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drumih/turbo-fieldfare

Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook

#LLM inference
Visit GitHub
Swift
7.1k
507
1 contributors
Apache License 2.0
AchievementsView all →
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Momentum

How fast drumih/turbo-fieldfare 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 2 – Nov 1, 2026

Stars +567 in 61 days

0204060
47

Forks +88 in 61 days

0510
8

Merged PRs 8 in 61 days

01
1

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

Top 25 in Swift

8251520
Sep 2Sep 10Sep 18Sep 26Oct 4Oct 12Oct 20Oct 28
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 PRsSwift
Wed, Sep 2, 2026+47+40#8
Thu, Sep 3, 2026+29+60#25
Fri, Sep 4, 2026+16+21Not trending
Sat, Sep 5, 2026+13+10Not trending
Sun, Sep 6, 2026+16+10Not trending
Mon, Sep 7, 2026+8+20Not trending
Tue, Sep 8, 2026+9+11Not trending
Wed, Sep 9, 2026+11+10Not trending
Thu, Sep 10, 2026+12+00Not trending
Fri, Sep 11, 2026+10+10Not trending
Sat, Sep 12, 2026+11+00Not trending
Sun, Sep 13, 2026+8+00Not trending
Mon, Sep 14, 2026+5+20Not trending
Tue, Sep 15, 2026+9+10Not trending
Wed, Sep 16, 2026+12+20Not trending
Thu, Sep 17, 2026+15+10Not trending
Fri, Sep 18, 2026+7+11Not trending
Sat, Sep 19, 2026+7+10Not trending
Sun, Sep 20, 2026+7+00Not trending
Mon, Sep 21, 2026+10+00Not trending
Tue, Sep 22, 2026+4+11Not trending
Wed, Sep 23, 2026+15+30Not trending
Thu, Sep 24, 2026+3+00Not trending
Fri, Sep 25, 2026+2+00Not trending
Sat, Sep 26, 2026+7+00Not trending
Sun, Sep 27, 2026+4+01Not trending
Mon, Sep 28, 2026+8+00Not trending
Tue, Sep 29, 2026+3+10Not trending
Wed, Sep 30, 2026+6+10Not trending
Thu, Oct 1, 2026+2+00Not trending
Fri, Oct 2, 2026+2+30Not trending
Sat, Oct 3, 2026+4+00Not trending
Sun, Oct 4, 2026+2+10Not trending
Mon, Oct 5, 2026+0+10Not trending
Tue, Oct 6, 2026+7+10Not trending
Wed, Oct 7, 2026+3+00Not trending
Thu, Oct 8, 2026+2+10Not trending
Fri, Oct 9, 2026+3+00Not trending
Sat, Oct 10, 2026+3+00Not trending
Sun, Oct 11, 2026+3+00Not trending
Mon, Oct 12, 2026+3+00Not trending
Tue, Oct 13, 2026+39+70#15
Wed, Oct 14, 2026+8+21Not trending
Thu, Oct 15, 2026+4+31Not trending
Fri, Oct 16, 2026+4+10Not trending
Sat, Oct 17, 2026+2+80Not trending
Sun, Oct 18, 2026+4+30Not trending
Mon, Oct 19, 2026+0+70Not trending
Tue, Oct 20, 2026+23+30Not trending
Wed, Oct 21, 2026+25+00#20
Thu, Oct 22, 2026+1+10Not trending
Fri, Oct 23, 2026+20+20Not trending
Sat, Oct 24, 2026+20+30Not trending
Sun, Oct 25, 2026+14+00Not trending
Mon, Oct 26, 2026+9+21Not trending
Tue, Oct 27, 2026+18+10Not trending
Wed, Oct 28, 2026+6+00Not trending
Thu, Oct 29, 2026+14+50Not trending
Fri, Oct 30, 2026+2+00Not trending
Sat, Oct 31, 2026+5+00Not trending
Sun, Nov 1, 2026+1+00Not trending
Total+567+888
  • 1#1 on the list
  • 7Rank that day
  • Not trending

    • Mentions and achievements

    Where people are talking about drumih/turbo-fieldfare, and every badge it has earned
    1. Sep 21 post

      • Integration with Turbo FieldFare possible as a local model?

        Read full on Reddit

        r/OdysseusAI

    2. 15 days earlier
    3. Aug 181 post

      • 2. TurboFieldfare It runs Gemma 4 26B-A4B on Apple Silicon without loading the full 14 GB model into RAM. The shared core and KV cache stay in memory. The routed MoE experts are streamed from SSD…

        Read full on X, posted by @felixtiss

        @felixtiss · x.com

    4. Aug 131 post

      • this is f***king insane you can run gemma 4 26b on a macbook air for $0 turbo fieldfare is a custom swift metal runtime that fits gemma 4 26b-a4b in ~2gb of ram on any apple silicon mac. what you get…

        Read full on X, posted by @0x_sakata

        @0x_sakata · x.com

    5. Aug 92 posts

      • DeepSeek-V4-Flash-0731(284B) on a 64G M5 Pro Mac — 6.5 tok/s decode with ~30 GB memory usage in Codex

        Read full on Reddit

        r/LocalLLM

      • 26B parameters. 2 GB of RAM. The MacBook you already own. Turbo Fieldfare runs Gemma 4 26B-A4B inference locally on any M-series MacBook, using about 2 GB of memory. No cloud, no GPU rental, your…

        Read full on X, posted by @SedraLab

        @SedraLab · x.com

    6. Aug 83 posts

      • Someone built a way to run a 26-billion-parameter model in about 2GB of RAM. On a regular Mac. The trick: don't load the model into memory at all. TurboFieldfare keeps a ~1.35GB resident core…

        Read full on X, posted by @lifeisameeme

        @lifeisameeme · x.com

      • 翻完Issues发现不少信息。只支持Gemma 4 26B A4B。Issue #39有人要expert caching。Issue #44要支持其他MoE模型。8个测试文件对315源码。作者还没做这些。思路可复制不过代码模型专用 📌

        Read full on X, posted by @BencyMarrit

        @BencyMarrit · x.com

      • 个人判断：26B模型塞进2GB内存这事，原理比大家想的简单。TurboFieldfare把专家参数从SSD流式读取，内存只放1.35GB共享base。ExpertStreamer.swift用pread系统调用直接读SSD。纯Swift和Metal写的，不套MLX。280 Fork。 😱

        Read full on X, posted by @BencyMarrit

        @BencyMarrit · x.com

    7. Aug 61 post

      • 26B 大模型，为什么能在 Apple Silicon 上用约 2GB 的权重和 KV cache 运行？ TurboFieldfare 的答案不是魔法，而是内存布局：共享核心常驻，当前 token 需要的专家从 SSD 流式读取。 项目：

        Read full on X, posted by @caizm1688

        @caizm1688 · x.com

    8. Aug 51 post

      • 3/ Alibaba's Qwen3.8-Max claims it can match or beat Anthropic's Fable 5. That puts it alongside DeepSeek and ByteDance as evidence the gap between Chinese and US frontier models is narrowing fast.

        Read full on X, posted by @PrizmalAi

        @PrizmalAi · x.com

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