How to Deploy gemma-4-26B-A4B-it-qat-GGUF PC with NPU Dummy Proof Guide

Docker offers the quickest path to setting up this model locally.

Refer to the instructions below to proceed.

The setup auto-downloads all needed files (several GBs).

During setup, the script automatically determines and applies the best settings tailored to your machine.

🔍 Hash-sum: 5c97f7414ee3b21322b95368d135ebe3 | 🕓 Last update: 2026-06-23 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 48 GB needed to prevent memory swapping to disk Disk Space: at least 100 GB for multiple local LLM variants GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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.

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