Development Flow

• Support for mainstream deep learning frameworks and models, including CNNs and select vision transformer architectures
• Quantization tools to balance model accuracy, performance, and power consumption
• Model compilation and runtime APIs that enable efficient deployment of custom AI inference workloads
• NPU IP optimized for deterministic, low-latency, and scalable AI inference on embedded platforms

Deploy AI inference on AMD evaluation boards using Vitis AI software, enabling rapid prototyping and system bring‑up for embedded applications such as automotive, machine vision, industrial, and robotics.