# Overview

The Qualcomm® Neural Processing SDK allows for the preparation and execution of AI models on Qualcomm supported hardware. It comes with tools to prepare your model for a target device, runtimes for executing your model on that device, and an API to control how your model interacts with your device’s processors.

In order to use your model on the target device, there are two major stages:

1. [Building and Executing your Model](https://docs.qualcomm.com/doc/80-63442-10/topic/building_and_executing_tutorial.html) on your target device.
2. [Creating an app that runs on your target device to use your model.](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup8.html).

The tools / binaries / executables that are needed for each stage will vary based on your host machine, target device, model, and which optimizations you enable.

## **Model Workflow**

![../images/snpe.png](data:image/png;base64,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)

Model training is performed on a popular deep learning framework (PyTorch, TFLite, ONNX, and TensorFlow models are supported by Qualcomm® Neural Processing SDK). After training is complete the trained model is converted into a DLC file that can be loaded into the Qualcomm® Neural Processing SDK runtime. This DLC file can then be used to perform forward inference passes using one of the Snapdragon accelerated compute cores.

The basic Qualcomm® Neural Processing SDK workflow consists of only a few steps:

1. Convert the network model to a DLC file that can be loaded by Qualcomm® Neural Processing SDK.
2. Optionally quantize the DLC file for running on the Hexagon DSP.
3. Prepare input data for the model.
4. Load and execute the model using Qualcomm® Neural Processing SDK runtime.

## **Understanding the docs**

These docs are organized based on the workflow above.

1. “[Setup](https://docs.qualcomm.com/doc/80-63442-10/topic/SNPE_general_setup.html)” explains how to install SNPE and all necessary dependencies to work with your model and target device.
2. “[Tutorials](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup6.html)” gives step by step guides for how to use SNPE in a variety of situations.
3. “[Network Models](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup1.html)” explains which network operations (ex. <cite>SoftMax</cite>) which your model may use are supported for which processors.
4. “[Input Data and Preprocessing](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup5.html)” explains how to format input data in a way your model can interpret.
5. “[Benchmarking and Accuracy](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup10.html)” explains how to test and analyze your model’s performance to optimize for your target device.
6. “[Tools](https://docs.qualcomm.com/doc/80-63442-10/topic/SNPE_general_tools.html)” provides a reference for all CLI tools that are used with SNPE.
7. “[Debug Tools](https://docs.qualcomm.com/doc/80-63442-10/topic/usergroup11.html)” provides a reference for additional debugging tools which may help resolve issues.
8. “[API](https://docs.qualcomm.com/doc/80-63442-10/topic/SNPE_general_api.html)” gives a detailed reference for how to use the SNPE API when developing your app / executable.
9. “[Limitations](https://docs.qualcomm.com/doc/80-63442-10/topic/limitations.html)” contains known issues and workarounds.
10. “[Revision History](https://docs.qualcomm.com/doc/80-63442-10/topic/SNPE_general_revision_history.html)” notes changes for each new version of the SNPE SDK.
11. “[References](https://docs.qualcomm.com/doc/80-63442-10/topic/appx_ref.html)” contains a glossary of terms.

**The best place to start for new readers is the** [Building and Executing a Model Tutorial](https://docs.qualcomm.com/doc/80-63442-10/topic/building_and_executing_tutorial.html) **as that will walk you through all the steps needed to work with your model (including the Setup steps).**

## **Detailed Capabilities**

The Qualcomm® Neural Processing SDK is a Qualcomm Snapdragon software accelerated runtime for the execution of deep neural networks. With the Qualcomm® Neural Processing SDK, users can:

- Execute an arbitrarily deep neural network.
- Execute the network on the Snapdragon CPU, the Adreno GPU or the Hexagon DSP.
- Debug the network execution on x86 Ubuntu Linux.
- Convert PyTorch, TFLite, ONNX, and TensorFlow models to a Qualcomm® Neural Processing SDK Deep Learning Container (DLC) file.
- Quantize DLC files to 8 or 16 bit fixed point for running on the Hexagon DSP.
- Debug and analyze the performance of the network with Qualcomm® Neural Processing SDK tools.
- Integrate a network into applications and other code via C++ or Java.

