{"product_id":"lattepanda-mu-a-micro-x86-compute-module-n100-cpu-8gb-ram-64gb-emmc","title":"LattePanda Mu - A Micro x86 Compute Module (N100 CPU,8GB RAM,64GB eMMC)","description":"\u003ch1\u003eSPECIFICATIONS\u003c\/h1\u003e\u003cp\u003e\u003cspan\u003eBattery Included\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eno\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eBrand Name\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003ecbhioarpd\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eDemo Board Type\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eARM\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eHigh-concerned chemical\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003enone\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eOrigin\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eMainland China\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eTypical Application Fields\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eEducation and Learning\u003c\/span\u003e\u003c\/p\u003e\u003cdiv class=\"detailmodule_html\"\u003e\u003cdiv class=\"detail-desc-decorate-richtext\"\u003e\n\u003cdiv class=\"detailmodule_dynamic\"\u003e \n \u003ckse:widget data-widget-type=\"customText\" id=\"1005000003593677\" type=\"custom\"\u003e\u003c\/kse:widget\u003e \n\u003c\/div\u003e\n\u003ch4 style=\"font-family:roboto, -webkit-pictograph;font-size:24px;font-weight:700;letter-spacing:normal;line-height:1.1;text-align:start;white-space:normal;color:rgb(49, 49, 49);background-color:rgb(245, 245, 245);box-sizing:border-box;margin-top:0px;margin-bottom:10px;\" align=\"start\"\u003eINTRODUCTION\u003c\/h4\u003e\n\u003cdiv style=\"font-family:roboto, -webkit-pictograph;font-size:16px;font-weight:400;letter-spacing:normal;text-align:start;white-space:normal;color:rgb(83, 83, 83);background-color:rgb(245, 245, 245);border-bottom:1px solid rgb(201, 201, 201);box-sizing:border-box;padding-bottom:20px;margin-bottom:20px;\" class=\"desCon\" align=\"start\"\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Mu is a micro x86 compute module featuring Intel N100 quad-core processor, 8GB LPDDR5 memory and 64GB storage. LattePanda Mu exposes extensive pins, including 3 HDMI\/DisplayPort, 8 USB 2.0, up to 4 USB 3.2, up to 9 PCIe 3.0 lanes. These flexible ports and open-source carrier board files enable users to effortlessly design custom carrier boards to meet their unique requirements.\u003c\/p\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/kit-004.html\" target=\"_blank\" class=\"\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module Kit\" src=\"https:\/\/ae01.alicdn.com\/kf\/S1ecf6b6ce4df4c5b9628fe182f5fd3241.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S1ecf6b6ce4df4c5b9628fe182f5fd3241.jpg\"\u003e\u003c\/a\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003e\u003cbr\u003e\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eSmall but Powerful\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Mu x86 compute module features Intel N100 quad-core processor with 3.4GHz turbo frequency, offering ample performance and multitasking capabilities for the majority of applications.\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eEquipped with an Intel Processor N100, LattePanda Mu compute module offers a multi-core score of 3115 and a single-core score of 1217 on Geekbench 6, outperforming the Raspberry Pi 5, Intel Celeron N510, and Atom x5-Z8350. Its CPU performance doubles the Raspberry Pi 5.\u003c\/p\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module 4 cores max 3.4GHz performance\" src=\"https:\/\/ae01.alicdn.com\/kf\/S83733f1ccd4742c8a3b393f8238a6ec0r.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S83733f1ccd4742c8a3b393f8238a6ec0r.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module outperforming benchmark\" src=\"https:\/\/ae01.alicdn.com\/kf\/S948d08780d97425ba70379d155d75edda.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S948d08780d97425ba70379d155d75edda.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003e\u003cbr\u003e\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eCard-Sized\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eDespite its small size of 69.6mm x 60mm, The pocket size of the LattePanda Mu N100 computer-on-module allows for integration into space-constrained devices, delivering powerful computation without occupying much space.