Choosing the Right YOLO Inference Strategy for NVIDIA Jetson: A Practical Comparison
When deploying real-time object detection with Ultralytics YOLO on NVIDIA Jetson devices like the Orin NX, you quickly realize there's more than one way to do it. Each approach has trade-offs in terms of performance, complexity, and flexibility. This essay compares the most practical options for YOLO inference, especially in the context of multi-camera systems where performance and ease of maintenance are critical. ☕️ Introducing the CCTV wonder concept: "Housewife Box" Not every end-user is a mathematician like Lobachevsky — in fact, most users just want a box they can turn on and forget. This is the heart of the Housewife Box philosophy: No configuration rituals. No deep learning know-how required. Just plug it in, get detections, and watch streams with boxes overlaid — in VLC, on a phone, or on a laptop. With that mindset, let's compare options from the perspective of building a product that fits this vision.

When deploying real-time object detection with Ultralytics YOLO on NVIDIA Jetson devices like the Orin NX, you quickly realize there's more than one way to do it. Each approach has trade-offs in terms of performance, complexity, and flexibility. This essay compares the most practical options for YOLO inference, especially in the context of multi-camera systems where performance and ease of maintenance are critical.
☕️ Introducing the CCTV wonder concept: "Housewife Box"
Not every end-user is a mathematician like Lobachevsky — in fact, most users just want a box they can turn on and forget. This is the heart of the Housewife Box philosophy:
- No configuration rituals.
- No deep learning know-how required.
- Just plug it in, get detections, and watch streams with boxes overlaid — in VLC, on a phone, or on a laptop.
With that mindset, let's compare options from the perspective of building a product that fits this vision.