Nvidia Jetson Nano GPIO Pinout

Nvidia Jetson Nano GPIO Pinout guide

Overview

The Nvidia Jetson Nano is a powerful developer board from Nvidia, ideal for robotics, artificial intelligence, and edge computing. It features a quad-core ARM Cortex-A57 CPU, 128-core Maxwell GPU, and 4 GB LPDDR4 RAM.

Pinout Table

Pin Number Name Function I/O Voltage Level Notes
1 3.3V 3.3V Power - 3.3V
2 5V 5V Power - 5V
3 GPIO2 GPIO I/O 3.3V TTL
4 5V 5V Power - 5V
5 GPIO3 GPIO I/O 3.3V TTL
6 GPIO4 GPIO I/O 3.3V TTL
7 GND Ground - -
8 GPIO5 GPIO I/O 3.3V TTL
9 GPIO6 GPIO I/O 3.3V TTL
10 GPIO7 GPIO I/O 3.3V TTL
11 GPIO8 GPIO I/O 3.3V TTL
12 GPIO9 GPIO I/O 3.3V TTL
13 GND Ground - -
14 GPIO10 GPIO I/O 3.3V TTL
15 GPIO11 GPIO I/O 3.3V TTL
16 GPIO12 GPIO I/O 3.3V TTL
17 GPIO13 GPIO I/O 3.3V TTL
18 GPIO14 GPIO I/O 3.3V TTL
19 GPIO15 GPIO I/O 3.3V TTL
20 GPIO16 GPIO I/O 3.3V TTL
21 GPIO17 GPIO I/O 3.3V TTL
22 GPIO18 GPIO I/O 3.3V TTL
23 GPIO19 GPIO I/O 3.3V TTL
24 GPIO20 GPIO I/O 3.3V TTL
25 GND Ground - -
26 1.8V 1.8V Power - 1.8V
27 SDA I2C Data I/O 3.3V TTL
28 SCL I2C Clock I/O 3.3V TTL
29 GPIO22 GPIO I/O 3.3V TTL
30 GND Ground - -
31 GPIO23 GPIO I/O 3.3V TTL
32 GPIO24 GPIO I/O 3.3V TTL
33 GPIO25 GPIO I/O 3.3V TTL
34 GND Ground - -
35 GPIO26 GPIO I/O 3.3V TTL
36 GPIO27 GPIO I/O 3.3V TTL
37 GPIO28 GPIO I/O 3.3V TTL
38 GPIO29 GPIO I/O 3.3V TTL
39 GND Ground - -
40 GPIO21 GPIO I/O 3.3V TTL

Pinout Diagram

 2  4  6  8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
-----------------------------------------------------------
 1  3  5  7  9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39

Key Features

  • Powerful computing with a quad-core ARM Cortex-A57 CPU.
  • 128-core Maxwell GPU for AI and graphical tasks.
  • 4 GB LPDDR4 RAM ensures smooth multitasking.
  • Connectivity options including GPIO, I2C, I2S, SPI, and UART.
  • Supports popular AI frameworks like TensorFlow, PyTorch, and Caffe.
  • Perfect for edge computing, robotics, and AI projects.
  • MicroSD slot for storage expandability.

Usage Scenarios

The Nvidia Jetson Nano is perfect for:

  • Robotics projects requiring AI capabilities.
  • Edge computing tasks where high processing power is necessary.
  • Developing and deploying machine learning models on-device.
  • AI-based camera solutions for security or recognition.
  • Multimedia applications requiring GPU acceleration.

Safety Precautions

  • Ensure you use an adequate power supply.
  • Handle with care, considering ESD precautions.
  • Disconnect from power when making hardware changes.
  • Avoid short circuits and double-check pin connections.
  • Keep the board in a cool, dry place for optimal performance.

External Resources

© 2023, Pinout.ai. All rights reserved.