NVIDIA® Jetson™ TX2 series modules give you exceptional speed and power efficiency in an embedded AI computing device. Each supercomputer-on-a-module brings true AI computing to the edge with an NVIDIA Pascal™ GPU, up to 8 GB of memory and 59.7 GB/s of memory bandwidth, and a wide range of standard hardware interfaces.
Rugged design, small form factor, and reduced power envelope make Jetson TX2i ideal for high-performance edge computing devices such as industrial robots, machine vision cameras, and portable medical equipment.
Features
SIze
MINIMIZE YOUR FOOTPRINT Now you can get exceptionally high compute, accuracy, and power efficiency in a module the size of a credit card. Its small 50 mm x 87 mm size enables real deep learning applications in small form-factor products like drones and more.
Performance
MAXIMIZE YOUR PERFORMANCE Experience more than double the performance or twice the energy efficiency of Jetson TX1. It’s all made possible by Jetson TX2’s 256-core NVIDIA Pascal architecture and 8 GB memory for the fastest compute and inference.
Power
OPTIMIZE YOUR POWER EFFICIENCY With Jetson TX2, you can now run large, deep neural networks for higher accuracy on edge devices. At just 7.5 watts, it delivers 25X more energy efficiency than a state-of-the-art desktop-class CPU. This makes it ideal for real-time processing in applications where bandwidth and latency can be an issue. These include factory robots, commercial drones, enterprise collaboration devices, intelligent cameras for smart cities.
A JETSON TX2 FOR ANY APPLICATION The extended Jetson TX2 family of embedded modules provides up to 2.5X the performance of Jetson Nano in as little as 7.5 W. Jetson TX2 NX offers pin and form-factor compatibility with Jetson Nano, while Jetson TX2, TX2 4GB, and TX2i all share the original Jetson TX2 form-factor. The rugged Jetson TX2i is ideal for settings including industrial robots and medical equipment.
Specifications
GPU
NVIDIA Pascal™architecture with 256 NVIDIA CUDA cores 1.3 TFLOPS (FP16)
CPU
Dual-core Denver 2 64-bit CPU and quad-core ARM A57 complex
{"id":6620752576598,"title":"NVIDIA Jetson TX2i Module","handle":"nvidia-jetson-tx2i-module-online","description":"\u003cp\u003eNVIDIA® Jetson™ TX2 series modules give you exceptional speed and power efficiency in an embedded AI computing device. Each supercomputer-on-a-module brings true AI computing to the edge with an NVIDIA Pascal™ GPU, up to 8 GB of memory and 59.7 GB\/s of memory bandwidth, and a wide range of standard hardware interfaces.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eRugged design, small form factor, and reduced power envelope make Jetson TX2i ideal for high-performance edge computing devices such as industrial robots, machine vision cameras, and portable medical equipment.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch5\u003eFeatures\u003c\/h5\u003e\n\u003cp\u003eSIze\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMINIMIZE YOUR FOOTPRINT\u003c\/strong\u003e\u003cbr\u003eNow you can get exceptionally high compute, accuracy, and power efficiency in a module the size of a credit card. Its small 50 mm x 87 mm size enables real deep learning applications in small form-factor products like drones and more.\u003c\/p\u003e\n\u003cp\u003ePerformance \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMAXIMIZE YOUR PERFORMANCE\u003c\/strong\u003e\u003cbr\u003eExperience more than double the performance or twice the energy efficiency of Jetson TX1. It’s all made possible by Jetson TX2’s 256-core NVIDIA Pascal architecture and 8 GB memory for the fastest compute and inference.\u003c\/p\u003e\n\u003cp\u003ePower\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eOPTIMIZE YOUR POWER EFFICIENCY\u003c\/strong\u003e\u003cbr\u003eWith Jetson TX2, you can now run large, deep neural networks for higher accuracy on edge devices. At just 7.5 watts, it delivers 25X more energy efficiency than a state-of-the-art desktop-class CPU. This makes it ideal for real-time processing in applications where bandwidth and latency can be an issue. These include factory robots, commercial drones, enterprise collaboration devices, intelligent cameras for smart cities.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eA JETSON TX2 FOR ANY APPLICATION\u003c\/strong\u003e\u003cbr\u003eThe extended Jetson TX2 family of embedded modules provides up to 2.5X the performance of Jetson Nano in as little as 7.5 W. Jetson TX2 NX offers pin and form-factor compatibility with Jetson Nano, while Jetson TX2, TX2 4GB, and TX2i all share the original Jetson TX2 form-factor. The rugged Jetson TX2i is ideal for settings including industrial robots and medical equipment.