I Benchmarked Two Local LLMs on Real Dev Work — Qwopus 27B vs Muse Glimmer 30B

Two open-weight models, one 20 GB GPU, two real development tasks, and a third model as the referee. Here is what actually happened when I made Qwopus 3.6 27B and Meta's Muse Glimmer 30B implement a bug fix and then a full feature in my own project.

The setup

Both models ran fully local on an AMD Radeon RX 7900 XT (20 GB VRAM) via a llama.cpp multi-model router (one OpenAI-compatible endpoint, GGUF models, load-mode=dio — more on why below). Each model was driven by the pi CLI in non-interactive mode with --thinking high. A third model — Codex, through a disciplined stdin wrapper — reviewed both outputs and gave the verdict.

The fairness method was simple but strict:

I Benchmarked Two Local LLMs on Real Dev Work — Qwopus 27B vs Muse Glimmer 30B

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