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L-Forster/open-jet

An offline coding agent for local models. One command sets up the best model your GPU can run, and on 24 GB+ RTX 30/40/50-series cards Qwen3.8-27B runs up to 1.9x faster than llama.cpp.

#AI agent#AI coding assistant#LLM inference
Visit GitHub
Python
102
13
3 contributors
GNU Affero General Public License v3.0
website
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Momentum

How fast L-Forster/open-jet 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

Oct 1 – Oct 22, 2026

Stars +52 in 22 days

01020
18

Forks +8 in 22 days

0123
3

Merged PRs 6 in 22 days

012
2

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

Not in the Trendshift top 25 in this period

Oct 1Oct 4Oct 7Oct 10Oct 13Oct 16Oct 19Oct 22
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
Thu, Oct 1, 2026+1+00
Fri, Oct 2, 2026+0+00
Sat, Oct 3, 2026+0+00
Sun, Oct 4, 2026+0+00
Mon, Oct 5, 2026+0+00
Tue, Oct 6, 2026+0+00
Wed, Oct 7, 2026+0+00
Thu, Oct 8, 2026+0+00
Fri, Oct 9, 2026+0+00
Sat, Oct 10, 2026+8+22
Sun, Oct 11, 2026+18+30
Mon, Oct 12, 2026+9+12
Tue, Oct 13, 2026+4+10
Wed, Oct 14, 2026+2+12
Thu, Oct 15, 2026+0+00
Fri, Oct 16, 2026+4+00
Sat, Oct 17, 2026+1+00
Sun, Oct 18, 2026+0+00
Mon, Oct 19, 2026+1+00
Tue, Oct 20, 2026+2+00
Wed, Oct 21, 2026+2+00
Thu, Oct 22, 2026+0+00
Total+52+86
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Oct 121 post

    • llama.cpp optimizations for specific hardware and models

      Read full on Reddit

      r/LocalLLaMA

  2. Oct 113 posts

    • Qwen3.8-27B at 140 tok/s on a single RTX 3090 with a custom CUDA megakernel (1.4-1.9x llama.cpp)

      Read full on Reddit

      r/LocalLLM

    • A CUDA megakernel built for Qwen3.8-27B: 140 tok/s on one RTX 3090, KL divergence 0.0009 vs llama.cpp

      Read full on Reddit

      r/Qwen_AI

    • UPDATE: Qwen 3.8 27B 140 tok/s on single RTX 3090 Megakernel: KL divergence 0.0009 vs llama.cpp

      Read full on Reddit

      r/LocalLLaMA

  3. Oct 101 post

    • Qwen3.8-27B on a single 3090: 140 tok/s on code with a custom megakernel

      Read full on Reddit

      r/LocalLLaMA

  4. 2 months earlier
  5. Aug 181 post

    • Make your codex subscription go 5x further with OpenJet v0.5. Here's how it works: - It finds and runs the best local model for your hardware for you (including Qwen 3.8 27B) using llama.cpp - It…

      Read full on X, posted by @FlouisLF

      @FlouisLF · x.com

  6. 3 months earlier
  7. Jun 41 post

    • With OpenJet, you can seamlessly switch between cloud and local models, allowing you to pick the best option for your use case! This is designed to have as little manual configuration as possible,…

      Read full on X, posted by @FlouisLF

      @FlouisLF · x.com

  8. 11 days earlier
  9. May 241 post

    • Claude Code for local LLMs. Unified backend, setup, and coding harness for your own models. Would this fit your current agent stack?

      Read full on X, posted by @AIDailyGems

      @AIDailyGems · x.com

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