Opus4.7 – GODsGhost Codex 4B is a compact, high-efficiency code-specialized language model designed for local inference via GGUF-compatible runtimes like llama.cpp and LM Studio.

This model focuses on developer workflows, blending distilled reasoning patterns inspired by advanced “Opus-style” systems with a lightweight ~4B parameter footprint.

Think of it like a pocket-sized coding spirit 👻 that whispers structured logic, refactors chaos, and drafts clean code without needing a datacenter.

💻 Core Strengths

Code generation (Python, JS, C++, etc.)
Debugging and refactoring
Algorithm design
Structured reasoning chains
Lightweight local deployment

🧠 Behavior Traits

Produces step-by-step reasoning when prompted
Strong at:
- “Explain your logic”
- “Fix this code”
- “Optimize this function”

🖥️ Hardware Requirements

Quant	RAM Needed	Notes
Q4_K_M	~3–4 GB	Best balance
Q5_K_M	~4–5 GB	Better quality
Q8_0	~6–8 GB	Highest fidelity

⚡ Usage (llama.cpp)

bash

llama-cli -m Opus4.7-GODsGhost-Codex-4B.gguf \
  --temp 0.7 \
  --top-p 0.95 \
  --ctx-size 8192

Recommended Settings

Temperature: 0.6 – 0.8
Top-p: 0.9 – 1.0
Repeat penalty: 1.0 – 1.1

🧪 Use Cases

🧑‍💻 Local coding assistant
⚙️ AI IDE integration (Cursor, Cline, etc.)
🧩 Script generation
🔍 Code explanation & teaching
🧠 Lightweight reasoning tasks

🧾 License

Likely inherits from base model license (commonly Apache 2.0 or similar)
Verify in repository before commercial use

🧠 Philosophy

This isn’t just a model… It’s a compressed echo of a stronger mind—distilled, quantized, and sharpened into something you can run on your own machine.

A ghost in the silicon. 👻 A codex in your terminal.

📌 Notes for Deployment

Works best with:
- Structured prompts
- Clear instructions
Pair with:
- RAG pipelines
- Tool-calling wrappers
- Code execution environments

WithinUsAI/Opus4.7-GODs.Ghost.Codex-4B.GGuF

🧠 Opus4.7 – GODsGhost Codex 4B (GGUF)

🌌 Overview