# QNN EP Non-ABI

The section demonstrates using [ONNX Runtime (ORT) with QNN](https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html#qnn-execution-provider) as the execution provider (EP) to accelerate workloads on the Hexagon Tensor Processor (HTP) which is specifically designed to handle neural networks. The QNN EP also provides a CPU backend that you can use to run the AI workloads in FP32 precision on the Qualcomm^®^ Oryon^™^ CPU.

## Prerequisites

- Python amd64 version 3.12.6
- Visual Studio Redistributable Version 14.44.35208 or above
- onnxruntime-qnn==1.24.4 python package

Complete the steps in the following section to automatically download and install the prerequisites.

## Setup

This tutorial requires the following setup which 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. You must run PowerShell 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.

cd $DIR_PATH
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powershell -command "&{. .\Downloads\Setup_Scripts\ort_setup.ps1; ORT_QNN_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\_ENV) with the necessary libraries for the QNN EP.
>     - onnxruntime-qnn==1.24.4

Note

Avoid installing any other ONNX Runtime variant in this environment. The setup.ps1 script installs the necessary onnxruntime-directml. Installing a different variant may result in fetching the incorrect ONNX Runtime variant and may cause issues.
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, setup scripts, etc.
> - `Python_Env`: This directory contains the virtual environment (SDX\_ORT\_QNN\_ENV) created for the EPs.
> - `Debug_Logs`: This directory contains logs corresponding to setup.
> - `Models`: This directory holds model sub-directories and its respective artifacts(Ex: Mobilenet\_v2).

## ORT QNN tutorial

This tutorial describes usages of ORT QNN EP 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_VENV -rootDirPath $DIR_PATH}"
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Note

The following 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\_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_cpu.py` file in the working directory.

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

#File_name : ort_qnn_cpu.py
        
        import onnxruntime as ort
        import numpy as np
        import time
        #Qualcomm utility for pre-/postprocessing of input/outputs in model inference
        import io_utils
        
        # Step1: Runtime and model initialization
        # Set QNN Execution Provider options.
        execution_provider_option = {"backend_path": "QnnCpu.dll"}
        
        # Create ONNX Runtime session.
        onnx_model_path = "./mobilenet_v2.onnx"
        
        session = ort.InferenceSession(onnx_model_path,
                                      providers=["QNNExecutionProvider"],
                                      provider_options=[execution_provider_option])
        
        # Step2: Input/Output handling, Generate raw input
        # github repo for below artifact: https://github.com/quic/wos-ai/tree/main/Artifacts
        img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
        raw_img = io_utils.preprocess(img_path)

        # Model input and output names
        outputs = session.get_outputs()[0].name
        inputs = session.get_inputs()[0].name
        
        # Step3: 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")
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3. Execute the `ort_qnn_cpu.py` Python script from the working directory.

python .\ort_qnn_cpu.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 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_cpu.png](data:image/png;base64,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)

    Based on the inference results in the previous figure, 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\_gpu.py file in the working directory.

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

#File_name : ort_qnn_gpu.py
        
        import onnxruntime as ort
        import numpy as np
        import time
        #Qualcomm utility for pre-/postprocessing of input/outputs in model inference
        import io_utils
        
        # Step1: Runtime and model initialization
        # Set QNN Execution Provider options.
        execution_provider_option = {"backend_path": "QnnGpu.dll"}
        
        # Create ONNX Runtime session.
        onnx_model_path = "./mobilenet_v2.onnx"
        
        session = ort.InferenceSession(onnx_model_path,
                                      providers=["QNNExecutionProvider"],
                                      provider_options=[execution_provider_option])
        
        # Step2: Input/Output handling, Generate raw input
        # github repo for below artifact: https://github.com/quic/wos-ai/tree/main/Artifacts
        img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
        raw_img = io_utils.preprocess(img_path)

        # Model input and output names
        outputs = session.get_outputs()[0].name
        inputs = session.get_inputs()[0].name
        
        # Step3: 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")
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3. Execute the `ort_qnn_gpu.py` Python script from the working directory.

python .\ort_qnn_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_gpu.png](data:image/png;base64,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)

    Based on the inference results in the previous figure, the model identified a “coffee mug” as an object in the input image, with a probability score of ~89.6%.

