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| Product Overview |
|---|
The NVIDIA Jetson TX2 8GB Development Module combines a powerful GPU and CPU architecture to handle AI workloads at the edge. It works well in embedded systems requiring efficient processing for applications like robotics and intelligent video, offering a balance of performance and power efficiency in a compact form factor. |
| General Information | |
|---|---|
| Brand | Nvidia |
| Part Number | 135-0807-003-R2 |
| Technical Information | |
|---|---|
| Chipset | Dual-core NVIDIA Denver 2 + Quad-core ARM Cortex‑A57, up to 2.0 GHz |
| Compatible Processors | NVIDIA Tegra X2 (Jetson TX2), NVIDIA Denver 2 (dual-core), ARM Cortex-A57 (quad-core) |
| Board Socket Type | 400-pin board-to-board mezzanine connector |
| Memory Slots | Onboard 8GB LPDDR4 (no user-upgradeable memory slots) |
| Memory Support | 8 GB, 128-bit, 1866 MHz, 59.7 GB/s |
| Storage Interfaces | PCIe Gen2 (var config), 3× USB‑3, USB‑2, 1× Gigabit Ethernet (Dev Kit), MIPI‑CSI, DisplayPort/HDMI, I²C, SPI, UART, I²S, CAN, GPIO |
| Expansion Slots | PCIe Gen2 x4 (via carrier board), M.2 (carrier/DevKit), GPIO, I2C, SPI, UART |
| USB Port | USB 3.0, USB 2.0 (OTG) (ports exposed via carrier board) |
| Physical Characteristics | |
|---|---|
| Form Factor | System-on-Module (SOM) / Jetson TX2 module (module form factor, ~50 x 87 mm) |
| Dimensions | 4.7 x 87 x 50 mm |
| Weight | 4.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Product Description |
|---|
The NVIDIA Jetson TX2 8GB Development Module is designed to deliver AI computing at the edge. It is commonly found in robotics, drones, and intelligent video analytics systems where efficient AI processing is needed without relying on cloud services. Built for developers and researchers, this module provides the computational power necessary for embedded AI, machine learning, and computer vision applications in compact, power-constrained environments. Key Features
This module is typically deployed in industrial automation, smart cities, and autonomous machines where real-time AI inference is crucial. Its compact size and efficient design allow it to be integrated into various devices that require advanced computing without bulky hardware. |