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gemma-4-31B-it-AWQ-4bit PC with NPU Uncensored Edition Windows

gemma-4-31B-it-AWQ-4bit PC with NPU Uncensored Edition Windows

The fastest way to get this model running locally is via Optional Features.

Kindly follow the on-screen instructions below.

All large files and heavy weights are downloaded automatically by the script.

The smart installation system will instantly find the perfect configuration.

đź’ľ File hash: 1c45b8cbebcb796b32c56feea6a38993 (Update date: 2026-07-01)
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  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Gemma-4-31B-it-AWQ-4bit model is a 31‑billion parameter instruction‑tuned language model optimized for efficient inference. It leverages AWQ quantization to achieve 4‑bit precision while preserving much of the original performance. The model supports a 2048‑token context window, enabling coherent long‑form 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 consumer‑grade 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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