Forked from google/gemma-4-26b-a4b-qat
Capabilities
Minimum system memory
Tags
Last updated
Updated 26 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
Gemma 4 26B A4B QAT is the Quantization-Aware Training version of Gemma 4 26B A4B. 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 26B A4B uses an efficient architecture for scalable local deployment. The QAT build helps make that setup lighter to load while keeping the same model family behavior.