Note

The following error is due to the OpenCL driver dependency.

> 
> 
> 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)

If you see it, do the following:

    - Add the following code for enabling verbose logging in `ort_qnn_gpu.py` before ORT session creation.

> 
> 
> sess_opt = ort.SessionOptions()
>             sess_opt.log_severity_level = 0
>             Copy to clipboard
    - Pass `sess_opt` to `ort.InferenceSession` as follows:

> 
> 
> session = ort.InferenceSession(onnx_model_path,
>             sess_opt,
>             providers=["QNNExecutionProvider"],
>             provider_options=[execution_provider_option])
>             Copy to clipboard

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. The following tutorial demonstrates the workflow of the JIT approach.

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

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

> 
> 
> # File_name : ort_qnn_npu.py
>             
>             import onnxruntime as ort
>             import numpy as np
>             import time
>             #Qualcomm utility for pre-/postprocessing of input/outputs in model inference
>             import io_utils
>             
>             # Step1: Runtime and model initialization
>             # Set QNN Execution Provider options.
>             execution_provider_option = {"backend_path": "QnnHtp.dll",
>                                           "enable_htp_fp16_precision" : "1",
>                                        "htp_performance_mode": "high_performance"}
>             
>             # Create ONNX Runtime session.
>             onnx_model_path = "./mobilenet_v2.onnx"
>             options = ort.SessionOptions()
>             options.add_session_config_entry("session.disable_cpu_ep_fallback", "1")
>             
>             session = ort.InferenceSession(onnx_model_path,
>                                           providers=["QNNExecutionProvider"],
>                                           provider_options=[execution_provider_option])
>             
>             # Step2: Input/Output handling, Generate raw input
>             # github repo for below artifact: https://github.com/quic/wos-ai/tree/main/Artifacts
>             img_path = "https://raw.githubusercontent.com/quic/wos-ai/refs/heads/main/Artifacts/coffee_cup.jpg"
>             raw_img = io_utils.preprocess(img_path)
>             
>             
>             # Model input and output names
>             outputs = session.get_outputs()[0].name
>             inputs = session.get_inputs()[0].name
>             
>             # Step3: 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")
>             Copy to clipboard
> 
> 
> Note
> 
> 
> To configure the NPU in performance mode, set the `htp_performance_mode` option in the execution provider option as shown in the previous example. See [ORT QNN EP](https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html) for all available options.
    - Execute the `ort_qnn_npu.py` Python script from the working directory.

> 
> 
> python .\ort_qnn_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.
> 
> 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)
> 
> Based on the inference results in the previous figure, the model identified a “coffee mug” as an object in the input image, with a probability score of ~90%.
2. Ahead-of-Time (AoT): You can use the model’s context binary 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_ctx.py` file in the working directory.

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

> 
> 
> import onnxruntime as ort
>             
>             options = ort.SessionOptions()
>             options.add_session_config_entry("ep.context_enable","1")
>             # Set QNN Execution Provider options.
>             execution_provider_option = {"backend_path": "QnnHtp.dll",
>                                           "enable_htp_fp16_precision" : "1",
>                                        "htp_performance_mode": "high_performance"}
>             
>             # Create ONNX Runtime session.
>             onnx_model_path = "./mobilenet_v2.onnx"
>             
>             session = ort.InferenceSession(onnx_model_path,
>                                           sess_options=options,
>                                           providers=["QNNExecutionProvider"],
>                                           provider_options=[execution_provider_option])
>             del session
>             Copy to clipboard
    - Execute the `ort_npu_ctx.py` Python script from the working directory.

> 
> 
> python .\ort_npu_ctx.py
>             Copy to clipboard
> 
> 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)
    - This creates mobilenet\_v2\_ctx.onnx ctx onnx model that you can use for offline model inferencing.
    - Follow the [JIT section](https://docs.qualcomm.com/doc/80-62010-1/topic/ort-qnn-ep.html#ort-npu-run) and create a `ort_qnn_npu.py` script and change the model name to `mobilenet_v2_ctx.onnx`.
    - Execute the `ort_qnn_npu.py` Python script from the working directory.

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

Note

The previous 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 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.

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

## Performance analysis

Optrace profiling provides AI Runtime SDK users 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 Non-ABI, 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 [QNN EP ABI Tutorial](https://docs.qualcomm.com/doc/80-62010-1/topic/ort-qnn-ep-plugin.html#ort-qnn-ep-plugin).

