc

        @hank_aibtc · x.com

      • All measured on an M4 Air, 16GB. Local model: 656MB RAM, tens of ms per decision, $0. Same rules as always: measure on your own data, engineer the input before blaming the model, never trust a…

        Read full on X, posted by @Raju_M_A

        @Raju_M_A · x.com

      • 0xb6a2841277583072f6bc83704007573e97317777 进群看是真的嘞

        Read full on X, posted by @k7633336A

        @k7633336A · x.com

    7. Sep 211 post

      • laya, a multilingual non-autoregressive decision engine, 100+ languages, 33ms/decision. Three checkpoints + a router that auto-picks the right one per request. Claims to beat Jev on several…

        Read full on X, posted by @0x5uZ

        @0x5uZ · x.com

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