Embedded Solutions NVIDIA RTX PRO Embedded GPU Solutions
Powering the next era of AI.
Overview AI, Graphics, and Compute for Specialized Systems
From ultrasound devices to advanced digital displays and robotics, NVIDIA RTX PRO™-powered embedded GPU solutions provide excellent performance and power efficiency while meeting the highest quality and reliability standards. No matter the industry, application, or deployment environment, embedded GPU solutions accelerated by NVIDIA RTX PRO are designed to deliver graphics, compute, deep learning, and AI capabilities to a wide variety of systems.
Benefits
Key Benefits of NVIDIA RTX PRO Embedded GPU Solutions
NVIDIA RTX PRO embedded GPUs combine exceptional performance with power efficiency, delivering AI and graphics computing wherever your applications demand it.
Performance and Efficiency
RTX PRO embedded GPUs scale from 35W to 150W, delivering workstation-class NVIDIA CUDA™, Tensor, and RT Core performance into compact form factors–without compromising on size, weight, or thermal constraints. Built on the NVIDIA Blackwell architecture, they deliver major gains in compute throughput, ray tracing, and memory bandwidth for real-time AI inference, computer vision, and advanced
Ruggedization and Form Factors
RTX PRO embedded GPUs are designed for high‑performance computing that can survive vibration, temperature extremes, and space‑constrained environments in defense, aerospace, and industrial systems. These designs allow you to place compute very close to sensors (cameras, radar, EO/IR, medical probes), reducing data‑movement latency and enabling on‑device processing.
Long Lifecycle and Enterprise Reliability
RTX PRO embedded GPUs are backed by long-life availability commitments—keeping hardware consistent across multi-year deployments. They’re purpose-built for applications like medical imaging, industrial automation, and commercial gaming systems, where supply stability and platform continuity are non-negotiable.
Software Ecosystem and Manageability
RTX PRO embedded GPUs integrate into the broader NVIDIA software stack (NVIDIA CUDA-X™ libraries, AI frameworks, Omniverse™ libraries, NVIDIA AI Enterprise), making it easier to reuse code between data center, workstation, and embedded edge deployments.
Products RTX PRO Embedded GPU Specifications
| GPU Features | NVIDIA RTX PRO 5000 Blackwell | NVIDIA RTX PRO 4000 Blackwell | NVIDIA RTX PRO 2000 Blackwell | NVIDIA RTX PRO 500 Blackwell |
|---|---|---|---|---|
| GPU Architecture | NVIDIA Blackwell | NVIDIA Blackwell | NVIDIA Blackwell | NVIDIA Blackwell |
| CUDA® Parallel Processor Cores | 10,496 | 7,680 | 3,328 | 1,792 |
| Tensor Cores | 320 | 240 | 104 | 56 |
| Memory Size | 24GB | 16GB | 8GB | 6GB |
| Memory Type | GDDR7 | GDDR7 | GDDR7 | GDDR7 |
| Memory Interface | 256-bit | 256-bit | 128-bit | 64-bit |
| Memory Bandwidth | 896 GB/sec | 896 GB/sec | 384 GB/sec | 112 GB/sec |
| ECC Error Correction Code | Yes | Yes | Yes | No |
| Max Power Consumption, Total Graphics Power (Graphics Sub-System) | 115W | 115W | 60-100W | 60W |
| Display Port | 2.1b | 2.1b | 2.1b | 2.1b |
| Encode Sessions | Unlimited | Unlimited | Unlimited | Unlimited |
| Long-Life Availability | Yes | Yes | Yes | Yes |
| GPU Features | NVIDIA RTX 5000 Ada Generation | NVIDIA RTX 3500 Ada Generation | NVIDIA RTX 2000 Ada Generation |
|---|---|---|---|
| GPU Architecture | Ada Lovelace architecture | Ada Lovelace architecture | Ada Lovelace architecture |
| CUDA® Parallel Processor Cores | 9,728 | 5,120 | 3,072 |
| Tensor Cores | 304 (4th Gen) | 160 (4th Gen) | 96 (4th Gen) |
| Memory Size | 16GB | 12GB | 8GB |
| Memory Type | GDDR6 | GDDR6 | GDDR6 |
| Memory Interface | 256-bit | 192-bit | 128-bit |
| Memory Bandwidth | 576 GB/sec | 432 GB/sec | 256 GB/sec |
| ECC Error Correction Code | Yes | Yes | Yes |
| Max Power Consumption, Total Graphics Power (Graphics Sub-System) | 80-150W | 60-115W | 35-115W |
| Display Port | 1.4a | 1.4a | 1.4a |
| Encode Sessions | Unlimited | Unlimited | Unlimited |
