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trymirai/uzu

A high-performance inference engine for AI models

#LLM inference
Visit GitHub
Rust
3.2k
245
17 contributors
MIT License
website
AchievementsView all →
FeaturedAdvertise to 180K+ monthly visitors
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Momentum

How fast trymirai/uzu 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 5 – Nov 4, 2026

Stars +1,485 in 61 days

0100200300
265

Forks +167 in 61 days

01020
18

Merged PRs 181 in 61 days

051015
12

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

Top 25 in Rust

21612
Sep 5Sep 13Sep 21Sep 29Oct 7Oct 15Oct 23Oct 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 PRsRust
Sat, Sep 5, 2026+8+23Not trending
Sun, Sep 6, 2026+5+02Not trending
Mon, Sep 7, 2026+3+11Not trending
Tue, Sep 8, 2026+6+01Not trending
Wed, Sep 9, 2026+4+02Not trending
Thu, Sep 10, 2026+6+10Not trending
Fri, Sep 11, 2026+1+10Not trending
Sat, Sep 12, 2026+5+10Not trending
Sun, Sep 13, 2026+11+10Not trending
Mon, Sep 14, 2026+12+12Not trending
Tue, Sep 15, 2026+7+02Not trending
Wed, Sep 16, 2026+2+17Not trending
Thu, Sep 17, 2026+5+20Not trending
Fri, Sep 18, 2026+0+10Not trending
Sat, Sep 19, 2026+2+03Not trending
Sun, Sep 20, 2026+1+00Not trending
Mon, Sep 21, 2026+2+13Not trending
Tue, Sep 22, 2026+1+11Not trending
Wed, Sep 23, 2026+0+05Not trending
Thu, Sep 24, 2026+0+07Not trending
Fri, Sep 25, 2026+0+10Not trending
Sat, Sep 26, 2026+0+11Not trending
Sun, Sep 27, 2026+2+03Not trending
Mon, Sep 28, 2026+3+00Not trending
Tue, Sep 29, 2026+0+04Not trending
Wed, Sep 30, 2026+1+03Not trending
Thu, Oct 1, 2026+2+13Not trending
Fri, Oct 2, 2026+1+04Not trending
Sat, Oct 3, 2026+0+01Not trending
Sun, Oct 4, 2026+1+00Not trending
Mon, Oct 5, 2026+0+03Not trending
Tue, Oct 6, 2026+1+06Not trending
Wed, Oct 7, 2026+0+01Not trending
Thu, Oct 8, 2026+13+01Not trending
Fri, Oct 9, 2026+234+179#21
Sat, Oct 10, 2026+82+73Not trending
Sun, Oct 11, 2026+23+50Not trending
Mon, Oct 12, 2026+55+512Not trending
Tue, Oct 13, 2026+59+510Not trending
Wed, Oct 14, 2026+45+36Not trending
Thu, Oct 15, 2026+16+48Not trending
Fri, Oct 16, 2026+21+45Not trending
Sat, Oct 17, 2026+13+42Not trending
Sun, Oct 18, 2026+11+81Not trending
Mon, Oct 19, 2026+19+55Not trending
Tue, Oct 20, 2026+43+32Not trending
Wed, Oct 21, 2026+35+04Not trending
Thu, Oct 22, 2026+50+32Not trending
Fri, Oct 23, 2026+16+04Not trending
Sat, Oct 24, 2026+11+20Not trending
Sun, Oct 25, 2026+8+02Not trending
Mon, Oct 26, 2026+8+11Not trending
Tue, Oct 27, 2026+265+175#6
Wed, Oct 28, 2026+147+183#12
Thu, Oct 29, 2026+43+46Not trending
Fri, Oct 30, 2026+66+157Not trending
Sat, Oct 31, 2026+35+51Not trending
Sun, Nov 1, 2026+26+41Not trending
Mon, Nov 2, 2026+26+65Not trending
Tue, Nov 3, 2026+16+55Not trending
Wed, Nov 4, 2026+7+03Not trending
Total+1,485+167181
  • 1#1 on the list
  • 7Rank that day
  • Not trending
4

