Install gemma-4-26B-A4B-it-qat-GGUF PC with NPU No Admin Rights

Deploying this model locally is quickest when done via Docker.

Refer to the instructions below to proceed.

The setup auto-streams the model assets (expect a multi-GB download).

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

📦 Hash-sum → ac8805232e8177e719a109a2908cb154 | 📌 Updated on 2026-06-24 Verify Processor: 6-core 3.5 GHz minimum required RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space:70 GB free space for full FP16 weights storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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