| Long-Life Availability | Yes | Yes | Yes |
| GPU Features | NVIDIA RTX A4500 | NVIDIA RTX A2000 | NVIDIA RTX A1000 | NVIDIA RTX A500 |
|---|---|---|---|---|
| GPU Architecture | Ampere architecture | Ampere architecture | Ampere architecture | Ampere architecture |
| CUDA® Parallel Processor Cores | 5,888 | 2,560 | 2,048 | 2,048 |
| Tensor Cores | 184 (3rd Gen) | 80 (3rd Gen) | 64 (3rd Gen) | 64 (3rd Gen) |
| Memory Size | 16GB | 8GB | 4GB | 4GB |
| Memory Type | GDDR6 | GDDR6 | GDDR6 | GDDR6 |
| Memory Interface | 256-bit | 224-bit | 224-bit | 64-bit |
| Memory Bandwidth | 512 GB/sec | 224 GB/sec | 224 GB/sec | 112 GB/sec |
| ECC Error Correction Code | Yes | Yes | - | - |
| Max Power Consumption, Total Graphics Power (Graphics Sub-System) | 115 W | 60 W | 60 W | 35 W |
| Display Port | 1.4 | 1.4 | 1.4 | 1.4 |
| Encode Sessions | Unlimited | Unlimited | 3 | 3 |
| GPUDirect® Remote Direct Memory Access (RDMA) and Video | Yes | Yes | - | - |
| Long-Life Availability | Yes | Yes | Yes | Yes |
| GPU Features | NVIDIA Quadro RTX 5000 | NVIDIA Quadro RTX 3000 | NVIDIA Quadro T1000 |
|---|---|---|---|
| GPU Architecture | Turing architecture | Turing architecture | Turing architecture |
| CUDA® Parallel Processor Cores | 3,072 | 1,920 | 896 |
| Tensor Cores | 384 (2nd Gen) | 240 (2nd Gen) | - |
| Memory Size | 16GB | 6GB | 4GB |
| Memory Type | GDDR6 | GDDR6 | GDDR6 |
| Memory Interface | 256-bit | - | 128-bit |
| Memory Bandwidth | 448 GB/sec | 336 GB/sec | 128 GB/sec |
| ECC Error Correction Code | - | - | - |
| Max Power Consumption, Total Graphics Power (Graphics Sub-System) | 110 W | 80 W | 50 W |
| Display Port | 1.4 | 1.4 | 1.4 |
| Encode Sessions | Unlimited | Unlimited | 3 |
| GPUDirect® Remote Direct Memory Access (RDMA) and Video | Yes | Yes | - |
| Long-Life Availability | Yes | Yes | Yes |
Use Cases
NVIDIA RTX PRO Embedded GPU Use Cases by Industry
Bring AI‑powered perception and decision‑making to embedded systems with NVIDIA RTX PRO—delivering breakthrough performance, rugged designs, and long‑lifecycle reliability at the edge.
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Robotics
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Manufacturing and Industrial
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Healthcare
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Aerospace
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Edge AI Infrastructure
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Commercial Gaming
Robotics
Robots accelerated by NVIDIA RTX PRO embedded GPUs perform real‑time 3D perception, object detection, and motion planning at the edge. RTX PRO delivers the compute needed for agentic AI—robots that continuously sense, decide, and adapt their actions to dynamic environments.
Manufacturing and Industrial
Smart factory systems powered by NVIDIA RTX PRO embedded GPUs run advanced computer vision and AI quality inspection directly on the line. From collaborative robots to 3D printers, RTX PRO enables agentic automation—systems that detect defects, adjust processes, and optimize throughput in real time.
Healthcare
NVIDIA RTX PRO‑powered medical devices bring accelerated imaging and AI assistance to the point of care, enabling real‑time reconstruction, enhancement, and clinical decision support across ultrasound, endoscopy, and radiology.
Aerospace
NVIDIA RTX PRO embedded GPUs power real‑time video, sensor fusion, and AI analytics in SWaP‑constrained aircraft and space systems, enabling faster insights for environmental monitoring, natural disaster assessment, and advanced avionics.
Edge AI Infrastructure
Modular infrastructure environments packed with NVIDIA RTX PRO embedded GPUs enable accelerated video broadcasting, AI, and virtual graphics where multiple GPUs can power edge and remote devices.
Commercial Gaming
NVIDIA RTX PRO powers graphics for casino terminals with specialized customization requirements, including long lifecycle support and enterprise reliability for continued business operation.
