Description
Gemma 4 31B optimized with Quantization-Aware Training (QAT)
Capabilities
Minimum system memory
Tags
Last updated
Updated 22 days agobyREADME
Gemma 4 31B QAT is the Quantization-Aware Training version of Gemma 4 31B. 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 31B is a larger Gemma 4 model. It is suited for stronger reasoning, coding, and agentic workflows while still benefiting from the memory savings of QAT.
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
Description
Gemma 4 31B optimized with Quantization-Aware Training (QAT)
Capabilities
Minimum system memory
Tags
Last updated
Updated 22 days agobyREADME
Gemma 4 31B QAT is the Quantization-Aware Training version of Gemma 4 31B. 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 31B is a larger Gemma 4 model. It is suited for stronger reasoning, coding, and agentic workflows while still benefiting from the memory savings of QAT.
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