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NVIDIA Jetson Xavier NX 8GB 16GB eMMC Linux AI IoT Development Board

Description: Jetson Xavier NX Brings Supercomputer Performance To The Edge In A Small Form Factor SOM NVIDIA Jetson Xavier NX brings supercomputer performance to the edge in a small form factor system-on-module (SOM). Up to 21 TOPS of accelerated computing delivers the horsepower to run modern neural networks in parallel and process data from multiple high-resolution sensors—a requirement for full AI systems. Jetson Xavier NX is production-ready and supports all popular AI frameworks. ☑ Integrates 16 GB eMMC storage ☑ Industrial grade, more stable ☑ As powerful as Xavier, as small as Nano Compact, Powerful Performance At The Edge SIZE:XAVIER PERFORMANCE. NANO SIZE. At 70 mm x 45 mm, Jetson Xavier NX packs the power of the NVIDIA Xavier SoC into a module the size of a Jetson Nano. This compact module combines exceptional performance and power advantage with a rich set of IOs—from high-speed CSI and PCIe to low-speed I2Cs and GPIOs. Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capability to all your embedded AI and edge systems. PERFORMANCE:POWERFUL 21 TOPS AI PERFORMANCE Jetson Xavier NX delivers up to 21 TOPS, making it ideal for high-performance compute and AI in embedded and edge systems. You get the performance of 384 NVIDIA CUDA Cores, 48 Tensor Cores, 6 Carmel ARM CPUs, and two NVIDIA Deep Learning Accelerators (NVDLA) engines. Combined with over 51GB/s of memory bandwidth, video encoded, and decode, these features make Jetson Xavier NX the platform of choice to run multiple modern neural networks in parallel and process high-resolution data from multiple sensors simultaneously. POWER:INCREDIBLE POWER EFFICIENCY Jetson Xavier NX supports multiple power modes, including low-power modes for battery-operated systems, and delivers up to 14 TOPs for AI applications in as little as 10 W. This leaves more of your power budget for sensors and peripherals, while still letting you use the entire NVIDIA software stack. You now have the performance to run all modern AI networks and frameworks with accelerated libraries for deep learning, computer vision, computer graphics, multimedia, and more. Ideal For Critical Embedded Applications Jetson Xavier NX is perfect for high-performance AI systems like commercial robots, medical instruments, smart cameras, high-resolution sensors, automated optical inspection, smart factories, and other AIoT embedded systems. Specifications RAM OPTION 8GB 16GB AI PERFORMANCE 21 TOPS GPU 384-core NVIDIA Volta GPU with 48 Tensor Cores CPU 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3 MEMORY 8 GB128-bit LPDDR4x 59.7GB/s 16 GB128-bit LPDDR4x 59.7GB/s STORAGE 16 GB eMMC 5.1 POWER 10W | 15W | 20W PCIE 1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4), total 144 GT/s1 CSI CAMERA Up to 6 cameras (36 via virtual channels) 12 lanes (3x4 or 6x2) MIPI CSI-2 D-PHY 1.2 (up to 30 Gbps) VIDEO ENCODE 2x 4Kp30 | 6x 1080p60 | 14x 1080p30 (H.265 & H.264) VIDEO DECODE 2x 4Kp60 | 4x 4Kp30 | 12x 1080p60 | 32x 1080p30 (H.265) 2x 4Kp30 | 6x 1080p60 | 16x 1080p30 (H.264) DISPLAY 2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0 DL ACCELERATOR 2x NVDLA Engines VISION ACCELERATOR 7-Way VLIW Vision Processor NETWORKING 10/100/1000 BASE-T Ethernet MECHANICAL 69.6 mm x 45 mm 260-pin SO-DIMM connector

Price: 793.86 USD

Location: ShenZhen

End Time: 2024-09-24T10:26:52.000Z

Shipping Cost: 2.99 USD

Product Images

NVIDIA Jetson Xavier NX 8GB 16GB eMMC Linux AI IoT Development BoardNVIDIA Jetson Xavier NX 8GB 16GB eMMC Linux AI IoT Development BoardNVIDIA Jetson Xavier NX 8GB 16GB eMMC Linux AI IoT Development Board

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money back or replacement (buyer's choice)

Brand: Unbranded

MPN: 1

Available Variations

Color: 8GB

Price: 793.86 USD

Available Quantity: 5

Quantity Sold: 0

Color: 16GB

Price: 1031.96 USD

Available Quantity: 5

Quantity Sold: 0

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