Frequently Asked Questions: NVIDIA RTX PRO Embedded GPU Solutions
NVIDIA RTX PRO embedded GPUs bring workstation-class AI, compute, and graphics into embedded and edge systems—medical imaging, robotics, industrial automation, aerospace, and gaming machines. Delivered mainly as compact MXM and PCIe modules through NVIDIA's embedded partners, they pair the NVIDIA Blackwell architecture (and prior generations) with the full NVIDIA software stack, so models built in the data center or on a workstation run at the edge with minimal rework.
The embedded lineup scales from roughly 35W to 150W. For lighter graphics and entry AI inference, lower-power modules (e.g., RTX PRO 500/1000/2000 class, 6–8 GB) are the practical minimum. For real-time 3D perception, multi-stream vision, or larger models, step up to mid-to-high-tier modules (RTX PRO 4000/5000 class, 16-24 GB and up of GDDR7). Match GPU memory to your model size and number of concurrent streams, and confirm the module form factor (MXM vs. PCIe) and thermal/power budget of your chassis with your integrator.
RTX PRO embedded modules are sold through NVIDIA's embedded and OEM partners rather than at a public list price, so pricing is quote-based and depends on the partner, board, and volume. On TCO, the value is in power efficiency and long-lifecycle availability: Efficient performance-per-watt lowers thermal and power costs at the edge, and a stable multi-year supply avoids the expensive re-certification and redesign cycles that hardware changes trigger in regulated markets like medical and industrial. Running inference locally also reduces recurring cloud compute and data-transfer costs, compared with sending everything to a data center.
The differentiator is the platform, not just the silicon. One CUDA-based software stack spans data center, workstation, and edge, so code and models port with minimal changes. You also get RT Cores and Tensor Cores for combined graphics + AI in a single module, enterprise-grade drivers and support, long-lifecycle availability programs, and a broad ecosystem of embedded partners—reducing integration risk and time to market.
They plug into the full NVIDIA ecosystem: CUDA-X libraries, AI frameworks, NVIDIA AI Enterprise for production deployment and management, Omniverse for physical AI, and the NVIDIA App for drivers and optimization. To start, choose a partner board that fits your form factor and power budget, develop against the same CUDA/AI Enterprise tools you'd use on a workstation, then deploy to the edge module.
Both target the edge, but they solve different problems. Jetson is an integrated system-on-module (CPU + GPU + memory) built for compact, low-power autonomous machines. RTX PRO embedded GPUs are discrete modules that add workstation-class graphics and higher AI/compute throughput to an existing embedded host—ideal when you need real-time ray tracing, multi-stream vision, or larger models in an industrial PC or system. Choose Jetson for the smallest, lowest-power, self-contained devices; choose RTX PRO embedded when graphics and throughput are the priority.
They pair high performance with power efficiency (scaling from 35W to 150W), ruggedization for harsh environments, long-lifecycle availability for multi-year deployments, and full integration with the NVIDIA software stack, including CUDA-X libraries, Omniverse libraries, and NVIDIA AI Enterprise.
RTX PRO embedded solutions span the latest NVIDIA Blackwell architecture plus Ada Lovelace, Ampere, and Turing. NVIDIA Blackwell delivers the biggest gains in compute throughput, ray tracing, and memory bandwidth for the most demanding real-time AI and graphics; earlier generations remain cost-effective, proven choices for power-constrained or established designs. Pick based on your performance target, power envelope, and how long you need the part to stay available.
Long-life availability means consistent hardware and stable supply across multi-year deployment cycles, backed by NVIDIA and partner lifecycle programs. That's critical in medical, industrial, and aerospace systems, where swapping a component can force costly re-certification or redesign. Predictable availability protects your engineering investment and lowers long-term cost.
They power real-time perception and motion planning in robotics, accelerated image reconstruction in medical devices (ultrasound, endoscopy, radiology), sensor fusion and AI analytics in SWaP-constrained aerospace systems, and computer-vision quality inspection on the factory floor.
By placing the GPU directly in the edge device, sensor data no longer has to travel to a remote data center for processing. This enables near-instant, on-device decisions—essential for safety-sensitive workloads like robotics and autonomous machines.
RTX PRO embedded modules are delivered through a network of embedded and OEM partners—including ADLINK, Advantech, Curtiss-Wright, EIZO, PNY, Wolf, and ZOTAC—that provide the boards, systems, and integration support. Start with the partner finder or NVIDIA Marketplace to find a solution that matches your application.
NVIDIA RTX PRO Embedded Partner Ecosystem
