AI Deployment on NVIDIA Jetson (Nano, Orin)
NVIDIA Jetson — best AI edge platforms for computer vision, robotics, industrial AI. JetPack SDK provides complete stack: CUDA, TensorRT, DeepStream, Isaac. We deploy and optimize AI solutions for specific Jetson models.
Jetson Model Lineup (Current)
| Model | AI Performance | RAM | Use Case |
|---|---|---|---|
| Orin Nano 4GB | 20 TOPS | 4 GB | Basic edge AI tasks |
| Orin Nano 8GB | 40 TOPS | 8 GB | Computer vision, ROS |
| Orin NX 8GB | 70 TOPS | 8 GB | Multi-camera, inference server |
| Orin NX 16GB | 100 TOPS | 16 GB | Complex CV, LLM inference |
| Orin AGX | 275 TOPS | 64 GB | Autonomous vehicles, robots |
Optimization via TensorRT
TensorRT compiles ONNX/PyTorch models for specific Jetson GPU:
import tensorrt as trt
# or via trtexec:
# trtexec --onnx=model.onnx --saveEngine=model.trt --fp16
3–10× acceleration vs. PyTorch on same hardware. FP16 default, INT8 for maximum performance.
DeepStream for Video Analytics
NVIDIA DeepStream SDK — optimized pipeline for multi-camera analytics. GStreamer-based. Typical Orin AGX performance: 30+ Full HD cameras with YOLOv8 detection.
ROS2 + Jetson
Robotics: ROS2 Humble natively supported on JetPack 5/6. Isaac ROS — NVIDIA optimized ROS2 packages for computer vision.