Docker offers the quickest path to setting up this model locally.
Please follow the instructions listed below to get started.
The installer auto-downloads and deploys the entire model pack.
The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.
The Gemma-4-31B-it-AWQ-4bit model is a 31тАСbillion parameter instructionтАСtuned language model optimized for efficient inference. It leverages AWQ quantization to achieve 4тАСbit precision while preserving much of the original performance. The model supports a 2048тАСtoken context window, enabling coherent longтАСform generation. Benchmarks show it rivals larger models on reasoning, coding, and multilingual tasks despite its reduced memory footprint. Its compact design makes it suitable for deployment on consumerтАСgrade hardware and edge devices. The following table compares key specifications with related models:
| Model | Parameters | Quantization | Context Length | Avg. Benchmark |
|---|---|---|---|---|
| Gemma-4-31B-it-AWQ-4bit | 31B | 4-bit AWQ | 2048 | 84.3 |
| Llama-2-70B | 70B | 16-bit | 4096 | 86.1 |
| Mistral-7B-v0.1 | 7B | 16-bit | 8192 | 78.5 |
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