Which NVIDIA solution is best suited for deploying AI models in an embedded system for an autonomous vehicle project requiring real-time processing?

The NVIDIA Jetson AGX Xavier is highly suited for deploying AI models in embedded systems for autonomous vehicle projects due to its powerful computing capabilities and design tailored for real-time processing. It is equipped with a powerful GPU, CPU cores, and dedicated AI accelerators, which are specifically built to handle complex AI workloads, making it ideal for tasks such as object detection, path planning, and sensor fusion needed in autonomous vehicles.

This platform is designed to deliver high performance while operating within the power constraints typical of embedded applications, enabling efficient processing and decision-making crucial for safety-critical systems like those in autonomous vehicles. Furthermore, Jetson AGX Xavier supports a wide variety of deep learning frameworks and provides extensive development tools, facilitating the deployment of sophisticated AI models for real-time applications.

The other options mentioned, while valuable in different contexts, do not provide the same combination of embedded performance, real-time capabilities, and support for AI workloads required for this specific application scenario.