NVIDIA 900-83489-0080-000 | Jetson TX2 4GB AI Compute Module, Pascal 256 CUDA Cores

Q: What is the difference between Jetson TX2 4GB and the standard TX2?
A: The TX2 4GB variant features 4GB LPDDR4 memory and 16GB eMMC storage (versus 8GB memory and 32GB storage on standard TX2), while maintaining the same GPU and CPU architecture. It delivers identical compute performance at a lower price point, making it ideal for cost-sensitive edge AI deployments.

Q: Does this module require a carrier board to operate?
A: Yes, the Jetson TX2 4GB is a System-on-Module (SOM) that requires a compatible carrier board to provide power, I/O connectivity, and physical interfaces. NVIDIA and third-party manufacturers offer various carrier boards designed for different applications and form factors.

Q: What AI frameworks and tools are supported?
A: The module is supported by NVIDIA JetPack SDK, which includes CUDA, cuDNN, TensorRT for inference acceleration, and support for popular frameworks including TensorFlow, PyTorch, Caffe, and MXNet. It also includes computer vision libraries like VisionWorks and OpenCV with GPU acceleration.

Q: Can this module handle multiple camera inputs simultaneously?
A: Yes, the TX2 4GB supports up to 6 camera inputs via MIPI CSI-2 interface with up to 12 lanes. The integrated ISP can process up to 1.4 Gpix/s, enabling multi-camera applications such as 360-degree vision systems, stereo depth sensing, and surveillance applications.

Q: What are typical applications for this module?
A: Common deployments include autonomous mobile robots, industrial inspection systems, smart city cameras with real-time analytics, agricultural drones, retail analytics, medical imaging devices, and AR/VR applications. The configurable power modes make it suitable for both battery-powered and continuously-powered edge devices.