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8GB 128 Bit LPDDR4 Jetson NX Dev Kit Module Xavier NX GPU 900 83668 0000 000

Categories Nvidia Jetson Xavier NX
Brand Name: NVIDIA
Model Number: (900-83668-0000-000)
Place of Origin: USA
MOQ: 1pcs
Supply Ability: 1000pcs
Delivery Time: 15-30 work days
Price: USD480-USD500\PCS
NAME: 8GB 128Bit LPDDR4 Jetson NX Dev Kit Module Xavier NX GPU
Keyword: 8GB 128Bit LPDDR4 Jetson NX Dev Kit Module Xavier NX GPU
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 GB 128-bit LPDDR4x 59.7GB/s
Storage: 16 GB eMMC 5.1
Power: 10W | 15W | 20W
Mechanical: 69.6mm x 45mm 260-pin SO-DIMM connector
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8GB 128 Bit LPDDR4 Jetson NX Dev Kit Module Xavier NX GPU 900 83668 0000 000

8GB 128Bit LPDDR4 Jetson NX Dev Kit Module Xavier NX GPU


NVIDIA Jetson Xavier NX Module


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.

Xavier Performance. Nano Size.

At 70mm x 45mm, 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.

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 59.7GB/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.



NVIDIA Jetson Xavier NX 8G module

AI Performance21 TOPS
GPU384-core NVIDIA Volta™ GPU with 48 Tensor Cores
CPU6-core NVIDIA Carmel ARM® v8.2 64-bit CPU
6MB L2 + 4MB L3
Memory8 GB 128-bit LPDDR4x
59.7GB/s
Storage16 GB eMMC 5.1
Power10W | 15W | 20W
PCIe1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4), total 144 GT/s*
CSI CameraUp to 6 cameras (24 via virtual channels)
14 lanes (3x4 or 6x2 or 3x4 + 1x2 or 5x2 + 1x4) MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)
Video Encode2x 4K60 | 4x 4K30 | 10x 1080p60 | 22x 1080p30 (H.265)
2x 4K60 | 4x 4K30 | 10x 1080p60 | 20x 1080p30 (H.264)
Video Decode2x 8K30 | 6x 4K60 | 12x 4K30 | 22x 1080p60 | 44x 1080p30 (H.265)
2x 4K60 | 6x 4K30 | 10x 1080p60 | 22x 1080p30 (H.264)
Display2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
DL Accelerator2x NVDLA
Vision Accelerator2x PVA
Networking10/100/1000 BASE-T Ethernet
Mechanical69.6mm x 45mm
260-pin SO-DIMM connector

* Please refer to the Software Features section of the latest NVIDIA Jetson Linux Developer Guide for a list of supported features


Compare Modules

NVIDIA Jetson Xavier NX 16GBNVIDIA Jetson Xavier NX 8GB
AI Performance21 TOPS
GPU384-core NVIDIA Volta™ GPU with 48 Tensor Cores
CPU
6-core NVIDIA Carmel ARM®v8.2 64-bit CPU
6MB L2 + 4MB L3

Memory
16 GB 128-bit LPDDR4x
59.7GB/s

8 GB 128-bit LPDDR4x
59.7GB/s
Storage16 GB eMMC 5.1
Power10 W | 15 W | 20 W
PCIe1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4), total 144 GT/s*
CSI Camera
Up to 6 cameras (24 via virtual channels)
14 lanes (3x4 or 6x2) MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)

Video Encode
2x 4K60 | 4x 4K30 | 10x 1080p60 | 22x 1080p30 (H.265)
2x 4K60 | 4x 4K30 | 10x 1080p60 | 20x 1080p30 (H.264)

Video Decode
2x 8K30 | 6x 4K60 | 12x 4K30 | 22x 1080p60 | 44x 1080p30 (H.265)
2x 4K60 | 6x 4K30 | 10x 1080p60 | 22x 1080p30 (H.264)

Display2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
DL Accelerator2x NVDLA Engines
Vision Accelerator7-Way VLIW Vision Processor
Networking10/100/1000 BASE-T Ethernet
Mechanical
69.6 mm x 45 mm
260-pin SO-DIMM connector



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