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Palit Pandora NVIDIA Jetson Orin NX Super 16GB AI Accelerator

Palit Pandora NVIDIA Jetson Orin NX Super 16GB AI Accelerator

SKU:VCPA-PAN-A002-16G

The Palit Pandora NVIDIA Jetson Orin NX Super is a compact AI accelerator module designed for edge computing and embedded AI applications. Featuring 16GB LPDDR5 memory, 1024-core Ampere GPU, and up to 157 TOPS performance, it delivers efficient AI inference for developers and ...
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BrandPalit
CategoryVideo/Graphics Cards
SKUVCPA-PAN-A002-16G
AvailabilityIn Stock
Palit Pandora NVIDIA Jetson Orin NX Super 16GB AI Accelerator$2,010.09
$2,010.09
Overview
  • The Palit Pandora NVIDIA Jetson Orin NX Super is a powerful AI accelerator module purpose-built for edge computing environments. It combines a capable 8-core Arm CPU with a 1024-core Ampere GPU to deliver high-performance AI inference without requiring cloud connectivity or expensive server infrastructure.

    With 157 TOPS of sparse AI performance and 78 TOPS dense performance, this module accelerates machine learning workloads efficiently at the network edge. The 16GB LPDDR5 memory and 102.4 GB/s bandwidth support demanding computer vision, natural language processing, and other AI-intensive tasks locally, reducing latency and improving responsiveness.

    Ideal for developers, integrators, and businesses deploying autonomous systems, smart sensors, or real-time AI analytics. The Jetson Orin NX Super provides enterprise-grade performance in a compact form factor suitable for robotics, manufacturing, surveillance, and logistics applications.
Specifications
ProcessorNVIDIA Jetson Orin NX 16GB SUPER
CPU Cores8-core Arm Cortex-A78AE v8.2 64-bit
CPU Cache2MB L2 + 4MB L3
GPU1024-core NVIDIA Ampere architecture
GPU Cores32 Tensor Cores
AI Performance (Sparse)157 TOPS
AI Performance (Dense)78 TOPS
System Memory16GB LPDDR5
Memory Bandwidth102.4 GB/s
Warranty24 months
Manufacturer Part NumberA002FV1P1
Key Features
NVIDIA Jetson Orin NX 16GB SUPER platform with 8-core Arm Cortex-A78AE CPU
1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
Up to 157 TOPS sparse / 78 TOPS dense AI performance
16GB LPDDR5 system memory with 102.4 GB/s bandwidth
Compact form factor optimised for edge computing deployments
Ideal For
Edge AI inference and real-time machine learning applications
Autonomous robotics and computer vision systems
Industrial IoT and smart factory automation
Embedded AI development and prototyping
Organisations deploying distributed AI at the edge
FAQs
What is the difference between sparse and dense AI performance?

Sparse performance (157 TOPS) measures throughput when calculations skip zero values, typical in certain neural networks. Dense performance (78 TOPS) measures throughput for standard matrix operations. Actual performance depends on your specific AI models and workloads.

Can the Jetson Orin NX Super run AI inference without internet connectivity?

Yes, the module is designed for edge computing and can run AI inference locally on the device without cloud connectivity, reducing latency and improving privacy.

What software frameworks does this module support?

The Jetson Orin NX Super supports NVIDIA CUDA, TensorRT, and popular AI frameworks including TensorFlow, PyTorch, and OpenCV. Refer to NVIDIA's Jetson documentation for full framework compatibility.

Is this suitable for industrial and manufacturing environments?

Yes, the Jetson Orin NX Super is commonly used in industrial IoT, factory automation, quality control vision systems, and predictive maintenance applications due to its reliable performance and edge computing capabilities.

What cooling solutions are available?

Specific cooling requirements depend on your deployment environment. Refer to the product datasheet and system integration guidelines for recommended thermal management approaches.

What is the warranty coverage?

The Palit Pandora NVIDIA Jetson Orin NX Super includes a 24-month manufacturer warranty covering defects in materials and workmanship.

Can multiple modules be connected for increased performance?

Scalability options depend on your system architecture and application. Refer to NVIDIA's Jetson documentation and integration guides for multi-module deployment strategies.

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