# QNN EP ABI

ONNX Runtime supports hardware acceleration through Execution Providers (EPs). The [QNN EP](https://github.com/onnxruntime/onnxruntime-qnn) is a plugin‑based execution provider, distributed as a standalone shared library that integrates with a standard ONNX Runtime installation at runtime, without requiring a custom ONNX Runtime build.

![../../_images/qnn_ep_plugin.png](data:image/png;base64,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)

QNN EP Plugin Architecture

## Prerequisites

- Python amd64 version 3.12.6
- Visual Studio Redistributable Version 14.44.35208 or above
- onnxruntime-qnn python package

Follow the steps in `Setup` section to automatically download and install these prerequisites.

### Setup

Complete ths setup before you run the tutorial. It takes approximately five minutes. For more information about the setup, see [ort_setup.ps1](https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Scripts/ort_setup.ps1)

1. Open PowerShell in administrator mode and run the following commands to install the dependencies. PowerShell must be in administrator mode to grant the elevated permissions required to automatically install the necessary applications and execute the PowerShell scripts.
2. Set `$DIR_PATH`. It’s `C:\WoS_AI` by default although you can change it to your desired path.

$DIR_PATH  = "C:\WoS_AI"
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3. Run the following command to download the setup script.

if (!(Test-Path $DIR_PATH\Downloads\Setup_Scripts)) {mkdir $DIR_PATH\Downloads\Setup_Scripts}
        Invoke-WebRequest -O ort_setup.ps1 https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Scripts/ort_setup.ps1
        Move-Item -Path ".\ort_setup.ps1" -Destination $DIR_PATH\Downloads\Setup_Scripts -Force
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4. If your system blocks running scripts, run the following command and enter ‘A’(Yes for all).

Set-ExecutionPolicy RemoteSigned
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5. Run the following commands to install the dependencies for QNN EP.

    ORT-QNN-EP-Plugin setup:

cd $DIR_PATH
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powershell -command "&{. .\Downloads\Setup_Scripts\ort_setup.ps1; ORT_QNN_PLUGIN_Setup -rootDirPath $DIR_PATH}"
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    The command downloads and installs the following dependencies:

> 
> 
> - Python amd64 version 3.12.6
>     - Model artifacts include mobilenet\_v2.onnx model and io\_utils.py for pre/post processing.
>     - Visual Studio Redistributable Version 14.44.35208
>     - Creates a virtual environment (SDX\_ORT\_QNN\_PLUGIN\_ENV) with the necessary libraries for the QNN EP.
>     - onnxruntime-qnn
6. When setup is complete, the following folder structure is in $DIR\_PATH:

> 
> 
> ![../../_images/folders_structure_ort.png](data:image/png;base64,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)

> 
> 
> - `Downloads`: This folder stores all the files required to complete the setup, such as Python installers and setup scripts.
> - `Python_Env`: This directory contains the virtual environment (SDX\_ORT\_QNN\_PLUGIN\_ENV) created for the EPs.
> - `Debug_Logs`: This directory contains logs corresponding to the setup.
> - `Models`: This directory holds model sub-directories and their respective artifacts (for example, Mobilenet\_v2).

### ORT QNN tutorial

This tutorial describes usages of ORT QNN EP Plugin for running the classification model (Mobilenet\_v2) on the CPU/GPU/NPU backend.

1. Open a PowerShell and run the following commands to set DIR\_PATH and activate the Python virtual environment. Ensure that DIR\_PATH is the same as the one used during the setup.

${DIR_PATH} = "C:\WoS_AI"
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powershell -NoExit -command "&{cd $DIR_PATH; . .\Downloads\Setup_Scripts\ort_setup.ps1; Activate_ORT_QNN_PLUGIN_VENV -rootDirPath $DIR_PATH}"
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Note

The below example is for the MobileNet model. If you need to try the same example for a different model, use the existing Python virtual environment (SDX\_ORT\_QNN\_PLUGIN\_ENV) and handle the dependencies by providing the absolute path.

Tab CPU
Tab GPU
Tab NPU

1. Run the following to create the `ort_qnn_plugin_cpu.py` file in the working directory.

notepad.exe ort_qnn_plugin_cpu.py
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2. Copy the following code into the `ort_qnn_plugin_cpu.py` file and save.

