With its integrated system-on-chip (SoC), the Jetson Nano can run multiple neural networks in parallel. It supports popular AI frameworks such as TensorFlow, PyTorch, Caffe/Caffe2, Keras, and MXNet. This enables powerful AI functions like image classification, object detection, segmentation, and speech processing—ideal for robotics, smart devices, automation systems, and advanced AI projects.
Features
- Supports multiple AI frameworks and neural networks in parallel
- Capable of real-time image and video processing
- Includes camera support and multiple display output options
- Various peripheral connectivity options: PCIe, USB, SPI, I2C, I2S, GPIO
- Low power consumption with high performance for edge AI projects
- Suitable for robotics, autonomous vehicles, and smart surveillance systems
- Supports integration with sensors, actuators, and external hardware
Specifications
- GPU: 128-core NVIDIA Maxwell GPU
- CPU: Quad-core ARM A57
- Memory: 4 GB 64-bit LPDDR4
- Storage: 16 GB eMMC 5.1 flash
- Video Encoder: 4K @ 30 fps (H.264/H.265)
- Video Decoder: 4K @ 60 fps (H.264/H.265)
- Camera Interface: 12 lanes MIPI CSI-2 (1.5Gbps)
- Connectivity: Gigabit Ethernet
- Display Options: HDMI 2.0, DP 1.2, eDP 1.4, DSI (1x2)
- Peripheral Connectivity: PCIe, USB 3.0, USB 2.0, SPI, I2C, I2S, GPIO
- Dimensions: 100 × 80 × 29 mm
Usage Notes
This developer kit is ideal for learning AI concepts, experimenting with machine learning models, and building smart embedded projects. It supports hardware-accelerated deep learning and can run multiple neural networks simultaneously. Recommended for users interested in computer vision, autonomous robotics, image classification, and real-time data processing.
With its integrated system-on-chip (SoC), the Jetson Nano can run multiple neural networks in parallel. It supports popular AI frameworks such as TensorFlow, PyTorch, Caffe/Caffe2, Keras, and MXNet. This enables powerful AI functions like image classification, object detection, segmentation, and speech processing—ideal for robotics, smart devices, automation systems, and advanced AI projects.
Features
- Supports multiple AI frameworks and neural networks in parallel
- Capable of real-time image and video processing
- Includes camera support and multiple display output options
- Various peripheral connectivity options: PCIe, USB, SPI, I2C, I2S, GPIO
- Low power consumption with high performance for edge AI projects
- Suitable for robotics, autonomous vehicles, and smart surveillance systems
- Supports integration with sensors, actuators, and external hardware
Specifications
- GPU: 128-core NVIDIA Maxwell GPU
- CPU: Quad-core ARM A57
- Memory: 4 GB 64-bit LPDDR4
- Storage: 16 GB eMMC 5.1 flash
- Video Encoder: 4K @ 30 fps (H.264/H.265)
- Video Decoder: 4K @ 60 fps (H.264/H.265)
- Camera Interface: 12 lanes MIPI CSI-2 (1.5Gbps)
- Connectivity: Gigabit Ethernet
- Display Options: HDMI 2.0, DP 1.2, eDP 1.4, DSI (1x2)
- Peripheral Connectivity: PCIe, USB 3.0, USB 2.0, SPI, I2C, I2S, GPIO
- Dimensions: 100 × 80 × 29 mm
Usage Notes
This developer kit is ideal for learning AI concepts, experimenting with machine learning models, and building smart embedded projects. It supports hardware-accelerated deep learning and can run multiple neural networks simultaneously. Recommended for users interested in computer vision, autonomous robotics, image classification, and real-time data processing.