    • GitHub trending history

    Where the repository ranked on GitHub Trending, one dot for each day it was on a list

    Rust

    Oct 21 – Oct 29, 2026Best #4

    #1#5#10#15#20#25
    Top 10
    Oct 21, 2026Oct 29, 2026
    The left and right arrow keys step from day to day; Home and End go to the first and the last

    Mentions and achievements

    Where people are talking about trymirai/uzu, and every badge it has earned
    1. Nov 31 post

      • We have added decision model support in uzu! Run a local server using Typesafe's API: Or try "trymirai/d3-flash-M" in our interactive CLI: What are you building with decision models? Share your use…

        Read full on X, posted by @AleksGolokoz

        @AleksGolokoz · x.com

    2. Nov 11 post

      • Run AI inside your Apple app — without routing every prompt through a cloud API. uzu is a Rust-based inference engine for builders adding local AI models to macOS and iOS apps. It helps you get from…

        Read full on X, posted by @DanKornas

        @DanKornas · x.com

    3. Oct 302 posts

      • 💥 Same Qwen3.5 9B on an M5 MacBook. Same prompt. No speculative decoding: 42s Regular speculative: 30s DFlash + Weaver (uzu): 11s About 4x faster. Clip is all three side by side. Chip and prompt…

        Read full on X, posted by @QwenAIFans

        @QwenAIFans · x.com

      • the way past the local llm speed limit isn't a faster gpu. it's more tokens per read of the weights. a small drafter guesses 16 tokens ahead, the big model checks them in one pass, keeps what it…

        Read full on X, posted by @DLife_hacker

        @DLife_hacker · x.com

    4. Oct 291 post2 posts

      • Big win for local LLM inference! uzu hit 92.1 tokens/s running Qwen3.5 9B on a base M5 MacBook Pro 🤯 In the developer’s comparison: - llama.cpp: 22.0 tokens/s - MLX: 25.1 tokens/s - uzu: 92.1…

        Read full on X, posted by @simplifyinAI

        @simplifyinAI · x.com

      • Uzu boosted inference by 3.5x ! Context: 512 Uzu: 68.3 tok/s MLX-LM: 20.9 tok/s llama.cpp: 19.8 tok/s Context: 64k Uzu: 36.6 tok/s MLX-LM: 10.4 tok/s llama.cpp: 9.8 tok/s

        Read full on X, posted by @trevorwood222

        @trevorwood222 · x.com

    5. Oct 271 post

      • 同一台基础款 M5 MacBook Pro，同一个 Qwen3.5 9B，只换推理引擎：llama.cpp 22 tok/s，MLX 25，uzu 直接 92，差不多快了 4 倍。 我第一反应是不信。M5 内存带宽大概 153GB/s，4bit 的 9B 差不多 5GB，老老实实一个 token 一个 token 吐，理论上限也就 30…

        Read full on X, posted by @LJL06019

        @LJL06019 · x.com

    6. 14 days earlier
    7. Oct 131 post

      • 想在 App 里直接跑模型、不走云端，可以看看 uzu。 Rust 写的推理引擎，MIT，用 Apple 的统一内存，Rust、Python、Swift、TS 都有接口。 README 自己提醒：模型很吃内存，同时只留一个会话，iOS 建议申请 Increased Memory Capability。

        Read full on X, posted by @_ninetyhe

        @_ninetyhe · x.com

    8. Oct 121 post

      • uzu: A high-performance inference engine for AI models (2.2k stars)

        Read full on Reddit

        r/BestGitHubRepos

    9. 1 month earlier
    10. Sep 31 post

      • The quantization pipeline itself is PTQ followed by a very short distillation run. For PTQ, we use a modified version of YAQA a state of the art second-order quantization algorithm. On our evals, we…

        Read full on X, posted by @norpadon

        @norpadon · x.com

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