#File_name : ort_qnn_plugin_cpu.py
        
        import onnxruntime as ort
        import onnxruntime_qnn as qnn_ep
        import io_utils
        import time
        
        # Register QNN EP library
        ep_lib_path = qnn_ep.get_library_path()
        ep_registration_name = "QNNExecutionProvider"
        ort.register_execution_provider_library(ep_registration_name, ep_lib_path)
        
        # Select QNN EP device
        all_ep_devices = ort.get_ep_devices()
        selected_ep_devices = [ep_device for ep_device in all_ep_devices if ep_device.ep_name == ep_registration_name]
        
        # Configure and create session
        ep_options = {'backend_path': qnn_ep.get_qnn_cpu_path()}
        print("ep_options: ",ep_options)
        session_options = ort.SessionOptions()
        session_options.add_provider_for_devices(selected_ep_devices, ep_options)
        session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)

        img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
        raw_img = io_utils.preprocess(img_path)
        
        outputs = session.get_outputs()[0].name
        inputs = session.get_inputs()[0].name
        
        # Model inferencing using preprocessed input.
        start_time = time.time()
        for i in range(10):
           prediction = session.run([outputs], {inputs: raw_img})
        end_time = time.time()
        execution_time = ((end_time-start_time) * 1000)/10
        
        # Step4: Output postprocessing
        io_utils.postprocess(prediction)
        print("Execution Time: ", execution_time, "ms")
        
        # Clean up
        del session
        ort.unregister_execution_provider_library(ep_registration_name)
        Copy to clipboard
3. Execute the `ort_qnn_plugin_cpu.py` Python script from the working directory.

python .\ort_qnn_plugin_cpu.py
        Copy to clipboard

    This script uses Python utilities to preprocess a specified .jpg image according to the model’s requirements and sends it to the CPU EP for inference.
The results from the CPU EP inference are then processed to show the identified object’s class and probability, as shown in the following example.

![../../_images/ort_qnn_plugin_cpu.png](data:image/png;base64,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)

    The inference results in the previous image show that the model identified a “coffee mug” as an object in the input image  with a probability score of ~89.6%.

1. Run the following to create the `ort_qnn_plugin_gpu.py` file in the working directory.

notepad.exe ort_qnn_plugin_gpu.py
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2. Copy the following code into the `ort_qnn_plugin_gpu.py` file and save.

#File_name : ort_qnn_plugin_gpu.py
        
        import onnxruntime as ort
        import onnxruntime_qnn as qnn_ep
        import io_utils
        import time
        
        # Register QNN EP library
        ep_lib_path = qnn_ep.get_library_path()
        ep_registration_name = "QNNExecutionProvider"
        ort.register_execution_provider_library(ep_registration_name, ep_lib_path)
        
        # Select QNN EP device
        all_ep_devices = ort.get_ep_devices()
        selected_ep_devices = [ep_device for ep_device in all_ep_devices if ep_device.ep_name == ep_registration_name]
        
        # Configure and create session
        ep_options = {'backend_path': qnn_ep.get_qnn_gpu_path()}
        print("ep_options: ",ep_options)
        session_options = ort.SessionOptions()
        session_options.add_provider_for_devices(selected_ep_devices, ep_options)
        session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)

        img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
        raw_img = io_utils.preprocess(img_path)
        
        outputs = session.get_outputs()[0].name
        inputs = session.get_inputs()[0].name
        
        # Model inferencing using preprocessed input.
        start_time = time.time()
        for i in range(10):
           prediction = session.run([outputs], {inputs: raw_img})
        end_time = time.time()
        execution_time = ((end_time-start_time) * 1000)/10
        
        # Step4: Output postprocessing
        io_utils.postprocess(prediction)
        print("Execution Time: ", execution_time, "ms")
        
        # Clean up
        del session
        ort.unregister_execution_provider_library(ep_registration_name)
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3. Execute the `ort_qnn_plugin_gpu.py` Python script from the working directory.

python .\ort_qnn_plugin_gpu.py
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    This script uses Python utilities to preprocess a specified .jpg image according to the model’s requirements and sends it to the GPU EP for inference.
The results from the GPU EP inference are then processed to show the identified object’s class and probability, as shown in the following example.

![../../_images/ort_qnn_plugin_gpu.png](data:image/png;base64,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)

    The inference results in the previous image show that the model identified a “coffee mug” as an object in the input image  with a probability score of ~89.6%.

Note

Both FP32 and FP16 precision models are supported.

1. Just-in-time (JIT) : The model can be executed directly using ORT with online graph preparation. Following tutorial demonstrates the workflow of JIT approach.

    This section introduces the inference of the model on the NPU backend.

    - Run the following to create the `ort_qnn_plugin_npu.py` file in the working directory.

> 
> 
> notepad.exe ort_qnn_plugin_npu.py
>             Copy to clipboard
    - Copy the following code into the `ort_qnn_plugin_npu.py` file and save.

