If you want the fastest local installation for this model, use Docker.
Use the instructions provided below to complete the setup.
The loader auto-caches the model archive (several GBs included).
There is no manual tuning required; the builder will automatically deploy the best matching configuration.
The Gemma-4-31B-it-qat-w4a16-ct is a large language model designed for instruction following and conversational tasks. It leverages 31鈥痓illion parameters to achieve a balance between accuracy and computational efficiency. The model employs QAT (quantized aware training) combined with a w4a16 format, enabling reduced memory footprint while preserving performance. Its CT architecture incorporates advanced attention mechanisms that improve context retention and response relevance. The following table summarizes key technical attributes.
| Parameter Count | 31鈥疊 |
| Quantization | QAT (w4a16) |
| Precision | 16鈥慴it float |
| Training Method | Instruction鈥慺ollowing fine鈥憈uning |
| Architecture | CT with enhanced attention |
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