## **Supported Snapdragon Devices**

### Linux/Android

| **Snapdragon Device/Chip** | **Supported Tool Chains** | **CPU** | **GPU** | **DSP Hexagon Arch** | **AIP** |
| --- | --- | --- | --- | --- | --- |
| SD 8 Elite Gen 5 (SM8850) | aarch64-android | Yes | Yes | V81 | No |
| SD 8 Gen 4 (SM8750) | aarch64-android | Yes | Yes | V79 | No |
| SD 8 Gen 3 (SM8650) | aarch64-android | Yes | Yes | V75 | No |
| SD 8 Gen 2 (SM8550) | aarch64-android | Yes | Yes | V73 | No |
| SD 8s Gen 3 (SM8635) | aarch64-android | Yes | Yes | V73 | No |
| SD 8+ Gen 1 (SM8475) | aarch64-android | Yes | Yes | V69 | No |
| SD 8 Gen 1 (SM8450) | aarch64-android | Yes | Yes | V69 | No |
| 888+ (SM8350P) | aarch64-android | Yes | Yes | V68 | No |
| 888 (SM8350) | aarch64-android | Yes | Yes | V68 | No |
| 7+ Gen 3 (SM7675) | aarch64-android | Yes | Yes | V73 | No |
| 7 Gen 1 (SM7450) | aarch64-android | Yes | Yes | V69 | No |
| 778G (SM7325) | aarch64-android | Yes | Yes | V68 | No |
| QCM6490 | aarch64-android, aarch64-ubuntu-gcc9.4, aarch64-oe-linux-gcc11.2 | Yes | Yes | V68 | No |
| 865 (SM8250) | aarch64-android | Yes | Yes | V66 | Yes |
| 765 (SM7250) | aarch64-android | Yes | Yes | V66 | Yes |
| 750G (SM7225) | aarch64-android | Yes | Yes | V66 | Yes |
| 690 (SM6350) | aarch64-android | Yes | Yes | V66 | Yes |
| QRB5165U | aarch64-ubuntu-gcc9.4 | Yes | Yes | V66 | Yes |
| QRB5165LE | aarch64-oe-linux-gcc9.3, aarch64-oe-linux-gcc11.2 | Yes | Yes | V66 | Yes |
| QCS7230LA | aarch64-android | Yes | Yes | V66 | Yes |
| QCS7230LE | aarch64-oe-linux-gcc9.3, aarch64-oe-linux-gcc11.2 | Yes | Yes | V66 | Yes |
| 695 (SM6375) | aarch64-android | Yes | Yes | V66 | No |
| 680 (SM6225) | aarch64-android | Yes | Yes | V66 | No |
| 480 (SM4350/6325) | aarch64-android | Yes | Yes | V66 | No |
| 460 (SM4250) | aarch64-android | Yes | Yes | V66 | No |
| 662 (SM6115) | aarch64-android | Yes | Yes | V66 | No |
| QCS610LA | aarch64-android | Yes | Yes | V66 | No |
| QCS610LE | aarch64-oe-linux-gcc9.3 | Yes | Yes | V66 | No |
| QCS410LA | aarch64-android | Yes | Yes | V66 | No |
| QCS410LE | aarch64-oe-linux-gcc9.3 | Yes | Yes | V66 | No |
| QCM4290 | aarch64-android | Yes | Yes | V66 | No |
| QCM6125 | aarch64-android | Yes | Yes | V66 | No |
| QRB4210LE | aarch64-oe-linux-gcc9.3 | Yes | Yes | V66 | No |
| QCM4490 | aarch64-android | Yes | Yes | N/A | No |
| XR2 Gen 2 (SXR2230P) | aarch64-android | Yes | Yes | V69 | No |
| XR2 Gen 2 (SXR2250P) | aarch64-android | Yes | Yes | V69 | No |
| QCS/QCM8550LA | aarch64-android | Yes | Yes | V73 | No |
| QCS/QCM8550LE | aarch64-oe-linux-gcc11.2 | Yes | Yes | V73 | No |
| QCS9100 | aarch64-oe-linux-gcc11.2 | Yes | Yes | V73 | No |
| QCS/QCM6690 | aarch64-android | Yes | Yes | V73 | No |
| QCS/QCM2290 | aarch64-android | Yes | Yes | N/A | No |
| QCS8625 | aarch64-oe-linux-gcc11.2, aarch64-android | Yes | No | V75 | No |
| Dragonwing Q‑8750 | aarch64-oe-linux-gcc11.2, aarch64-android | Yes | Yes | V79 | No |
| SD W6 Gen 1 (SW6100) | aarch64-oe-linux-gcc11.2, arm-android, aarch64-android | Yes | Yes | V81 | No |

