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.
Jetson TX2 is a 7.5-watt supercomputer on a module that brings true AI computing at the edge. It's built around an NVIDIA Pascal™-family GPU and loaded with 8 GB of memory and 59.7 GB/s of memory bandwidth. It features a variety of standard hardware interfaces that make it easy to integrate into a wide range of products and form factors.
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
AI Performance
1.33 TFLOPS
GPU
NVIDIA Pascal™architecture with 256 NVIDIA CUDA cores 1.3 TFLOPS (FP16)
CPU
Dual-core NVIDIA Denver 2 64-bit CPU and quad-core Arm®Cortex®-A57 MPCore processor complex
Memory
8 GB 128-bit LPDDR4 59.7 GB/s
Power
7.5W | 15W
PCIe
1 x4 + 1 x1 OR 2 x1 + 1 x2 PCIe Gen 2, total 50GT/s
CSI Camera
Up to 6 cameras (12 via virtual channels) 12 lanes MIPI CSI-2 (3x4 or 6x2), D-PHY 1.2 (up to 30 Gbps)
{"id":6620746219606,"title":"NVIDIA Jetson TX2 8GB","handle":"nvidia-jetson-tx2-8gb-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\u003eJetson TX2 is a 7.5-watt supercomputer on a module that brings true AI computing at the edge. It's built around an NVIDIA Pascal\u003c\/span\u003e\u003csup\u003e™\u003c\/sup\u003e\u003cspan\u003e-family GPU and loaded with 8 GB of memory and 59.7 GB\/s of memory bandwidth. It features a variety of standard hardware interfaces that make it easy to integrate into a wide range of products and form factors.\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: 483.812px;\" 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: 89px;\" class=\"tableCLdata\"\u003eAI Performance\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1.33 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eGPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" 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: 89px;\" class=\"tableCLdata\"\u003eCPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eDual-core NVIDIA Denver 2 64-bit CPU and quad-core Arm\u003csup data-mce-fragment=\"1\"\u003e®\u003c\/sup\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eCortex\u003csup data-mce-fragment=\"1\"\u003e®\u003c\/sup\u003e-A57 MPCore processor complex\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eMemory\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e8 GB 128-bit LPDDR4\u003cbr data-mce-fragment=\"1\"\u003e59.7 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003ePower\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e7.5W | 15W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003ePCIe\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1 x4 + 1 x1 OR 2 x1 + 1 x2\u003cbr data-mce-fragment=\"1\"\u003ePCIe Gen 2, total 50GT\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eCSI Camera\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eUp to 6 cameras (12 via virtual channels)\u003cbr data-mce-fragment=\"1\"\u003e12 lanes MIPI CSI-2 (3x4 or 6x2),\u003cbr data-mce-fragment=\"1\"\u003eD-PHY 1.2 (up to 30 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1x 4K60 | 3x 4K30 | 4x 1080p60 | 8x 1080p30 (H.265)\u003cbr data-mce-fragment=\"1\"\u003e1x 4K60 | 3x 4K30 | 7x 1080p60 | 14x 1080p30 (H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e2x 4K60 | 4x 4K30 | 7x 1080p60 | 14x 1080p30 (H.265 \u0026amp; H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eDisplay\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e2 multi-mode DP 1.2\/eDP 1.4\/HDMI 2.0\u003cbr data-mce-fragment=\"1\"\u003e2 x4 DSI (1.5Gbps\/lane)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eNetworking\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eWi-Fi onboard\u003cbr data-mce-fragment=\"1\"\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: 89px;\" class=\"tableCLdata\"\u003eMechanical\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px; text-align: left;\" colspan=\"2\" class=\"tableCRdata\"\u003e87 mm x 50 mm\u003cbr data-mce-fragment=\"1\"\u003e400-pin connector\u003cbr data-mce-fragment=\"1\"\u003eThermal Transfer Plate (TTP)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e","published_at":"2022-12-06T11:11:49+05:30","created_at":"2021-08-24T15:39:24+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 8GB","tx2 nx"],"price":4899999,"price_min":4899999,"price_max":4899999,"available":true,"price_varies":false,"compare_at_price":5199900,"compare_at_price_min":5199900,"compare_at_price_max":5199900,"compare_at_price_varies":false,"variants":[{"id":39516438495318,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"SBC1103-MOD8","requires_shipping":true,"taxable":true,"featured_image":null,"available":true,"name":"NVIDIA