An offline coding agent for local models. One command sets up the best model your GPU can run, and on 24 GB+ RTX 30/4...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Reasonable to try, but it will take more than a quick skim to get real signal.
GitHub health 57/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Claude Code
Model
Llama
Fastest way to find out if open-jet belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
git clone https://github.com/L-Forster/open-jet ~/.claude/agents/open-jetRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/open-jetNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ skills/ ├─ agents/ │ └─ open-jet/ ← installs here └─ settings.json
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.
Source: GitHub repository
Source check: October 12, 2026
Upstream commit: October 12, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.