NVIDIA

Jetson AGX Xavier 64GB

Jetson AGX Xavier series modules enable new levels of compute density, power efficiency, and AI inferencing capabilities at the edge. These modules have 10X the energy efficiency and 20X the performance of Jetson TX2.
Jetson AGX Xavier 64GB
General Description

The Jetson AGX Xavier 64GB module makes AI-powered autonomous machines possible, running in as little as 10W and delivering up to 32 TOPs. Customers can leverage the 64GB memory to store multiple AI models, run complex applications, and enhance their real time pipelines. As part of the world’s leading AI computing platform, it benefits from the rich set of NVIDIA AI tools and workflows, enabling developers to train and deploy neural networks quickly. Jetson AGX Xavier 64GB is supported by NVIDIA JetPack SDK, which can help you save development effort and expense.

*Available in Jan 2022
Contact Us to Order Now
 
Technical Specifications
 
GPU NVIDIA Volta™ architecture with 512 NVIDIA® CUDA® cores and 64 Tensor cores
22 TOPS (INT8)
CPU 8-core NVIDIA Carmel Arm®v8.2 64-bit CPU
8MB L2 + 4MB L3
DL Accelerator 2x NVDLA
10 TOPS (INT8)
Vision Accelerator 2x PVA
Memory 64GB 256-bit LPDDR4x
136.5GB/s
Storage 32GB eMMC 5.1
CSI Camera Up to 6 cameras (36 via virtual channels)
16 lanes MIPI CSI-2
D-PHY 1.2 (up to 40Gbps)
C-PHY 1.1 (up to 62Gbps)
Video Encode 4x 4K60 | 8x 4K30 | 16x 1080p60 | 32x 1080p30 (H.265)
4x 4K60 | 8x 4K30 | 14x 1080p60 | 30x 1080p30 (H.264)
Video Decode 2x 8K30 | 6x 4K60 | 12x 4K30 | 26x 1080p60 | 52x 1080p30 (H.265)
4x 4K60 | 8x 4K30 | 16x 1080p60 | 32x 1080p30 (H.264)
UPHY 8x PCIe Gen4
3x USB 3.1
Single Lane UFS
Networking 10/100/1000 BASE-T Ethernet
Display Three multi-mode DP 1.2a/e DP 1.4/HDMI 2.0 a/b
Other I/O USB 2.0
UART, SPI, CAN, I2C, I2S, DMIC & DSPK, GPIOs
Power 10W | 15W | 30W
Mechanical 100mm x 87mm
699 pin Molex Mirror Mezz Connector
Integrated Thermal Transfer Plate
 
Data Sheet Download
Document Name
Download
NVIDIA JETSON AGX XAVIER 64GB
NVIDIA JETSON AGX XAVIER 64GB
*NVIDIA Authorized Distributor
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