OpenSourceCoder is the new AiBrainWorX home for people who want to inspect the source, try useful tools and share what they build. The redesigned front page combines open-source stories, a model library, curated repositories and a community space.
Find a useful project
The repository library now contains 25 source-reviewed projects, from llama.cpp, Ollama, Transformers and ComfyUI to Cline, Penpot, OBS Studio and openDAW. Search by name or task, filter by category and sort by the recorded star count. Cards show stars, forks, language and license. Counts are dated GitHub snapshots, not a live trending feed or a security rating; projects and their model weights can have different terms.
Our 69 model profiles explain the creator, task, license and likely runtime. A listing is a starting point for research, not a promise that a model is installed or will fit your computer.
Show your work
The new builder showcase lets a community member add a GitHub username and up to three public repositories to a shareable profile. Choose whether to appear in the directory, then fetch public follower, repository, star and fork counts. These are timestamped and cached. Account ownership is member-declared, not verified; no GitHub password or access token is required.
Visit the community to sign in or join, create your profile, add the links and choose Refresh GitHub stats. Members can leave the directory or remove their GitHub link. Public discussions and profiles should never contain private keys or project secrets.
Make local AI useful
Our launcher download page distinguishes the current source branches from older release tags. On October 28, Windows source was 0.4.0-alpha.6 and the separate Linux source was 0.1.0-alpha.2; the version panel above can check for changes. Both are alpha projects, with runtimes and model files installed separately.
The step-by-step setup guide covers prerequisites, backend choice, starting a model and opening DeepSeek Harness, with real after-setup screenshots. Our latest documented Windows measurements explain the model, cache and hardware behind the numbers. Neither catalog listings nor these short tests guarantee the same results on other machines.
Create your showcase → · Explore the repository library → · Visit the research lab →
Original AiBrainWorX reporting. Version numbers are source-branch observations as of the date shown; GitHub release tags are tracked separately.
