🏔️ Winter LLM (Gemma Multimodal GGUF)

Welcome to Winter LLM, a lightweight, high-performance GGUF build based on Google's Gemma architecture with multimodal (vision + text) capabilities. Designed for fast, efficient local execution on consumer hardware, PCs, and edge setups across any region—from Kigali to anywhere in the world! 🌍✨

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🚀 Overview

• Base Architecture: Gemma Multimodal
• Format: Ready-to-run .gguf
• Features:
  • 💬 Text Generation & Chat: Fast local inference.
  • 👁️ Vision Capability: Powered by the included mmproj vision adapter for reading and understanding images.
  • ⚡ Optimized Memory Usage: Quantized to run efficiently on low-VRAM GPUs or standard CPUs.

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📂 Included Files

File Name	Size	Purpose
winter llm.gguf	~6 GB	Main LLM model weights & tokenizer
mmproj-gemma-4-12B-it-QAT-BF16.gguf	~100 MB	Multimodal vision projector (for image inputs)

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💻 How to Run Locally

You can run Winter LLM offline using any GGUF-compatible software:

1. LM Studio / Jan AI

1. Download both winter llm.gguf and the mmproj-...gguf file from the Files tab.
2. Drag and drop winter llm.gguf into LM Studio.
3. Attach the mmproj projector in settings if you wish to upload images to the chat!

2. Ollama / llama.cpp

Run via terminal using llama.cpp:

./main -m "winter llm.gguf" --mmproj "mmproj-gemma-4-12B-it-QAT-BF16.gguf" -p "User: Describe this image: [image] Assistant:"