### Windows

| **Snapdragon Device/Chip** | **Supported Tool Chains** | **CPU** | **GPU** | **DSP Hexagon Arch** | **AIP** |
| --- | --- | --- | --- | --- | --- |
| Snapdragon X2 Elite Extreme (SC8480XP) | aarch64-windows-msvc, arm64x-windows-msvc | Yes | No | V81 | No |
| Snapdragon 8cx Gen 4 (SC8380XP) | aarch64-windows-msvc, arm64x-windows-msvc | Yes | No | V73 | No |
| Snapdragon 8cx Gen 3 (SC8280X) | aarch64-windows-msvc | Yes | No | V68 | No |
| Snapdragon 8cx Gen 2 (SC8180X) | aarch64-windows-msvc | Yes | No | V66 | No |
| Snapdragon 7c gen 2 (SC7280X) | aarch64-windows-msvc | Yes | No | V68 | No |

Note

See  [Windows ARM64X Support](https://docs.qualcomm.com/doc/80-63442-10/topic/arm64x_support.html) for more information about arm64x-windows-msvc toolchain.

## **What’s included in the SDK**

### Linux/Android

| **SDK Asset** | **Type** | **Compiler** | **C++ STL** | **Description** |
| --- | --- | --- | --- | --- |
| bin/x86\_64-linux-clang | binary | clang | libc++ 14 | x86 Linux binaries |
| bin/aarch64-android | binary | clang | libc++ | Aarch64 Android binaries |
| bin/arm-android | binary | clang | libc++ | Arm Android binaries |
| bin/aarch64-ubuntu-gcc9.4 | binary | gcc9.4 | gnustl | Aarch64 Ubuntu binaries |
| bin/aarch64-oe-linux-gcc8.2 | binary | gcc8.2 | gnustl | Aarch64 Linux binaries |
| bin/aarch64-oe-linux-gcc9.3 | binary | gcc9.3 | gnustl | Aarch64 Linux binaries |
| bin/aarch64-oe-linux-gcc11.2 | binary | gcc11.2 | gnustl | Aarch64 Linux binaries |
| lib/android | lib | - | - | Android aar file used to include SNPE into your application |
| lib/x86\_64-linux-clang | lib | clang | libc++ 14 | x86 Linux libraries |
| lib/aarch64-android | lib | clang | libc++ | Aarch64 Android libraries |
| lib/arm-android | lib | clang | libc++ | Arm Android libraries |
| lib/hexagon-&lt;dsp\_version&gt; | lib | - | - | Hexagon DSP runtime libraries |
| lib/aarch64-ubuntu-gcc9.4 | lib | gcc9.4 | gnustl | Aarch64 Ubuntu libraries |
| lib/aarch64-oe-linux-gcc8.2 | lib | gcc8.2 | gnustl | Aarch64 Linux libraries |
| lib/aarch64-oe-linux-gcc9.3 | lib | gcc9.3 | gnustl | Aarch64 Linux libraries |
| lib/aarch64-oe-linux-gcc11.2 | lib | gcc11.2 | gnustl | Aarch64 Linux libraries |
| lib/python | lib | - | - | Qualcomm (R) Neural Processing SDK Python model tools modules |
| include/SNPE | include dir | - | - | Qualcomm (R) Neural Processing SDK API header files |
| examples | examples dir | - | - | Source code sample applications in Native C, C++ and Android Java |
| docs | documents | - | - | Reference Guide |
| benchmarks | scripts | - | - | Benchmark framework to gather runtime performance data on devices |

