Raspberry Pi 5 AI Kit vs NVIDIA Jetson Orin Nano: Best Edge AI Board?

The Big Question

If you’re building an edge-AI project — a vision pipeline, a smart sensor, a robotics prototype — two boards dominate the conversation: the Raspberry Pi 5 AI Kit (a Pi 5 plus a Hailo-8L NPU) and the NVIDIA Jetson Orin Nano. Both deliver on-device inference without a desktop GPU, but they come from opposite ends of the spectrum: the Pi kit is cheap and accessible; the Jetson brings real NVIDIA CUDA to the edge. Here’s how to choose.

Spec Comparison

Performance Comparison

On raw TOPS, the Jetson Orin Nano edges ahead — and more importantly, those TOPS come with the full NVIDIA CUDA stack: cuDNN, TensorRT, JetPack. If your model was trained on CUDA and you want to deploy it on the edge with minimal porting, the Jetson is the path of least resistance. It’s the board for serious robotics and computer-vision work.

The Pi 5 AI Kit delivers 13 TOPS via the Hailo-8L NPU — enough for real-time object detection and common vision models, and remarkably capable for the price. It won’t match the Jetson on the heaviest models or CUDA-specific pipelines, but for many edge-vision projects it’s more than enough, and the Hailo runtime is straightforward.

Software & Ecosystem

The Pi wins on community: the Raspberry Pi ecosystem is enormous, with endless tutorials, libraries, and accessories. The Jetson’s ecosystem is smaller and more pro-focused, but what it lacks in breadth it makes up in depth — NVIDIA’s documentation and ML tooling are best-in-class if you’re already in the CUDA world.

Value Comparison

The Pi 5 AI Kit is the clear value leader at $120 — it’s the cheapest credible way to do edge AI. The Jetson Orin Nano at $199+ is pricier, but you’re paying for CUDA and a more capable GPU. If your project genuinely needs CUDA, the Jetson’s premium is justified; if it doesn’t, the Pi kit is the smarter spend.

The Verdict

Tie — it depends on your stack. Choose the Raspberry Pi 5 AI Kit for budget builds, hobbyist edge vision, and any project that doesn’t strictly need CUDA — it’s the most accessible edge-AI platform available. Choose the NVIDIA Jetson Orin Nano for robotics, CUDA-native ML development, and projects where the NVIDIA software stack is a requirement. We scored the Pi kit 8.8 and the Jetson 8.5 — the Pi’s value and accessibility give it a slight overall edge, but the right pick is dictated by whether you need CUDA.

• Read our Raspberry Pi 5 AI Kit review →
• Read our NVIDIA Jetson Orin Nano review →