\u003c\/p\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"Card-Sized LattePanda Mu x86 compute module\" src=\"https:\/\/ae01.alicdn.com\/kf\/S257e21585e2e4aa3adfa80d666d0bd85D.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S257e21585e2e4aa3adfa80d666d0bd85D.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eFlexibility in Performance and Energy\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eThe processor's TDP can be adjusted from 6W to 35W, providing flexibility in power usage and heat output. The 6W setting enables efficient operation with minimal heat and silent passive cooling, while the 35W setting offers robust performance but requires active cooling.\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eDFRobot provides three distinct cooling solutions:\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/product-2823.html\" target=\"_blank\" class=\"\"\u003eAluminum Active Cooler\u003c\/a\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/product-2825.html\" target=\"_blank\" class=\"\"\u003eAluminum Fanless Heatsink\u003c\/a\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/product-2824.html\" target=\"_blank\" class=\"\"\u003eAluminum Passive Thin Heatsink\u003c\/a\u003e\u003c\/p\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module Thermal Design Power\" src=\"https:\/\/ae01.alicdn.com\/kf\/S3438f9386e1f44749663c4e6e54f8169E.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S3438f9386e1f44749663c4e6e54f8169E.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eFlexible Expansion Pins\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Mu compute module exposes extensive pins, such as 3 HDMI\/DisplayPort, 8 USB 2.0, up to 4 USB 3.2, 9 PCIe 3.0 lanes, 2 SATA 3.0 and 64 expandable GPIOs. This offers unparalleled flexibility and expandability, allowing you to create the specific solution.\u003c\/p\u003e \n \u003cdiv style=\"text-align:center;box-sizing:border-box;\" align=\"center\"\u003e \n  \u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module with Rich Expansion Pins\" src=\"https:\/\/ae01.alicdn.com\/kf\/S99a2de801d6a456e858aa0d6310f0922L.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S99a2de801d6a456e858aa0d6310f0922L.jpg\"\u003e \n \u003c\/div\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eCarrier Boards - Expanding Infinite Possibilities\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eDFRobot offers a\u003cspan\u003e \u003c\/span\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/product-2822.html\" target=\"_blank\" class=\"\"\u003elite carrier board for the LattePanda Mu\u003c\/a\u003e, providing a comprehensive development platform with various interfaces for swift design verification. Additionally,\u003cspan\u003e \u003c\/span\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/www.dfrobot.com\/product-2821.html\" target=\"_blank\" class=\"\"\u003ea full-function evaluation carrier board\u003c\/a\u003e\u003cspan\u003e \u003c\/span\u003eis available, exposing all pins of the LattePanda Mu for extensive hardware and software testing.\u003c\/p\u003e \n \u003cdiv\u003e \n  \u003cstrong\u003eNote:\u003c\/strong\u003e \n  \u003cstrong\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/strong\u003eThe PCIe slot of the lite carrier is available only when using a 12V power supply. \n \u003c\/div\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module Carrier Boards\" src=\"https:\/\/ae01.alicdn.com\/kf\/Sea67f19c179d413e816856042c2cc60bY.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/Sea67f19c179d413e816856042c2cc60bY.jpg\"\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eMaking Carrier Simpler and Easier\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Mu x86 compute module offers\u003cspan\u003e \u003c\/span\u003e\u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"https:\/\/github.com\/LattePandaTeam\/LattePanda-Mu\" target=\"_blank\" class=\"\"\u003eopen-source carrier board files and libraries\u003c\/a\u003e\u003cspan\u003e \u003c\/span\u003eas reference materials, enabling you to fine-tune the carrier board design to meet your specific needs, significantly reducing development time.