Goal: The ultimate goal of this project is to create the best Gemma 4 coder model available.
This model is a highly fine-tuned version of google/gemma-4-26B-A4B-it, optimized heavily on complex programming and software engineering tasks (such as the Evol-Instruct-Code dataset). It has been specifically quantized and converted to the GGUF format at 4-bit precision (q4_k_m), making it widely compatible with Windows, Linux, and Mac setups through tools like LM Studio, Ollama, and llama.cpp.
Key Features
Unmatched Coding Ability: Fine-tuned specifically for reasoning, complex debugging, algorithmic generation, and software architecture.
Universal GGUF Format: Compatible with almost any modern local LLM runner (llama.cpp, LM Studio, Text Generation WebUI).
4-bit Quantization: Uses the q4_k_m quantization method to squeeze the massive 26B parameter intelligence into a memory footprint that comfortably runs on 16GB+ RAM setups while preserving high precision.
