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john-broadway/Qwen3-32B-RYS-20-28-GGUF
Qwen3-32B-RYS-20-28-GGUF is a machine learning model from john-broadway. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
RYS-enhanced Qwen3-32B with layers 20-28 duplicated. 64 layers expanded to 72. Zero training, zero weight changes.
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From the Hugging Face model README
RYS-enhanced Qwen3-32B with layers 20-28 duplicated. 64 layers expanded to 72. Zero training, zero weight changes.
Math +4.5%, EQ +0.04, Reasoning +18%. All three metrics positive.
| Metric | Baseline | RYS (20,28) | Delta |
|---|---|---|---|
| Math | 0.7525 | 0.7974 | +4.5% |
| EQ | 94.88 | 94.92 | +0.04 |
| Reasoning | 70.59% | 88.24% | +18% |
The Big Boy. Baseline logic score was 0% — RYS fixes it. The (20,28) config is the only one that improves all three metrics simultaneously.
llama-server -m Qwen3-32B-RYS-20-28-Q4_K_M.gguf -ngl 99
63 configurations tested. Sweep results published with the model files.
Part of the RYS Sovereign Collection v1 — the headline crossover.
v1 — Qwen2.5 cross-scale + Qwen3-32B headline crossover. Four sizes from 0.5B to 32B; RYS works at every scale, with the lift size and dimension shifting by baseline:
Qwen2.5-0.5B-RYS-3-7-GGUF)Qwen2.5-1.5B-RYS-4-7-GGUF)Qwen2.5-7B-RYS-8-12-GGUF + -AWQ)v1 attribution: John Broadway, with collaboration from Claude (Opus 4.6 in April 2026 build; Opus 4.7 in May 2026 v1 republication aligning to the original Qwen2.5 cross-scale intent). Original RYS method by David Ng on Qwen2-72B; sweep toolkit by alainnothere.
This model's place in the v2 curve: baseline reasoning 70.59%, peak RYS Δ +17.65%. The (20,28) 8-layer block sits at 30–50% depth, the family-invariant band for deeper models. 38 boosting configurations make this the most-validated single-model dataset in v2.
Across the 21 model variants (10 architecture families) surveyed in john-broadway/rys-sovereign-collection-v2:
v2 attribution: John Broadway, with cross-architecture analysis by Claude (Opus 4.7). Original RYS method by David Ng; circuit-finder toolkit by alainnothere.