Jetson TX2 8GB","public_title":null,"options":["Default Title"],"price":4899999,"weight":799,"compare_at_price":5199900,"inventory_management":"shopify","barcode":"39516438495318","requires_selling_plan":false,"selling_plan_allocations":[]}],"images":["\/\/thinkrobotics.com\/cdn\/shop\/products\/Image4.png?v=1629800353","\/\/thinkrobotics.com\/cdn\/shop\/products\/tx2_module_170203_0017_transp_2000px.png?v=1629800391"],"featured_image":"\/\/thinkrobotics.com\/cdn\/shop\/products\/Image4.png?v=1629800353","options":["Title"],"media":[{"alt":"NVIDIA Jetson TX2 8GB Online","id":21213069770838,"position":1,"preview_image":{"aspect_ratio":1.0,"height":1000,"width":1000,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/Image4.png?v=1629800353"},"aspect_ratio":1.0,"height":1000,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/Image4.png?v=1629800353","width":1000},{"alt":"NVIDIA Jetson TX2 8GB Online","id":21213073309782,"position":2,"preview_image":{"aspect_ratio":1.591,"height":494,"width":786,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/tx2_module_170203_0017_transp_2000px.png?v=1629800391"},"aspect_ratio":1.591,"height":494,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/tx2_module_170203_0017_transp_2000px.png?v=1629800391","width":786}],"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\u003eJetson TX2 is a 7.5-watt supercomputer on a module that brings true AI computing at the edge. It's built around an NVIDIA Pascal\u003c\/span\u003e\u003csup\u003e™\u003c\/sup\u003e\u003cspan\u003e-family GPU and loaded with 8 GB of memory and 59.7 GB\/s of memory bandwidth. It features a variety of standard hardware interfaces that make it easy to integrate into a wide range of products and form factors.\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: 483.812px;\" 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: 89px;\" class=\"tableCLdata\"\u003eAI Performance\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1.33 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eGPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" 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: 89px;\" class=\"tableCLdata\"\u003eCPU\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eDual-core NVIDIA Denver 2 64-bit CPU and quad-core Arm\u003csup data-mce-fragment=\"1\"\u003e®\u003c\/sup\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eCortex\u003csup data-mce-fragment=\"1\"\u003e®\u003c\/sup\u003e-A57 MPCore processor complex\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eMemory\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e8 GB 128-bit LPDDR4\u003cbr data-mce-fragment=\"1\"\u003e59.7 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003ePower\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e7.5W | 15W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003ePCIe\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1 x4 + 1 x1 OR 2 x1 + 1 x2\u003cbr data-mce-fragment=\"1\"\u003ePCIe Gen 2, total 50GT\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eCSI Camera\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eUp to 6 cameras (12 via virtual channels)\u003cbr data-mce-fragment=\"1\"\u003e12 lanes MIPI CSI-2 (3x4 or 6x2),\u003cbr data-mce-fragment=\"1\"\u003eD-PHY 1.2 (up to 30 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e1x 4K60 | 3x 4K30 | 4x 1080p60 | 8x 1080p30 (H.265)\u003cbr data-mce-fragment=\"1\"\u003e1x 4K60 | 3x 4K30 | 7x 1080p60 | 14x 1080p30 (H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e2x 4K60 | 4x 4K30 | 7x 1080p60 | 14x 1080p30 (H.265 \u0026amp; H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eDisplay\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003e2 multi-mode DP 1.2\/eDP 1.4\/HDMI 2.0\u003cbr data-mce-fragment=\"1\"\u003e2 x4 DSI (1.5Gbps\/lane)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-mce-fragment=\"1\"\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 89px;\" class=\"tableCLdata\"\u003eNetworking\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px;\" colspan=\"2\" class=\"tableCRdata\"\u003eWi-Fi onboard\u003cbr data-mce-fragment=\"1\"\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: 89px;\" class=\"tableCLdata\"\u003eMechanical\u003c\/td\u003e\n\u003ctd data-mce-fragment=\"1\" style=\"width: 388.812px; text-align: left;\" colspan=\"2\" class=\"tableCRdata\"\u003e87 mm x 50 mm\u003cbr data-mce-fragment=\"1\"\u003e400-pin connector\u003cbr data-mce-fragment=\"1\"\u003eThermal Transfer Plate (TTP)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e"}
