Local Qwen inference server
Running an open-weight coding model on an iMac Pro, with llama.cpp inference and an Open WebUI interface.
I’m a Media Systems Engineer working across broadcast technology, networks, and infrastructure. Drabsnarg is where I document what I build, what I learn, and what comes next.
Running an open-weight coding model on an iMac Pro, with llama.cpp inference and an Open WebUI interface.
An invitation-only access design connecting Cloudflare Access and Tunnel to the existing local AI stack.
A planned study of coding assistants, independent code reviews, and controlled multi-agent development workflows.
Project labels distinguish active work from planned experiments. Results appear only when documented.
My work sits between disciplines. Understanding the connections is often where the most useful engineering happens.
Production infrastructure, signal transport, audio networking, and the systems behind live media.
Routing, switching, segmentation, and the connections that make complex systems work together.
Practical tools, Python and PowerShell workflows, APIs, and repeatable solutions to real problems.
Open-weight models, owner-operated hardware, inference experiments, and AI development tools.
Windows, macOS, servers, Microsoft 365, identity, device management, and reliable operations.
Secure access, infrastructure ownership, and a systematic approach to learning how things work.
An evolving environment for self-hosted AI, model experiments, and software development. Built around an iMac Pro, llama.cpp, and Open WebUI.
AI APPLICATION: INVITATION-ONLY · AUTHENTICATION REQUIRED
A repeatable plan for comparing local coding models without invented numbers.
A structured way to distinguish clock election, network reachability, and audio-flow symptoms.
Preflight validation, exit-code checks, and post-deployment smoke tests.
See the current focus, explore the technical notes, or learn more about the engineering behind Drabsnarg.