\u003c\/p\u003e\n\u003ch5\u003eSpecifications\u003c\/h5\u003e\n\u003ctable data-mce-fragment=\"1\" style=\"width: 430.812px;\" align=\"center\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n\u003ctbody data-mce-fragment=\"1\"\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eGPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eNVIDIA Pascal\u003csup data-mce-fragment=\"1\"\u003e™\u003c\/sup\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003earchitecture with 256 NVIDIA CUDA cores\u003cbr data-mce-fragment=\"1\"\u003e1.3 TFLOPS (FP16)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eCPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eDual-core Denver 2 64-bit CPU and quad-core ARM A57 complex\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eMemory\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e8 GB 128-bit LPDDR4\u003cbr data-mce-fragment=\"1\"\u003e1600MHz - 51.2 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eStorage\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e32 GB eMMC 5.1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e500 MP\/sec\u003cbr data-mce-fragment=\"1\"\u003e1x 4K @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e3x 4K @ 30 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e4x 1080p @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e8x 1080p @ 30 (HEVC)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1000 MP\/sec\u003cbr data-mce-fragment=\"1\"\u003e2x 4K @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e4x 4K @ 30 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e7x 1080p @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e14x 1080p @ 30 (HEVC)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" rowspan=\"2\" class=\"tableCLdata\"\u003eConnectivity\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eWi-Fi requires external chip\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e10\/100\/1000 BASE-T Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eCamera\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e12 lanes MIPI CSI-2, D-PHY 1.2 (30 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eDisplay\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eHDMI 2.0 \/ eDP 1.4 \/ 2x DSI \/ 2x DP 1.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eUPHY\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eGen 2 | 1x4 + 1x1 OR 2x1 + 1x2, USB 3.0 + USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eSize\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e87 mm x 50 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eMechanical\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e400-pin connector with Thermal Transfer Plate (TTP)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e","published_at":"2022-12-06T11:11:46+05:30","created_at":"2021-08-24T16:13:23+05:30","vendor":"ThinkRobotics","type":"Single Board Computers","tags":["Jetson GPU","Jetson module","jetson nano","Jetson Nano Case","jetson xavier","JT-SOM","NVDA","nvidia","nvidia gpu","nvidia jetson","nvidia nx","nvidia tx2","NVIDIA-com","SBC1","tx2","tx2 4gb","tx2 nx","tx2 nx1","tx2 nxi"],"price":8699999,"price_min":8699999,"price_max":8699999,"available":true,"price_varies":false,"compare_at_price":8999900,"compare_at_price_min":8999900,"compare_at_price_max":8999900,"compare_at_price_varies":false,"variants":[{"id":39516455469142,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"SBC1103-MODi","requires_shipping":true,"taxable":true,"featured_image":null,"available":true,"name":"NVIDIA Jetson TX2i Module","public_title":null,"options":["Default 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Online","id":21213119512662,"position":2,"preview_image":{"aspect_ratio":1.775,"height":169,"width":300,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-tx2-module-2c50-t.jpg?v=1629802003"},"aspect_ratio":1.775,"height":169,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-tx2-module-2c50-t.jpg?v=1629802003","width":300}],"requires_selling_plan":false,"selling_plan_groups":[],"content":"\u003cp\u003eNVIDIA® Jetson™ TX2 series modules give you exceptional speed and power efficiency in an embedded AI computing device. Each supercomputer-on-a-module brings true AI computing to the edge with an NVIDIA Pascal™ GPU, up to 8 GB of memory and 59.7 GB\/s of memory bandwidth, and a wide range of standard hardware interfaces.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eRugged design, small form factor, and reduced power envelope make Jetson TX2i ideal for high-performance edge computing devices such as industrial robots, machine vision cameras, and portable medical equipment.