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Important: requires a patched llama.cpp

RYS duplicates one of the middle layers, which breaks the hardcoded full_attention_interval = 4 assumption in stock llama.cpp's Qwen3.5 loader. These GGUFs are re-converted with per-layer head_count_kv baked in, and you need a llama.cpp that reads that per-layer metadata instead of falling back to the interval formula.

Patched fork: https://github.com/DJLougen/llama.cpp (default branch rys-qwen35, one commit on top of ggml-org/llama.cpp@d00685831, fully backward-compatible).

Stock llama.cpp, Ollama, LM Studio, and any other inference runtime built on stock llama.cpp will currently fail to load these files with a check_tensor_dims error on blk.33 — this is expected until/unless the patch is upstreamed.

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Available Quantizations

File	Quant	Size	Notes
`ornstein-3.6-27b-rys-q8_0.gguf`	Q8_0	~27 GB	Near-lossless, largest
`ornstein-3.6-27b-rys-q6_k.gguf`	Q6_K	~21 GB	Very high quality
`ornstein-3.6-27b-rys-q5_k_m.gguf`	Q5_K_M	~18 GB	Strong quality/size balance
`ornstein-3.6-27b-rys-q4_k_m.gguf`	Q4_K_M	~16 GB	Recommended default
`ornstein-3.6-27b-rys-q3_k_m.gguf`	Q3_K_M	~12 GB	Low-memory option

Model Lineage

Qwen 3.6 27B → Ornstein3.6 (DDM fine-tune) → RYS (layer 33 dup, +49%)

Model Details

Architecture: Qwen3.5 dense
Parameters: ~27B active
Layers: 65 (64 original + 1 RYS-duplicated layer 33)
Context: 131,072 tokens
GGUF metadata: per-layer head_count_kv array encoding the RYS-shifted attention pattern

Usage

Build the patched llama.cpp

bash

git clone https://github.com/DJLougen/llama.cpp.git
cd llama.cpp
git checkout rys-qwen35
cmake -B build -DGGML_CUDA=ON -DCMAKE_BUILD_TYPE=Release
cmake --build build -j

Drop -DGGML_CUDA=ON for a CPU-only build. The patch touches the GGUF loader and three model forward files; backend selection is independent.

Download + run

bash

hf download GestaltLabs/Ornstein-3.6-27B-RYS-GGUF \
    ornstein-3.6-27b-rys-q4_k_m.gguf \
    --local-dir .

./build/bin/llama-server \
    -m ornstein-3.6-27b-rys-q4_k_m.gguf \
    --host 0.0.0.0 --port 8080 \
    --n-gpu-layers 99 --ctx-size 131072 \
    --flash-attn on --jinja \
    -ctk q4_0 -ctv q4_0

License

Apache 2.0