abhishekchohan/gemma-3-27b-it-quantized-W4A16

Gemma 3 Quantized Models

This repository contains W4A16 quantized versions of Google's Gemma 3 instruction-tuned models, making them more accessible for deployment on consumer hardware while maintaining good performance.

Models

• abhishekchohan/gemma-3-27b-it-quantized-W4A16
• abhishekchohan/gemma-3-12b-it-quantized-W4A16
• abhishekchohan/gemma-3-4b-it-quantized-W4A16

Repository Structure

gemma-3-{size}-it-quantized-W4A16/
├── README.md
├── templates/
│   └── chat_template.jinja
├── tools/
│   └── tool_parser.py
└── [model files]

Quantization Details

These models use W4A16 quantization via LLM Compressor:

• Weights quantized to 4-bit precision
• Activations use 16-bit precision
• Significantly reduced memory requirements

Usage with vLLM

vllm serve abhishekchohan/gemma-3-{size}-it-quantized-W4A16 --chat-template templates/chat_template.jinja --enable-auto-tool-choice --tool-call-parser gemma --tool-parser-plugin tools/tool_parser.py

License

These models are subject to the Gemma license. Users must acknowledge and accept the license terms before using the models.

Citation

@article{gemma_2025,
    title={Gemma 3},
    url={https://goo.gle/Gemma3Report},
    publisher={Kaggle},
    author={Gemma Team},
    year={2025}
}