### Windows

| **SDK Asset** | **Type** | **Compiler** | **C++ STL** | **Description** |
| --- | --- | --- | --- | --- |
| bin/x86\_64-windows-msvc | binary | MSVC | MSVC | x86\_64 Windows binaries |
| bin/aarch64-windows-msvc | binary | MSVC | MSVC | ARM64 Windows binaries |
| bin/arm64x-windows-msvc | binary | MSVC | MSVC | ARM64X Windows binaries |
| lib/x86\_64-windows-msvc | lib | MSVC | MSVC | x86\_64 Windows libraries |
| lib/aarch64-windows-msvc | lib | MSVC | MSVC | ARM64 Windows libraries |
| lib/arm64x-windows-msvc | lib | MSVC | MSVC | ARM64X Windows libraries |
| lib/hexagon-v66 | lib | - | - | Hexagon DSP v66 runtime libraries |
| lib/hexagon-v68 | lib | - | - | Hexagon DSP v68 runtime libraries |
| lib/hexagon-v73 | lib | - | - | Hexagon DSP v73 runtime libraries |
| lib/python | lib | - | - | Qualcomm (R) Neural Processing SDK Python model tools modules |
| include/SNPE | include dir | - | - | Qualcomm (R) Neural Processing SDK API header files |
| examples | examples dir | - | - | Source code sample applications in Native C++ |
| docs | documents | - | - | Reference Guide |
| share | resources | - | - | Qualcomm (R) Neural Processing SDK Udo resources |

## **Important Files and Locations**

$SNPE\_ROOT refers to the base directory where the SDK is installed.

### Linux/Android

| File | Type | Details | Location |
| --- | --- | --- | --- |
| envsetup.sh | script | Sets up environment variables needed to run SDK tools and binaries | <ul class="simple"><br><li><p>$SNPE_ROOT/bin</p></li><br></ul> |
| snpe-onnx-to-dlc | script | Converts an ONNX model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-tensorflow-to-dlc | script | Converts a TensorFlow model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-tflite-to-dlc | script | Converts a TfLite model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-pytorch-to-dlc | script | Converts a Pytorch model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-quant | executable | Quantize a DLC file using 8/16 bit quantization | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-graph-prepare | executable | Prepares (offline) a graph for HTP on the host | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-quantize | script | Invokes snpe-dlc-quant and snpe-dlc-graph-prepare (for backward compatibility) | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-diagview | executable | Displays Neural Processing SDK timing output | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-info | script | Prints DLC file information | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-viewer | script | Displays a DLC file as an HTML file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-dlc-diff | script | Compares two different DLC files | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe-udo-package-generator | executable | Generates a UDO package | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br></ul> |
| snpe\_bench.py | script | Executes DLC model on device and collect benchmark information | <ul class="simple"><br><li><p>$SNPE_ROOT/benchmarks</p></li><br></ul> |
| snpe-net-run | executable | Executes neural networks using SDK APIs | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-linux-clang</p></li><br><li><p>$SNPE_ROOT/bin/aarch64-android</p></li><br><li><p>$SNPE_ROOT/bin/arm-android</p></li><br><li><p>$SNPE_ROOT/bin/aarch64-oe-linux-gcc8.2</p></li><br><li><p>$SNPE_ROOT/bin/aarch64-oe-linux-gcc9.3</p></li><br></ul> |
| libSNPE.so | library | Qualcomm® Neural Processing SDK runtime for host and device development | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/x86_64-linux-clang</p></li><br><li><p>$SNPE_ROOT/lib/aarch64-android</p></li><br><li><p>$SNPE_ROOT/lib/arm-android</p></li><br><li><p>$SNPE_ROOT/lib/aarch64-oe-linux-gcc8.2</p></li><br><li><p>$SNPE_ROOT/lib/aarch64-oe-linux-gcc9.3</p></li><br></ul> |
| libHtpPrepare.so | library | Library for offline graph preparation for HTP | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/x86_64-linux-clang</p></li><br></ul> |
| libSnpeDspV66Skel.so | library | Hexagon DSP runtime library for v66 targets | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/hexagon-v66/unsigned</p></li><br></ul> |
| libSnpeHtpVxxSkel.so | library | Hexagon DSP runtime library for v68/69/73/75/79 targets | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/hexagon-v68/unsigned</p></li><br><li><p>$SNPE_ROOT/lib/hexagon-v69/unsigned</p></li><br><li><p>$SNPE_ROOT/lib/hexagon-v73/unsigned</p></li><br><li><p>$SNPE_ROOT/lib/hexagon-v75/unsigned</p></li><br><li><p>$SNPE_ROOT/lib/hexagon-v79/unsigned</p></li><br></ul> |

