This product is no longer available
We no longer stock NVIDIA Jetson Nano Module, but here are current alternatives in NVIDIA Jetson Compute Modules.
NVIDIA Jetson Nano Module
Discontinued
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
