gemma-4-26B-A4B-it-qat-GGUF PC with NPU Offline Setup

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gemma-4-26B-A4B-it-qat-GGUF PC with NPU Offline Setup

Using a native PowerShell script is the absolute quickest way to install this model.

Please follow the instructions listed below to get started.

The installer automatically pulls the model (could be multiple GBs).

The smart installation system will instantly find the perfect configuration.

đź”— SHA sum: 061032c564e1304347bc5bf2acd3a798 | Updated: 2026-06-26
  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk: 150+ GB for high-context vector database storage
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

gemma-4-26B-A4B-it-qat-GGUF is a large language model built on the Gemma architecture with 26 billion parameters. It employs *QAT* techniques to improve inference efficiency while maintaining high performance. The model offers an 8K token context window, enabling detailed reasoning and long‑form generation. Benchmarks demonstrate *competitive* results across multilingual tasks, especially in code generation and factual QA. Its GGUF format ensures broad compatibility with inference engines and reduces memory usage for deployment.

Parameters 26 B
Context Length 8K tokens
Quantization QAT (GGUF)
Architecture Gemma‑4
Primary Use Text generation, code, QA
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