The power of modern AI is now available for makers, learners, and embedded developers everywhere. Jetson Nano is a small, powerful computer for embedded applications and AI IoT that delivers the power of modern AI in a module.
Get started fast with the comprehensiveJetPack SDKwith accelerated libraries for deep learning, computer vision, graphics, multimedia, and more. Jetson Nano has the performance and capabilities you need to run modern AI workloads, giving you a fast and easy way to add advanced AI to your next product. To get started with your development process, check out theJetson Nano Developer Kit.
Jetson Nano has the performance and capabilities needed to run modern AI workloads fast, making it possible to add advanced AI to any product. Jetson Nano brings AI to a world of new embedded and IoT applications, including entry-level network video recorders (NVRs), home robots, and intelligent gateways with full analytics capabilities.
Get started today with the Jetson Nano Kit. All Jetson kits ship FREE with Bluedart (applicable to Bluedart service zones only).
Specifications
Module Technical Specifications
GPU
NVIDIA Maxwell™architecture with 128 NVIDIA CUDA®cores 0.5 TFLOPs (FP16)
I had used a lots of LoRa module till now, but it's really the best among all of them! the 1262 is a great upgrade in terms of output power and configuration. we can configure the output power, bandwidth, spreading factor and a tons of other things, which are not possible to configure on previous modules. the radiolib library works preety good with it and it also supports rssi and snr like features, which are very crucial when you are seriously researching on antenna or range related works! that's why I eventually like this module more then ebyte LoRas. To me this is the best module in IN8 68MHz, which is completly legal and free to use in India upto 1W! And also thanks to thinkrobotics, I got it in just 1 working day, and your packaging was also too good! Love your service, and keep this modules available on your websight. Your pricing of this module is too good, and I'll buy many of these modules. Thank you!
I had used a lots of LoRa module till now, but it's really the best among all of them! the 1262 is a great upgrade in terms of output power and configuration. we can configure the output power, bandwidth, spreading factor and a tons of other things, which are not possible to configure on previous modules. the radiolib library works preety good with it and it also supports rssi and snr like features, which are very crucial when you are seriously researching on antenna or range related works! that's why I eventually like this module more then ebyte LoRas. To me this is the best module in IN8 68MHz, which is completly legal and free to use in India upto 1W! And also thanks to thinkrobotics, I got it in just 1 working day, and your packaging was also too good! Love your service, and keep this modules available on your websight. Your pricing of this module is too good, and I'll buy many of these modules. Thank you!
Team is suppotive and solves all the queries .
The product is good and will surely help me in my project...looking forward for more trades with think robotics.
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To get started with your development process, check out the\u003cspan\u003e \u003c\/span\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/buy\/jetson-nano-devkit\"\u003eJetson Nano Developer Kit\u003c\/a\u003e.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eJetson Nano has the performance and capabilities needed to run modern AI workloads fast, making it possible to add advanced AI to any product. Jetson Nano brings AI to a world of new embedded and IoT applications, including entry-level network video recorders (NVRs), home robots, and intelligent gateways with full analytics capabilities.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eGet started today with the Jetson Nano Kit. \u003c\/strong\u003e\u003cstrong\u003eAll Jetson kits ship FREE with Bluedart (applicable to Bluedart service zones only).\u003c\/strong\u003e\u003c\/p\u003e\n\u003ch5\u003eSpecifications\u003c\/h5\u003e\n\u003cp\u003e\u003cspan\u003eModule Technical Specifications\u003c\/span\u003e\u003c\/p\u003e\n\u003ctable align=\"center\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"width: 488.766px; border-collapse: collapse;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eGPU\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eNVIDIA Maxwell\u003csup\u003e™\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003earchitecture with 128 NVIDIA CUDA\u003csup\u003e®\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003ecores 0.5 TFLOPs (FP16)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eCPU\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eQuad-core ARM\u003csup\u003e®\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003eCortex\u003csup\u003e®\u003c\/sup\u003e-A57 MPCore processor\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eMemory\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4 GB 64-bit LPDDR4\u003cbr\u003e1600MHz - 25.6 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eStorage\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e16 GB eMMC 5.1 Flash\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4Kp30 | 4x 1080p30 | 9x 720p30 (H.264\/H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4Kp60 | 2x 4Kp30 | 8x 1080p30 | 18x 720p30 (H.264\/H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eCamera\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e12 lanes (3x4 or 4x2) MIPI CSI-2 D-PHY 1.1 (18 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" class=\"tableCLdata\" style=\"width: 98px;\"\u003eConnectivity\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eWi-Fi requires external chip\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e10\/100\/1000 BASE-T Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eDisplay\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eHDMI 2.0 or DP1.2 | eDP 1.4 | DSI (1 x2) 2 simultaneous\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eUPHY\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e1 x1\/2\/4 PCIE, 1x USB 3.0, 3x USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eI\/O\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e3x UART, 2x SPI, 2x I2S, 4x I2C, GPIOs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eSize\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e69.6 mm x 45 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eMechanical\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e260-pin