NVIDIA Jetson Nano Module
The NVIDIA Jetson Nano module delivers up to 472 GFLOPS of GPU-accelerated computing in a compact, low-power form factor. Powered by the NVIDIA Maxwell GPU with 128 CUDA cores and a quad-core ARM Cortex-A57 CPU, it runs AI frameworks including TensorFlow, PyTorch, and MXNet natively.
The module includes 4 GB LPDDR4 RAM and 16 GB eMMC storage, and connects to carrier boards via a 260-pin edge connector. It is supported by NVIDIA JetPack SDK, which includes Linux OS, CUDA, cuDNN, and TensorRT for deep learning, computer vision, and multimedia processing.
Key Features
- 128 NVIDIA CUDA Cores – Maxwell GPU architecture, 0.5 TFLOPS (FP16)
- Quad-Core ARM Cortex-A57 – 64-bit CPU
- 4 GB LPDDR4 RAM – 25.6 GB/s bandwidth
- 16 GB eMMC 5.1 – Onboard flash storage
- 4K Video – Hardware encode and decode (HEVC)
- 12-Lane MIPI CSI-2 – Support for multiple cameras
- Low Power – As little as 5 W
Specifications
- GPU: NVIDIA Maxwell, 128 CUDA cores
- CPU: Quad-core ARM Cortex-A57
- Memory: 4 GB 64-bit LPDDR4 @ 1600 MHz
- Storage: 16 GB eMMC 5.1
- Video Encode: 250 MP/s – 1× 4K @ 30, 2× 1080p @ 60, 4× 1080p @ 30 (HEVC)
- Video Decode: 500 MP/s – 1× 4K @ 60, 2× 4K @ 30, 4× 1080p @ 60, 8× 1080p @ 30 (HEVC)
- Camera: 12 lanes MIPI CSI-2 (3×4 or 4×2), D-PHY 1.1, 18 Gbps
- Display: HDMI 2.0 or DP 1.2, eDP 1.4, DSI (1×2), 2 simultaneous
- Connectivity: 1× PCIe (x1/x2/x4), 1× USB 3.0, 3× USB 2.0
- I/O: 3× UART, 2× SPI, 2× I2S, 4× I2C, GPIOs
- Dimensions: 69.6 × 45 mm
- Connector: 260-pin edge connector
Ideal For
- AI and deep learning at the edge
- Smart cameras and video analytics
- Robotics and autonomous machines
- AIoT gateways and embedded AI products
Package Contents
- 1× NVIDIA Jetson Nano module
Resources
Product Information
Product Information
Shipping & Returns
Shipping & Returns
Description
The NVIDIA Jetson Nano module delivers up to 472 GFLOPS of GPU-accelerated computing in a compact, low-power form factor. Powered by the NVIDIA Maxwell GPU with 128 CUDA cores and a quad-core ARM Cortex-A57 CPU, it runs AI frameworks including TensorFlow, PyTorch, and MXNet natively.
The module includes 4 GB LPDDR4 RAM and 16 GB eMMC storage, and connects to carrier boards via a 260-pin edge connector. It is supported by NVIDIA JetPack SDK, which includes Linux OS, CUDA, cuDNN, and TensorRT for deep learning, computer vision, and multimedia processing.
Key Features
- 128 NVIDIA CUDA Cores – Maxwell GPU architecture, 0.5 TFLOPS (FP16)
- Quad-Core ARM Cortex-A57 – 64-bit CPU
- 4 GB LPDDR4 RAM – 25.6 GB/s bandwidth
- 16 GB eMMC 5.1 – Onboard flash storage
- 4K Video – Hardware encode and decode (HEVC)
- 12-Lane MIPI CSI-2 – Support for multiple cameras
- Low Power – As little as 5 W
Specifications
- GPU: NVIDIA Maxwell, 128 CUDA cores
- CPU: Quad-core ARM Cortex-A57
- Memory: 4 GB 64-bit LPDDR4 @ 1600 MHz
- Storage: 16 GB eMMC 5.1
- Video Encode: 250 MP/s – 1× 4K @ 30, 2× 1080p @ 60, 4× 1080p @ 30 (HEVC)
- Video Decode: 500 MP/s – 1× 4K @ 60, 2× 4K @ 30, 4× 1080p @ 60, 8× 1080p @ 30 (HEVC)
- Camera: 12 lanes MIPI CSI-2 (3×4 or 4×2), D-PHY 1.1, 18 Gbps
- Display: HDMI 2.0 or DP 1.2, eDP 1.4, DSI (1×2), 2 simultaneous
- Connectivity: 1× PCIe (x1/x2/x4), 1× USB 3.0, 3× USB 2.0
- I/O: 3× UART, 2× SPI, 2× I2S, 4× I2C, GPIOs
- Dimensions: 69.6 × 45 mm
- Connector: 260-pin edge connector
Ideal For
- AI and deep learning at the edge
- Smart cameras and video analytics
- Robotics and autonomous machines
- AIoT gateways and embedded AI products
Package Contents
- 1× NVIDIA Jetson Nano module
