myeongjun77/Pungyo-Qwen36-A3B

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

램을 풍요롭게 — Run big. Keep your memory abundant.

OpenAI-compatible local server. Pick the files you need, drop them in a folder, run one of the two .exe files. The model loads on an 8GB laptop GPU; the operating point is chosen automatically in memory.

This repository is not a model release. The internal mechanism is not disclosed.

Speed (measured, RTX 4060 Laptop 8GB, 245-token steady-state)

profile	speed	VRAM	when to pick
single (octagon)	~34.5 tok/s	~7 GB (tight)	maximum speed
twin (wireframe)	~28.5 tok/s	~3.7 GB (headroom)	stability under load

Twin nearly halves VRAM pressure for ~17% less speed — far less likely to OOM during longer or heavier runs. Same model, different operating point.

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 — pick 4 files (5 if you want both profiles)

file	required?	size
Qwen3.6-35B-A3B-Q4_K_M.gguf	yes (the model)	~20 GB
cublas64_13.dll	yes (GPU runtime)	49 MB
cublasLt64_13.dll	yes (GPU runtime)	435 MB
pungyo-server-single.exe	pick at least one	246 MB
pungyo-server-twin.exe	pick at least one	246 MB

Put them all in the same folder. That's the install.

Run (3 steps)

1. Open PowerShell in the folder where you put the files.
2. Start the server — single (fast) or twin (stable):

# single profile (max speed)
.\pungyo-server-single.exe -m .\Qwen3.6-35B-A3B-Q4_K_M.gguf --port 8080 --host 127.0.0.1 -c 4096

# OR twin profile (stable)
.\pungyo-server-twin.exe   -m .\Qwen3.6-35B-A3B-Q4_K_M.gguf --port 8080 --host 127.0.0.1 -c 4096

3. Use it. Wait ~30-60 seconds for the model to load, then:
   • Browser: open http://localhost:8080 — built-in chat UI is ready
   • OpenAI-compatible clients (Cursor, Continue, ChatBox, Open WebUI, Jan, LangChain, etc.): set base URL to http://localhost:8080/v1
   • API: POST http://localhost:8080/v1/chat/completions (OpenAI schema)

Stop with Ctrl+C in the server window.

Requirements

• Windows 10/11
• NVIDIA RTX-class 8GB VRAM GPU (or larger), recent NVIDIA driver
• 32 GB system memory recommended
• ~21 GB free disk for the files

Security

The example uses --host 127.0.0.1 — the server is reachable only from your own PC. To allow other machines on your LAN to use it, change to --host 0.0.0.0 and add --api-key YOUR_KEY (and ideally place a TLS reverse proxy like Caddy in front). Never expose to the public internet without auth + TLS.

Not Included

• Qwen training data
• internal mechanism / operating-point logic (source)
• private validation traces

License

• Pungyo execution binaries: see LICENSE-PUNGYO.
• Built on llama.cpp / ik_llama.cpp (MIT): see LICENSE-LLAMACPP.
• Qwen base model (Qwen3.6-35B-A3B-Q4_K_M.gguf) is redistributed under Apache-2.0: see LICENSE-QWEN.
• License scope separation: see NOTICE.md.

Patent Notice

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