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KellerJordan/modded-nanogpt

NanoGPT (124M) in 90 seconds

#LLM training
Visit GitHub
Python
6k
891
62 contributors
MIT License
AchievementsView all →
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Momentum

How fast KellerJordan/modded-nanogpt 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 +253 in 61 days

0204060
42

Forks +60 in 61 days

024
4

Merged PRs 5 in 61 days

0123
3

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

Not in the Trendshift top 25 in this period

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 PRs
Sat, Sep 5, 2026+4+10
Sun, Sep 6, 2026+3+00
Mon, Sep 7, 2026+6+10
Tue, Sep 8, 2026+5+10
Wed, Sep 9, 2026+4+10
Thu, Sep 10, 2026+4+00
Fri, Sep 11, 2026+8+10
Sat, Sep 12, 2026+1+20
Sun, Sep 13, 2026+3+00
Mon, Sep 14, 2026+1+20
Tue, Sep 15, 2026+2+10
Wed, Sep 16, 2026+6+00
Thu, Sep 17, 2026+1+10
Fri, Sep 18, 2026+3+02
Sat, Sep 19, 2026+0+10
Sun, Sep 20, 2026+3+00
Mon, Sep 21, 2026+7+20
Tue, Sep 22, 2026+4+00
Wed, Sep 23, 2026+1+00
Thu, Sep 24, 2026+8+00
Fri, Sep 25, 2026+2+00
Sat, Sep 26, 2026+3+20
Sun, Sep 27, 2026+2+00
Mon, Sep 28, 2026+2+13
Tue, Sep 29, 2026+42+40
Wed, Sep 30, 2026+6+10
Thu, Oct 1, 2026+4+00
Fri, Oct 2, 2026+9+20
Sat, Oct 3, 2026+7+10
Sun, Oct 4, 2026+4+20
Mon, Oct 5, 2026+2+10
Tue, Oct 6, 2026+7+20
Wed, Oct 7, 2026+2+20
Thu, Oct 8, 2026+4+20
Fri, Oct 9, 2026+5+00
Sat, Oct 10, 2026+4+10
Sun, Oct 11, 2026+1+10
Mon, Oct 12, 2026+2+00
Tue, Oct 13, 2026+6+20
Wed, Oct 14, 2026+5+10
Thu, Oct 15, 2026+1+20
Fri, Oct 16, 2026+3+20
Sat, Oct 17, 2026+3+20
Sun, Oct 18, 2026+2+10
Mon, Oct 19, 2026+4+00
Tue, Oct 20, 2026+3+10
Wed, Oct 21, 2026+2+10
Thu, Oct 22, 2026+3+20
Fri, Oct 23, 2026+1+10
Sat, Oct 24, 2026+1+10
Sun, Oct 25, 2026+2+00
Mon, Oct 26, 2026+4+00
Tue, Oct 27, 2026+2+00
Wed, Oct 28, 2026+3+10
Thu, Oct 29, 2026+14+30
Fri, Oct 30, 2026+7+00
Sat, Oct 31, 2026+1+00
Sun, Nov 1, 2026+0+10
Mon, Nov 2, 2026+0+20
Tue, Nov 3, 2026+4+00
Wed, Nov 4, 2026+0+10
Total+253+605
  • 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

    Oct 14, 2025 – Jan 24, 2026Best #12

    #1#5#10#15#20#25
    Top 10
    Jan 2025MarMayJulSepNovJan 2026Mar
    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 KellerJordan/modded-nanogpt, and every badge it has earned
    1. Oct 61 post

      • Nah, #92 from @DevenPzak is still 27 seconds (36%) faster without the big bigram table His work is "by far the largest" improvement!

        Read full on X, posted by @OctoDb

        @OctoDb · x.com

    2. 7 days earlier
    3. Sep 293 posts

      • NanoGPT hit 39.9 seconds on 8 H100s. How much of this carries over?

        Read full on Reddit

        r/rajistics

      • New NanoGPT speedrun record: 39.9s to 3.28 FineWeb val loss on 8xH100, down from 67.6s. Same task, same GPUs. Two levers skip flops that don't pay: sampled softmax over a shared candidate set, sparse…

        Read full on X, posted by @jimmy_longbow_

        @jimmy_longbow_ · x.com

      • Training NanoGPT in 39.9 Seconds

        Read full on Hacker News

        Hacker News

    4. 1 month earlier
    5. Aug 231 post

      • NanoGPT Speedrun

        Read full on Hacker News

        Hacker News

    6. Aug 221 post

      • nanogpt speedrun records summary

        Read full on X, posted by @cosminnegruseri

        @cosminnegruseri · x.com

    7. 16 days earlier
    8. Aug 61 post

      • 🐳 New blog finally comes out! TL;DR: ELR, which controls directional changes in model weights, is a more intrinsic hyperparameter to tune than LR. Directly tuning ELR leads to better schedules that…

        Read full on X, posted by @zhanpeng_zhou

        @zhanpeng_zhou · x.com

    9. Jul 312 posts

      • Learning the entire computation stack: from hardware to mathematics

        Read full on Reddit

        r/Galgotias_university

      • Learning the entire computation stack: from hardware to mathematics. List of all the best possible resources and directions..Thanks to u/ klop0x90

        Read full on Reddit

        r/Galgotias_university

    10. 11 days earlier
    11. Jul 201 post

      • We submit MuonH with minus-sqrt LR scheduler (1-\sqrt{t}) to the modded-nanogpt Track 3 benchmark. It improves the current MuonH SOTA by 75 steps—and, surprisingly, nearly doubles the peak learning…

        Read full on X, posted by @zhanpeng_zhou

        @zhanpeng_zhou · x.com

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