> 
> 
> #File_name : ort_qnn_plugin_npu.py
>             
>             import onnxruntime as ort
>             import onnxruntime_qnn as qnn_ep
>             import io_utils
>             import time
>             
>             # Register QNN EP library
>             ep_lib_path = qnn_ep.get_library_path()
>             ep_registration_name = "QNNExecutionProvider"
>             ort.register_execution_provider_library(ep_registration_name, ep_lib_path)
>             
>             # Select QNN EP device
>             all_ep_devices = ort.get_ep_devices()
>             selected_ep_devices = [ep_device for ep_device in all_ep_devices if ep_device.ep_name == ep_registration_name]
>             
>             # Configure and create session
>             ep_options = {'backend_path': qnn_ep.get_qnn_htp_path()}
>             print("ep_options: ",ep_options)
>             session_options = ort.SessionOptions()
>             session_options.add_provider_for_devices(selected_ep_devices, ep_options)
>             session_options.add_session_config_entry("session.disable_cpu_ep_fallback", "1")
>             session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)
>             
>             # Set run options for this specific inference
>             run_options = ort.RunOptions()
>             run_options.add_run_config_entry("qnn.perf_mode", "burst")
>             run_options.add_run_config_entry("qnn.rpc_control_latency", "100")
>             
>             img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
>             raw_img = io_utils.preprocess(img_path)
>             
>             outputs = session.get_outputs()[0].name
>             inputs = session.get_inputs()[0].name
>             
>             # Model inferencing using preprocessed input.
>             start_time = time.time()
>             for i in range(10):
>                prediction = session.run([outputs], {inputs: raw_img})
>             end_time = time.time()
>             execution_time = ((end_time-start_time) * 1000)/10
>             
>             # Step4: Output postprocessing
>             io_utils.postprocess(prediction)
>             print("Execution Time: ", execution_time, "ms")
>             
>             # Clean up
>             del session
>             ort.unregister_execution_provider_library(ep_registration_name)
>             Copy to clipboard
> 
> 
> Note
> 
> 
> To configure the NPU in performance mode, set the `qnn.perf_mode` option in the execution provider option as shown in the previous example.
> For all available options, refer to [QNN EP Plugin Configuration options](https://github.com/onnxruntime/onnxruntime-qnn/blob/main/docs/execution_providers/QNN-ExecutionProvider.md#configuration-options).
    - Execute the `ort_qnn_plugin_npu.py` Python script from the working directory.

> 
> 
> python .\ort_qnn_plugin_npu.py
>             Copy to clipboard
> 
> 
> This script uses Python utilities to preprocess a specified .jpg image according to the model’s requirements and sends it to the QNN EP for inference.
> The results from the QNN EP inference are then processed to show the identified object’s class and probability, as illustrated in the following example.
> 
> ![../../_images/ort_qnn_plugin_npu.png](data:image/png;base64,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)
> 
> The inference results in the previous image show that the model identified a “coffee mug” as an object in the input image  with a probability score of ~90%.
2. Ahead-of-time (AoT): The model’s context binary can be used to run a cached model, thereby eliminating model initialization time. The following tutorial demonstrates the AOT workflow.

    - Run the following to create the ort\_npu\_plugin\_ctx.py file in the working directory.

> 
> 
> notepad.exe ort_npu_plugin_ctx.py
>             Copy to clipboard
    - Copy the following code into the *ort\_npu\_plugin\_ctx.py* file and save.

> 
> 
> #File_name : ort_npu_plugin_ctx.py
>             
>             import onnxruntime as ort
>             import onnxruntime_qnn as qnn_ep
>             import io_utils
>             import time
>             
>             # Register QNN EP library
>             ep_lib_path = qnn_ep.get_library_path()
>             ep_registration_name = "QNNExecutionProvider"
>             ort.register_execution_provider_library(ep_registration_name, ep_lib_path)
>             
>             # Select QNN EP device
>             all_ep_devices = ort.get_ep_devices()
>             selected_ep_devices = [ep_device for ep_device in all_ep_devices if ep_device.ep_name == ep_registration_name]
>             
>             # Configure and create session
>             ep_options = {'backend_path': qnn_ep.get_qnn_htp_path()}
>             print("ep_options: ",ep_options)
>             session_options = ort.SessionOptions()
>             session_options.add_provider_for_devices(selected_ep_devices, ep_options)
>             session_options.add_session_config_entry("ep.context_enable","1")
>             session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)
>             
>             # Clean up
>             del session
>             ort.unregister_execution_provider_library(ep_registration_name)
>             Copy to clipboard
    - Execute the *ort\_npu\_plugin\_ctx.py* Python script from the working directory.

