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== Programming ==
Mobile NPU vendors typically provide their own [[application programming interface]] such as the Snapdragon Neural Processing Engine. An operating system or a higher-level library may provide a more generic interface such as TensorFlow Lite with LiteRT Next (
Consumer CPU-integrated NPUs are accessible through vendor-specific APIs. AMD (Ryzen AI), Intel (OpenVINO), Apple Silicon (CoreML){{efn|MLX builds atop the CPU and GPU parts, not the Apple Neural Engine (ANE) part of Apple Silicon chips. The relatively good performance is due to the use of a large, fast [[unified memory]] design.}} each have their own APIs, which can be built upon by a higher-level library.
GPUs generally use existing [[GPGPU]] pipelines such as CUDA and OpenCL adapted for lower precisions. Custom-built systems such as the Google TPU use private interfaces.
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