# Genie NPU

이 섹션에서는 LLM 추론을 NPU에 오프로드하는 절차에 대해 설명합니다. NPU를 사용하면 Genie 실행 워크플로우의 대부분을 유지하면서, LLM 추론 시 와트당 최상의 성능을 실현할 수 있습니다. 그러나 [Genie CPU 섹션](https://docs.qualcomm.com/doc/80-62010-1KO/topic/genie-cpu.html#genie-cpu) 에서 설명한 INT4 모델의 양자화와 달리, NPU는 AIMET 워크플로우를 사용하여 모델을 양자화해야 합니다.

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![../../_images/GenAiTransformer-backend-npu_numbers.png](data:image/png;base64,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)
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> Genie NPU 워크플로우

1. [AIHub](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llm_on_genie) 튜토리얼을 참조하여 NPU 가속화를 위한 INT4 양자화된 QNN 컨텍스트 바이너리 모델을 생성합니다.
2. AIHub LLM 튜토리얼을 사용하여 필수 LLM에 대해 양자화된 QNN 컨텍스트 바이너리를 얻은 후에는, GenAiTransformer 백엔드와 마찬가지로 genie-t2t-run 도구를 사용하여 QNN NPU 백엔드에서 LLM을 실행할 수 있습니다.

GenAiTransformer에서 QNN NPU로 백엔드를 전환하는 설정은 다음 예시와 같이 genie config에서 구성됩니다.

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)

Last Published: Jan 13, 2026

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