Pungyo Twin (풍요 쌍발) — Run Qwen3.6-35B-A3B stably on an 8GB laptop

램을 풍요롭게 — Run big. Keep your memory abundant.

✅ It works, and it stays up. Single self-contained binary. Stability-first profile: more memory headroom, fewer out-of-memory failures under load.

This repository is not a model release. Model weights are not included. The internal mechanism is not disclosed.

Single vs Twin (measured, 8GB laptop)

profile	speed	VRAM	goal
Pungyo (single)	~33.27 tok/s	~7 GB (tight)	max speed
Pungyo Twin	~28.50 tok/s	~3.7 GB (headroom)	stability

Twin nearly halves VRAM pressure (7 → 3.7 GB) for ~14% less speed, so the model is far less likely to crash (OOM) during longer or heavier runs. Still one model.

Measured on Qwen3.6-35B-A3B (Q4_K_M, user-provided GGUF), 2026-05-30, 245-token steady-state.

How does it work?

Not explained here. The mechanism is covered by patent-filed technology (application filed, KR). This release only demonstrates that it works and stays stable — it does not disclose how.

Download & Run (3 steps)

Get a compatible Qwen3.6 35B-A3B GGUF from https://huggingface.co/Qwen
Download Pungyo-Qwen36-Twin-Public-Verification-20260530.zip from this repo, unzip.
Run:

.\bin\pungyo.exe "path\to\Qwen3.6-35B-A3B.gguf" "Hello, my name is" wireframe

The wireframe argument selects the twin (stability) profile. No setup, no separate llama.cpp install. Operating point chosen in memory, never on the command line.

Requirements

Windows 10/11
NVIDIA RTX-class 8GB VRAM GPU (or compatible), CUDA driver installed
32 GB system memory recommended
a user-provided Qwen3.6 35B-A3B compatible GGUF

(Bundled in the ZIP: bin\pungyo.exe, bin\cublas64_13.dll, bin\cublasLt64_13.dll. CUDA runtime libraries are included; you do NOT need the CUDA toolkit installed.)

Not Included

Qwen model weights (get from https://huggingface.co/Qwen)
training data
internal mechanism / operating-point logic
private validation traces

License

Pungyo execution package: see LICENSE-PUNGYO.
Built from llama.cpp / ik_llama.cpp (MIT): see LICENSE-LLAMACPP.
Qwen base model (not included): see LICENSE-QWEN.
License scope separation: see NOTICE.md.

Patent Notice

Pungyo Twin relates to patent-filed technology by Myeong Jun Jo (application filed, KR). It is provided as an observable public verification artifact, not as an internal implementation disclosure. Commercial or patent licensing inquiries: koing754@gmail.com

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