Qwopus GLM 18B Merged (Healed) A 64 layer frankenmerge of two of Jackrong's incredible Qwen3.5 9B finetunes, stacking all 32 layers from each to create an ~18B parameter model, then healed with a 1000 step QLoRA fine tune to smooth the layer boundary. This was a fun experiment! A lot of people have been asking for something between Jackrong's 27B and 9B models — something that runs well on 12–16 GB GPUs. This frankenmerge is an attempt at filling that gap, and the results are surprisingly good. Heal Fine Tune — It Works The raw frankenmerge had a known issue: garbled code output . Because two separately trained models were stacked at layer 32, structured output (code blocks, HTML, bracket matching) would occasionally come out malformed or hallucinated. We ran a 1000 step QLoRA heal fine tune using Jackrong's own training data to let gradients flow across the layer boundary — and the results are significant: HTML generation is now clean and production quality. We tested a complex single page weather dashboard (navbar, dark mode toggle, 5 day forecast grid, responsive sidebar, CSS variables, JavaScript) — the model produced 14,500+ chars of valid HTML/CSS/JS with perfectly balanced C…
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