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# Overview Qualcomm^®^ Linux AI stack allows developers to optimally deploy pre-trained, deep learning models on Qualcomm hardware accelerators, such as Neural Processing Unit (NPU), Graphic Processing Unit (GPU), and Central Processing Unit (CPU). Qualcomm AI software offering contains software development kits (SDKs), APIs, sample applications, development tools, and third-party frameworks support such as GStreamer and TFLite, to ease application development. **Top-level AI hardware and software blocks of the Qualcomm Linux AI stack** The key components of the Qualcomm Linux AI stack are: - **AI applications** - Sample applications based on GStreamer that can be used or customized as needed. - **GStreamer plugins** - Qualcomm Linux software offers GStreamer-based, machine learning plugins for accelerating AI inference using TFLite, Qualcomm^®^ Neural Processing Engine SDK, etc., along with GStreamer plugins for pre- and postprocessing. - **Qualcomm AI Stack** consists of two SDKs to accelerate AI workloads. The **Qualcomm Neural Processing Engine SDK** and **Qualcomm AI Engine Direct** provide tools, libraries, etc., to optimally accelerate AI models on multiple hardware accelerators. - Qualcomm SoCs offer three **hardware cores** for AI loads. - **Neural Processing Unit (NPU)** - Also referred to as Qualcomm® Hexagon™ Tensor Processor (HTP) or DSP/HMX, is suitable for executing AI workloads with low-power and high-performance. To get optimized performance, pre-trained models need be quantized to one of the supported precisions. - **Graphics Processing Unit (GPU)** - Qualcomm® Adreno™ GPU is suitable for executing AI workloads with medium-power, and medium-performance. AI workloads are accelerated with OpenCL kernels. The GPU can also be used to accelerate model pre/post processing. - **Central Processing Unit (CPU)** - AI inferencing on the CPU can be used to benchmark model accuracy/performance against other hardware accelerators. The CPU can also be used to run model pre/post processing. Last Published: Mar 27, 2025 [Next Topic Architecture](https://docs.qualcomm.com/bundle/publicresource/80-70018-15/topics/architecture.md)