## More details

> 
> 
> - [Learn more about ONNX Runtime QNN EP](https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html).
> - [Microsoft ORT Nuget Releases](https://www.nuget.org/packages/Microsoft.ML.OnnxRuntime.QNN)
> - [How to build C++ ORT QNN EP Sample App](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_cxx/QNN_EP/mobilenetv2_classification#how-to-run-the-application)

## FAQs

- **Which Python version is supported?**

> 
> 
> - ONNX Runtime QNN EP requires Python amd64 versions 3.8.10 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).
>     - ONNX Runtime QNN EP requires Python arm64 versions 3.11.x to 3.12.x.
> 
> 
> 
> > 
> > 
> > - If you use ORT QNN EP on arm64, it’s advised to create two Python environments: one with Python amd64 for preprocessing and postprocessing, and another with Python ARM for execution.
> >         - Note that Python arm64 has limitations with dependencies like PyTorch, ONNX, and other Python packages.
- **How to run inference using C/C++?**

> 
> 
> - Use this  [example](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_cxx/QNN_EP/mobilenetv2_classification)  to run inference using C/C++.
- **How to run FP32 model?**

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

> 
> 
> - Either use `{"backend_path": "QnnHtp.dll"}` or `{"backend_type": "htp"}` in the `execution_provider_option`, but not both.
- **How to enable CPU fallback for ORT-QNN?**

> 
> 
> - To enable CPU fallback, update the `ort_qnn_npu.py` by changing `session.disable_cpu_ep_fallback` to `0` as in the following example:
> 
> 
> 
> options = ort.SessionOptions()
>         options.add_session_config_entry("session.disable_cpu_ep_fallback", "0")
>         session = ort.InferenceSession(onnx_model_path,
>                                 sess_options=options,
>                                 providers=["QNNExecutionProvider"],
>                                 provider_options=[execution_provider_option])
>         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 in the following example:
> 
> 
> 
> options = ort.SessionOptions()
>         options.log_severity_level = 0 #0 = VERBOSE
>         session = ort.InferenceSession(onnx_model_path,
>                                 sess_options=options,
>                                 providers=["QNNExecutionProvider"],
>                                 provider_options=[execution_provider_option])
>         Copy to clipboard
- **How to check for the NPU availability?**

    - See [ORT Sample App with NPU availability check](https://github.com/quic/wos-ai/tree/main/apps/ORT_Sample_app_with_NPU_Availabilty_Check) for an example.
- **More details about QNN context binary feature?**

    - For more details about QNN context binary feature, see [QNN Context Binary](https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html#qnn-context-binary-cache-feature).
- **How to run the ONNX Profiler test?**

> 
> 
> - See the steps from [ONNX Profiler Test](https://github.com/microsoft/onnxruntime/tree/main/onnxruntime/test/perftest) to run the test.
>     - For more information about ONNX Profiler, see [Profiling Tools](https://onnxruntime.ai/docs/performance/tune-performance/profiling-tools.html#in-code-performance-profiling).
- **How to fix dynamic shape to static?**

> 
> 
> - To fix dynamic shape to static see [Making dynamic input shapes fixed](https://onnxruntime.ai/docs/tutorials/mobile/helpers/make-dynamic-shape-fixed.html).
- **How to run any other model using ORT-QNN EP?**

> 
> 
> See the following example:
> 
> 
> import onnxruntime as ort
>         import numpy as np
>         
>         # Step1: Runtime and model initialization
>         # Enter path to the model in the below
>         onnx_model_path = "path/to/model"
>         # Set QNN Execution Provider options.
>         execution_provider_option = {"backend_path": "QnnHtp.dll",
>                                    "htp_performance_mode": "high_performance"}
>         
>         # Step2: Input/Output handling, Generate raw input
>         input_shape = session.get_inputs()[0].shape
>         input_data = np.random.random(input_shape).astype(np.float32)
>         
>         # Model input name
>         input_name = session.get_inputs()[0].name
>         
>         # Step3: Model inferencing using preprocessed input.
>         result = session.run(None, {input_name: input_data})
>         Copy to clipboard

Last Published: Jun 16, 2026

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