900-13701-0040-000 NVIDIA Jetson AGX Orin, 8x 2.2 GHz, 200 TOPS, 32 GB DDR5

The NVIDIA Jetson AGX Orin 32 GB module provides up to 200 TOPS of AI performance with configurable power between 15 W and 40 W. This gives you more than six times the performance of the Jetson AGX Xavier in the same compact form factor for robotics and other autonomous machine use cases.

High-performance GPU with advanced architecture - 1792-core GPU with NVIDIA Ampere architecture and 56 tensor cores - 2x NVDLA v2.0 - 8-core Cortex-A78AE v8.2 64-bit CPU - High speed memory: 32 GB 256-bit LPDDR5 - Large memory: 64 GB eMMC 5.1 - PVA v2.0

The NVIDIA® Jetson AGX Orin ™ 32GB module delivers up to 200 TOPS of AI performance with configurable power between 15W and 40W. This gives you more than six times the performance of Jetson AGX Xavier™ in the same compact form factor for robotics and other autonomous machine use cases.

Technical data - AI performance: 200 TOPS (Sp) |100 TOPS (De) - GPU: 1792-core NVIDIA Ampere GPU with 56 tensor cores - DL accelerator: 2x NVDLA v2 - Vision Accelerator: PVA v2 - CPU: 8-core NVIDIA Arm Cortex A78AE v8.2 64-bit CPU / 2 MB L2 + 4 MB L3 - Memory: 32 GB 256-bit LPDDR5 @3200 MHz 204.8 GB/s - Memory: 64 GB eMMC 5.1 - Video encoding: 1x 4K60 | 3x 4K30 | 6x 1080p60 | 12x 1080p30 (H.265) | H.264, AV1 - video decoding: 1x 8K30 | 2x 4K60 | 4x 4K30 | 9x 1080p60| 18x 1080p30 (H.265) | H.264, VP9, AV1 - Camera: 16 tracks MIPI CSI-2 (16 virtual channels) / D-PHY 2.1 40 Gbit/s / C-PHY 2.0 164 Gbit/s - PCI Express: 22 lanes PCIe Gen 4 / Up to 2 x8, 1 x4, 2 x1 - Ethernet: 1 Gbe RGMII | 4x 10Gbe XFI - connector: 699 pin connector - power: 15 to 40 W - dimensions (LxW): 100 x 87 mm

Application - autonomous vehicles - robots and drones - industrial automation and machine vision - education and research

Manufacturer Information & Software https://developer.nvidia.com/embedded/jetson-modules https://developer.nvidia.com/embedded/learn/getting-started-jetson https://developer.nvidia.com/embedded/jetpack https://developer.nvidia.com/embedded/downloads