> 
> 
> python .\ort_npu_plugin_ctx.py
>             Copy to clipboard
> 
> 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)
    - This will create mobilenet\_v2\_ctx.onnx ctx onnx model that can be used for offline model inferencing.
    - Follow the `JIT` section and create `ort_qnn_plugin_npu.py` script and change the model name to **mobilenet\_v2\_ctx.onnx**.
    - Execute the `ort_qnn_plugin_npu.py` Python script from the working directory.

> 
> 
> python .\ort_qnn_plugin_npu.py
>             Copy to clipboard
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)

Note

The preceding tutorial demonstrates inference using an FP16 MobileNet‑V2 model. Developers can further optimize the model through [Olive](https://docs.qualcomm.com/doc/80-62010-1/topic/olive.html#olive-optimization) by applying quantization and perform inference on the optimized model using ONNX Runtime (ORT).

### Accuracy debugger

QAIRT provides the `qairt-accuracy-debugger` tool for identifying inaccuracies in neural networks at the layer level. This tool performs a comparison between the reference (golden) outputs generated by executing a model within an ML framework and the corresponding outputs obtained when running the same model on target hardware platforms, such as NPUs, CPUs, or GPUs.

Refer to the [Accuracy Debugger](https://docs.qualcomm.com/doc/80-62010-1/topic/accuracy_debugger.html#accuracy-debugger) section for an example using the MobileNet\_v2 model.

### Performance analysis

Optrace profiling provides you with visibility into how an AI model or network ran on the NPU hardware. It offers a detailed analysis of the execution flow and performance characteristics of the network on the NPU.
For more details, see [QAIRT Optrace](https://docs.qualcomm.com/doc/80-62010-1/topic/qnn-optrace.html#optrace).

### Next steps

Now that you know how to run a model using the QNN EP, go back to [ONNX Runtime](https://docs.qualcomm.com/doc/80-62010-1/topic/ort.html) or continue to the next section to try model inference with [HuggingFace Optimum + ONNX RT](https://docs.qualcomm.com/doc/80-62010-1/topic/hf-optimum-ort.html#hf-optimum-ort).

### More details

> 
> 
> - [Learn more about ONNX Runtime QNN EP Plugin](https://github.com/onnxruntime/onnxruntime-qnn).
> - [Microsoft ORT QNN EP Plugin releases](https://github.com/onnxruntime/onnxruntime-qnn/releases)
> - [C++ ORT QNN EP Plugin example](https://github.com/onnxruntime/onnxruntime-qnn/blob/main/docs/execution_providers/QNN-ExecutionProvider.md#c)

### FAQs

- Which Python version is supported?

> 
> 
> - ONNX Runtime QNN EP requires Python amd64 versions 3.10.4 to 3.12.x
> 
> 
> 
> > 
> > 
> > - Tutorial examples validated with [python-3.12.6-amd64](https://www.python.org/ftp/python/3.12.6/python-3.12.6-amd64.exe)
- How to run inference using C/C++?

> 
> 
> - Use this  [example](https://github.com/onnxruntime/onnxruntime-qnn/blob/main/docs/execution_providers/QNN-ExecutionProvider.md#c)  to run inference using C/C++.
- How to run FP32 model?

    - FP32 model by default run on FP16 precision when NPU backed is chosen.
- How to specify NPU backend?

> 
> 
> - Either use `{'backend_path': qnn_ep.get_qnn_htp_path()}` or `{"backend_type": "htp"}` in the `ep_options`, but not both.
- How to enable CPU fallback for ORT-QNN?

> 
> 
> - To enable CPU fallback, update the `ort_qnn_plugin_npu.py` by changing `session.disable_cpu_ep_fallback` to `0` as below:
> 
> 
> 
> > 
> > 
> > session_options = ort.SessionOptions()
> >             session_options.add_provider_for_devices(selected_ep_devices, ep_options)
> >             session_options.add_session_config_entry("session.disable_cpu_ep_fallback", "0")
> >             session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)
> >             Copy to clipboard
- How to enable Debug log for model execution?

> 
> 
> - To enable debug log, add the `log_severity_level` in the session options as below:
> 
> 
> 
> > 
> > 
> > session_options = ort.SessionOptions()
> >             session_options.add_provider_for_devices(selected_ep_devices, ep_options)
> >             session_options.log_severity_level = 0
> >             session = ort.InferenceSession("mobilenet_v2.onnx", sess_options=session_options)
> >             Copy to clipboard

Last Published: Jun 16, 2026

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