Forked from google/gemma-4-12b-qat
Capabilities
Minimum system memory
Tags
Last updated
Updated 9 days agobyREADME
Custom Fields
Special features defined by the model author
Enable Thinking
: boolean
(default=true)
Controls whether the model will think before replying
Parameters
Custom configuration options included with this model
Sources
The underlying model files this model uses
Based on
GGUF
Gemma 4 12B QAT is the Quantization-Aware Training version of Gemma 4 12B. It aims to keep quality close to bfloat16 while using much less memory to load the model.
Gemma 4 is an open multimodal model family from Google DeepMind. It supports text and image input, text output, reasoning, long context, system prompts, and native tool use.
Gemma 4 12B uses the Unified design, which routes multimodal inputs into the decoder-only LLM backbone through lightweight projection layers instead of separate encoders. The QAT build keeps that architecture while reducing the memory needed to load the model.
