# Tutorial - Use IR Backend by Using the Qualcomm® AI Engine Direct Delegate Qualcomm® AI Engine Direct Delegate has provided IR backend for users to generate a DLC from a model. This tutorial demonstrates how to use the IR backend with the Qualcomm® AI Engine Direct Delegate. We will go through how to use qtld-net-run to generate a DLC on a specified path. ## Prerequisites The following list of prerequisites must be met before starting this tutorial: 1. Finish [Tutorial qtld-net-run](https://docs.qualcomm.com/doc/80-63442-50/topic/tutorial_qtld_net_run.html) ## How to Generate DLC by Using qtld-net-run Please specify backend and ir_dlc_path. $ adb shell 'export LD_LIBRARY_PATH=/data/local/tmp/qnn_delegate/:$LD_LIBRARY_PATH && export ADSP_LIBRARY_PATH="/data/local/tmp/qnn_delegate/" && cd /data/local/tmp/qnn_delegate/inception_v3_quant/ && /data/local/tmp/qnn_delegate/qtld-net-run \ --model inception_v3_quant.tflite \ --input target_raw_list.txt \ --output output \ --backend ir \ --ir_dlc_path /data/local/tmp/qnn_delegate/inception_v3_quant.dlc Copy to clipboard The output should look similar to the following: TFLite model: [inception_v3_quant.tflite] Input list file: [target_raw_list.txt] Total number of inferences: [1] Using QNN Backend: [ir] IR DLC Path: [/data/local/tmp/qnn_delegate/inception_v3_quant.dlc] Loaded model successfully. === Pre-invoke Interpreter State === Line 945: Allocated 1 input tensor(s) Line 955: Allocated 1 output tensor(s) === Invoking Interpreter === Copy to clipboard You should find the DLC is generated on the specified path. Last Published: Oct 10, 2025 [Previous Topic A Running Example using Profiler APIs](https://docs.qualcomm.com/bundle/publicresource/80-63442-50/topics/tutorial_qtld_profiler.md) [Next Topic Acceleration Support](https://docs.qualcomm.com/bundle/publicresource/80-63442-50/topics/support.md)