edge connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","published_at":"2022-12-06T11:12:04+05:30","created_at":"2021-08-20T16:17:13+05:30","vendor":"NVIDIA","type":"System on Module","tags":["AI","AI GPU","CUDA","GPU","Jetson GPU","Jetson module","jetson nano","Jetson Nano Case","JETSON SOM","JT-SOM","NVDA","nvidia","nvidia jetson","SBC1","SOM","System on Module","ZOHO UPDATED"],"price":1364599,"price_min":1364599,"price_max":1364599,"available":true,"price_varies":false,"compare_at_price":1899999,"compare_at_price_min":1899999,"compare_at_price_max":1899999,"compare_at_price_varies":false,"variants":[{"id":39512343609430,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"SBC1101-MOD","requires_shipping":true,"taxable":true,"featured_image":null,"available":true,"name":"NVIDIA Jetson Nano Module","public_title":null,"options":["Default Title"],"price":1364599,"weight":125,"compare_at_price":1899999,"inventory_management":"shopify","barcode":"SBC1101-MOD","requires_selling_plan":false,"selling_plan_allocations":[]}],"images":["\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-nano-module-standing-2c50-d.jpg?v=1629456435","\/\/thinkrobotics.com\/cdn\/shop\/products\/jetson-nano-commercial-module-2c50-d.jpg?v=1629456435"],"featured_image":"\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-nano-module-standing-2c50-d.jpg?v=1629456435","options":["Title"],"media":[{"alt":"NVIDIA Jetson Nano Module Online","id":21199429795926,"position":1,"preview_image":{"aspect_ratio":1.78,"height":354,"width":630,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-nano-module-standing-2c50-d.jpg?v=1629456435"},"aspect_ratio":1.78,"height":354,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/nvidia-jetson-nano-module-standing-2c50-d.jpg?v=1629456435","width":630},{"alt":"NVIDIA Jetson Nano Module Online","id":21199429828694,"position":2,"preview_image":{"aspect_ratio":1.78,"height":354,"width":630,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/jetson-nano-commercial-module-2c50-d.jpg?v=1629456435"},"aspect_ratio":1.78,"height":354,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/jetson-nano-commercial-module-2c50-d.jpg?v=1629456435","width":630}],"requires_selling_plan":false,"selling_plan_groups":[],"content":"\u003cp\u003e\u003cspan data-mce-fragment=\"1\"\u003eThe power of modern AI is now available for makers, learners, and embedded developers everywhere. \u003c\/span\u003eJetson Nano is a small, powerful computer for embedded applications and AI IoT that delivers the power of modern AI in a module.\u003c\/p\u003e\n\u003cp\u003eGet started fast with the comprehensive\u003cspan\u003e \u003c\/span\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\"\u003eJetPack SDK\u003c\/a\u003e\u003cspan\u003e \u003c\/span\u003ewith accelerated libraries for deep learning, computer vision, graphics, multimedia, and more. Jetson Nano has the performance and capabilities you need to run modern AI workloads, giving you a fast and easy way to add advanced AI to your next product. To get started with your development process, check out the\u003cspan\u003e \u003c\/span\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/buy\/jetson-nano-devkit\"\u003eJetson Nano Developer Kit\u003c\/a\u003e.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eJetson Nano has the performance and capabilities needed to run modern AI workloads fast, making it possible to add advanced AI to any product. Jetson Nano brings AI to a world of new embedded and IoT applications, including entry-level network video recorders (NVRs), home robots, and intelligent gateways with full analytics capabilities.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eGet started today with the Jetson Nano Kit. \u003c\/strong\u003e\u003cstrong\u003eAll Jetson kits ship FREE with Bluedart (applicable to Bluedart service zones only).\u003c\/strong\u003e\u003c\/p\u003e\n\u003ch5\u003eSpecifications\u003c\/h5\u003e\n\u003cp\u003e\u003cspan\u003eModule Technical Specifications\u003c\/span\u003e\u003c\/p\u003e\n\u003ctable align=\"center\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"width: 488.766px; border-collapse: collapse;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eGPU\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eNVIDIA Maxwell\u003csup\u003e™\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003earchitecture with 128 NVIDIA CUDA\u003csup\u003e®\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003ecores 0.5 TFLOPs (FP16)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eCPU\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eQuad-core ARM\u003csup\u003e®\u003c\/sup\u003e\u003cspan\u003e \u003c\/span\u003eCortex\u003csup\u003e®\u003c\/sup\u003e-A57 MPCore processor\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eMemory\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4 GB 64-bit LPDDR4\u003cbr\u003e1600MHz - 25.6 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eStorage\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e16 GB eMMC 5.1 Flash\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4Kp30 | 4x 1080p30 | 9x 720p30 (H.264\/H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e4Kp60 | 2x 4Kp30 | 8x 1080p30 | 18x 720p30 (H.264\/H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eCamera\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e12 lanes (3x4 or 4x2) MIPI CSI-2 D-PHY 1.1 (18 Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" class=\"tableCLdata\" style=\"width: 98px;\"\u003eConnectivity\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eWi-Fi requires external chip\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e10\/100\/1000 BASE-T Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eDisplay\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003eHDMI 2.0 or DP1.2 | eDP 1.4 | DSI (1 x2) 2 simultaneous\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eUPHY\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e1 x1\/2\/4 PCIE, 1x USB 3.0, 3x USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eI\/O\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e3x UART, 2x SPI, 2x I2S, 4x I2C, GPIOs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eSize\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e69.6 mm x 45 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"tableCLdata\" style=\"width: 98px;\"\u003eMechanical\u003c\/td\u003e\n\u003ctd colspan=\"2\" class=\"tableCRdata\" style=\"width: 384.766px;\"\u003e260-pin edge connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e"}