### Windows

| File | Type | Details | Location |
| --- | --- | --- | --- |
| snpe-net-run.exe | executable | Executes neural networks using SDK APIs | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br><li><p>$SNPE_ROOT/bin/aarch64-windows-msvc</p></li><br></ul> |
| snpe-onnx-to-dlc | script | Converts an ONNX model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-tensorflow-to-dlc | script | Converts a TensorFlow model to a DLC file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-dlc-quant | executable | Quantizes a DLC file using 8/16 bit quantization | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-dlc-graph-prepare | executable | Prepares (offline) a graph for HTP on the host | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-diagview | executable | Displays Neural Processing SDK timing output | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br><li><p>$SNPE_ROOT/bin/aarch64-windows-msvc</p></li><br></ul> |
| snpe-dlc-info | script | Prints DLC file information | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-dlc-viewer | script | Displays a DLC file as an HTML file | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-dlc-diff | script | Compares two different DLC files | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| snpe-udo-package-generator | executable | Generates UDO package | <ul class="simple"><br><li><p>$SNPE_ROOT/bin/x86_64-windows-msvc</p></li><br></ul> |
| envsetup.ps1 | script | Sets up environment variables needed to run SDK tools and binaries | <ul class="simple"><br><li><p>$SNPE_ROOT/bin</p></li><br></ul> |
| SNPE.dll | library | Qualcomm® Neural Processing SDK runtime for host and device development | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/aarch64-windows-msvc</p></li><br><li><p>$SNPE_ROOT/lib/arm64x-windows-msvc</p></li><br><li><p>$SNPE_ROOT/lib/x86_64-windows-msvc</p></li><br></ul> |
| SnpeHtpPrepare.dll | library | Library for offline graph preparation for HTP | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/aarch64-windows-msvc</p></li><br><li><p>$SNPE_ROOT/lib/arm64x-windows-msvc</p></li><br></ul> |
| libSnpeDspV66Skel.so | library | Hexagon DSP runtime library for v66 targets | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/hexagon-v66/unsigned</p></li><br></ul> |
| libSnpeHtpV68Skel.so | library | Hexagon DSP runtime library for v68 targets | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/hexagon-v68/unsigned</p></li><br></ul> |
| libSnpeHtpV73Skel.so | library | Hexagon DSP runtime library for v73 targets | <ul class="simple"><br><li><p>$SNPE_ROOT/lib/hexagon-v73/unsigned</p></li><br></ul> |

Last Published: Jun 04, 2026

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