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NVIDIA

NVIDIA 900-13701-0040-000 | Jetson AGX Orin AI Module, 32GB LPDDR5, 200 TOPS, 8-Core Arm CPU

SKU:900-13701-0040-000

Stock Status: Enquire

$3,605.25 inc. GST
$3,277.50 ex. GST
Sale Sold out
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Description

The NVIDIA Jetson AGX Orin 32GB is a compact system-on-module designed for edge AI and autonomous machine applications. Delivering up to 200 TOPS of AI performance with configurable power from 15W to 40W, this module features an 8-core Arm Cortex-A78AE CPU, 1792-core Ampere GPU with 56 Tensor cores, and 32GB LPDDR5 memory. Ideal for robotics, industrial automation, vision AI, and complex multi-sensor fusion deployments requiring high-performance inference at the edge.

Features

NVIDIA Ampere GPU architecture with 1792 CUDA cores and 56 third-generation Tensor cores
- 8-core Arm Cortex-A78AE CPU with enhanced AI and compute capabilities
- Up to 200 TOPS INT8 AI inference performance
- 32GB LPDDR5 memory with 204 GB/s bandwidth for high-speed data processing
- Dual NVDLA v2.0 deep learning accelerators for concurrent AI pipeline execution
- Programmable Vision Accelerator (PVA v2.0) for computer vision workloads
- Multi-stream video encode and decode up to 8K resolution
- Support for multiple concurrent AI application pipelines
- Compatible with NVIDIA AI software stack including TensorRT, CUDA, and cuDNN
- High-speed I/O interfaces including PCIe Gen 4, USB 3.2, and MGBE Ethernet
- Compact 100mm x 87mm form factor for space-constrained edge deployments
- Power-configurable design (15W to 40W) for flexible thermal management
- Built on Samsung 8nm process for performance and efficiency balance
- Support for JetPack SDK, Isaac ROS, DeepStream SDK, and domain-specific frameworks

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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Technical Specifications

FAQs

Technical Specifications

AI Performance: Up to 200 TOPS (INT8)
- GPU: 1792-core NVIDIA Ampere architecture with 56 Tensor cores
- CPU: 8-core Arm Cortex-A78AE v8.2 64-bit, 2MB L2 + 4MB L3 cache
- Memory: 32GB 256-bit LPDDR5, 204 GB/s bandwidth
- Storage: 64GB eMMC 5.1
- Deep Learning Accelerators: 2x NVDLA v2.0
- Vision Accelerator: PVA v2.0
- Video Encode: 2x 4K60, 4x 4K30, 8x 1080p60, 16x 1080p30 (H.265)
- Video Decode: 1x 8K30, 3x 4K60, 7x 4K30, 11x 1080p60, 22x 1080p30 (H.265)
- Module Power: 15W - 40W configurable
- Input Voltage: 5V, 7V-20V
- Form Factor: 100mm x 87mm SOM
- Process Technology: Samsung 8nm
- Operating Temperature: Industrial-grade variants available

FAQs

Q: What applications is the Jetson AGX Orin 32GB module best suited for?
A: The module is designed for edge AI applications including autonomous mobile robots, industrial inspection systems, vision AI pipelines, natural language processing, 3D perception, multi-sensor fusion, and real-time inference workloads requiring up to 200 TOPS of performance.

Q: What is the difference between the 32GB and 64GB Jetson AGX Orin modules?
A: The 32GB module features an 8-core CPU, 1792 CUDA cores, 56 Tensor cores, and delivers up to 200 TOPS with 15-40W power range. The 64GB variant has a 12-core CPU, 2048 CUDA cores, 64 Tensor cores, and delivers up to 275 TOPS with 15-60W power range.

Q: Does this module require a carrier board to function?
A: Yes, the Jetson AGX Orin module is a system-on-module (SOM) that requires a compatible carrier board to provide I/O connectivity, power regulation, and peripheral interfaces. NVIDIA and ecosystem partners offer reference carrier boards and custom designs.

Q: What software frameworks and tools are supported?
A: The module runs NVIDIA JetPack SDK with support for TensorRT, cuDNN, CUDA, Isaac for robotics, DeepStream for vision AI, Riva for conversational AI, TAO Toolkit for model fine-tuning, and Omniverse Replicator for synthetic data generation.

Q: Can power consumption be adjusted based on application requirements?
A: Yes, the module supports configurable power modes ranging from 15W for energy-efficient edge deployment up to 40W for maximum AI performance, allowing optimization for thermal constraints and performance needs.

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