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch5\u003eFeatures\u003c\/h5\u003e\n\u003cp\u003eSIze\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMINIMIZE YOUR FOOTPRINT\u003c\/strong\u003e\u003cbr\u003eNow you can get exceptionally high compute, accuracy, and power efficiency in a module the size of a credit card. Its small 50 mm x 87 mm size enables real deep learning applications in small form-factor products like drones and more.\u003c\/p\u003e\n\u003cp\u003ePerformance \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMAXIMIZE YOUR PERFORMANCE\u003c\/strong\u003e\u003cbr\u003eExperience more than double the performance or twice the energy efficiency of Jetson TX1. It’s all made possible by Jetson TX2’s 256-core NVIDIA Pascal architecture and 8 GB memory for the fastest compute and inference.\u003c\/p\u003e\n\u003cp\u003ePower\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eOPTIMIZE YOUR POWER EFFICIENCY\u003c\/strong\u003e\u003cbr\u003eWith Jetson TX2, you can now run large, deep neural networks for higher accuracy on edge devices. At just 7.5 watts, it delivers 25X more energy efficiency than a state-of-the-art desktop-class CPU. This makes it ideal for real-time processing in applications where bandwidth and latency can be an issue. These include factory robots, commercial drones, enterprise collaboration devices, intelligent cameras for smart cities.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eA JETSON TX2 FOR ANY APPLICATION\u003c\/strong\u003e\u003cbr\u003eThe extended Jetson TX2 family of embedded modules provides up to 2.5X the performance of Jetson Nano in as little as 7.5 W. Jetson TX2 NX offers pin and form-factor compatibility with Jetson Nano, while Jetson TX2, TX2 4GB, and TX2i all share the original Jetson TX2 form-factor. The rugged Jetson TX2i is ideal for settings including industrial robots and medical equipment.\u003c\/p\u003e\n\u003ch5\u003eSpecifications\u003c\/h5\u003e\n\u003ctable data-mce-fragment=\"1\" style=\"width: 430.812px;\" align=\"center\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n\u003ctbody data-mce-fragment=\"1\"\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eGPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eNVIDIA Pascal\u003csup data-mce-fragment=\"1\"\u003e™\u003c\/sup\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003earchitecture with 256 NVIDIA CUDA cores\u003cbr data-mce-fragment=\"1\"\u003e1.3 TFLOPS (FP16)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eCPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eDual-core Denver 2 64-bit CPU and quad-core ARM A57 complex\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eMemory\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e8 GB 128-bit LPDDR4\u003cbr data-mce-fragment=\"1\"\u003e1600MHz - 51.2 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eStorage\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e32 GB eMMC 5.1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e500 MP\/sec\u003cbr data-mce-fragment=\"1\"\u003e1x 4K @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e3x 4K @ 30 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e4x 1080p @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e8x 1080p @ 30 (HEVC)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1000 MP\/sec\u003cbr data-mce-fragment=\"1\"\u003e2x 4K @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e4x 4K @ 30 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e7x 1080p @ 60 (HEVC)\u003cbr data-mce-fragment=\"1\"\u003e14x 1080p @ 30 (HEVC)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" rowspan=\"2\" class=\"tableCLdata\"\u003eConnectivity\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eWi-Fi requires external chip\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e10\/100\/1000 BASE-T Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eCamera\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e12 lanes MIPI CSI-2, D-PHY 1.2 (30 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eDisplay\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eHDMI 2.0 \/ eDP 1.4 \/ 2x DSI \/ 2x DP 1.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eUPHY\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003eGen 2 | 1x4 + 1x1 OR 2x1 + 1x2, USB 3.0 + USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eSize\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e87 mm x 50 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 93px;\" class=\"tableCLdata\"\u003eMechanical\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 20px;\" colspan=\"2\" class=\"tableCRdata\"\u003e400-pin connector with Thermal Transfer Plate (TTP)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e"}