\u003c\/p\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module open-source carrier board files and libraries\" src=\"https:\/\/ae01.alicdn.com\/kf\/S5bf2affb0696400ca4288c6e72a9d1399.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S5bf2affb0696400ca4288c6e72a9d1399.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eMulti-System Support\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Mu x86 computer-on-module supports multiple operating systems, including Windows 10, Windows 11, Ubuntu, ensuring that there is always one that suits your needs.\u003c\/p\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module supports multiple operating systems\" src=\"https:\/\/ae01.alicdn.com\/kf\/S3c3771eb14ec48169981cdc72f9a58bam.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S3c3771eb14ec48169981cdc72f9a58bam.jpg\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cbr\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003e\u003cstrong\u003eCustomized Solutions\u003c\/strong\u003e\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eLattePanda Team offers customized services, including customized carrier boards, boot screens, BIOS functionality, operating systems, etc. If you have any specific requirements, please feel free to contact us at \u003ca style=\"color:rgb(35, 161, 209);background-color:transparent;box-sizing:border-box;\" href=\"http:\/\/solution@lattepanda.com\/\" target=\"_blank\" class=\"\"\u003esolution@lattepanda.com\u003c\/a\u003e.\u003c\/p\u003e \n \u003cp style=\"margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\"\u003eThe LattePanda Team is dedicated to providing timely and professional support to meet your customization needs.\u003c\/p\u003e \n \u003cdiv\u003e \n  \u003cbr\u003e \n \u003c\/div\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"LattePanda Mu x86 compute module offers customized solutions\" src=\"https:\/\/ae01.alicdn.com\/kf\/Sce497e15f7c741c7be501b574a51e8f7m.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/Sce497e15f7c741c7be501b574a51e8f7m.jpg\"\u003e\u003c\/p\u003e \n\u003c\/div\u003e\n\u003ch4 style=\"font-family:roboto, -webkit-pictograph;font-size:24px;font-weight:700;letter-spacing:normal;line-height:1.1;text-align:start;white-space:normal;color:rgb(49, 49, 49);background-color:rgb(245, 245, 245);box-sizing:border-box;margin-top:0px;margin-bottom:10px;\" align=\"start\"\u003eFEATURES\u003c\/h4\u003e\n\u003cdiv style=\"font-family:roboto, -webkit-pictograph;font-size:16px;font-weight:400;letter-spacing:normal;text-align:start;white-space:normal;color:rgb(83, 83, 83);background-color:rgb(245, 245, 245);border-bottom:1px solid rgb(201, 201, 201);box-sizing:border-box;padding-bottom:20px;margin-bottom:20px;\" class=\"desCon\" align=\"start\"\u003e \n \u003cp\u003eIntel Processor N100 (Up to 3.4GHz, 4-core, 4-thread)\u003c\/p\u003e \n \u003cp\u003eOnboard 8GB 4800MHz LPDDR5 memory with IBECC supported\u003c\/p\u003e \n \u003cp\u003e64GB eMMC 5.1 storage\u003c\/p\u003e \n \u003cp\u003eConfigurable TDP: 6W ~ 35W\u003c\/p\u003e \n \u003cp\u003eMultiple OS Support: Windows 10, Windows 11, Ubuntu\u003c\/p\u003e \n \u003cp\u003eRich Expansion Pins, including: 3 HDMI\/DisplayPort, 8 USB 2.0, up to 4 USB 3.2, 9 PCIe 3.0 lanes, 2 SATA 3.0, 64 expandable GPIOs, etc.\u003c\/p\u003e \n \u003cp\u003eOpen-source Design Files (KiCAD) of Carrier Boards\u003c\/p\u003e \n\u003c\/div\u003e\n\u003ch4 style=\"font-family:roboto, -webkit-pictograph;font-size:24px;font-weight:700;letter-spacing:normal;line-height:1.1;text-align:start;white-space:normal;color:rgb(49, 49, 49);background-color:rgb(245, 245, 245);box-sizing:border-box;margin-top:0px;margin-bottom:10px;\" align=\"start\"\u003eAPPLICATIONS\u003c\/h4\u003e\n\u003cdiv style=\"font-family:roboto, -webkit-pictograph;font-size:16px;font-weight:400;letter-spacing:normal;text-align:start;white-space:normal;color:rgb(83, 83, 83);background-color:rgb(245, 245, 245);border-bottom:1px solid rgb(201, 201, 201);box-sizing:border-box;padding-bottom:20px;margin-bottom:20px;\" class=\"desCon\" align=\"start\"\u003e \n \u003cp style=\"text-align:center;margin:0px 0px 10px;box-sizing:border-box;margin:0px 0px 10px;\" align=\"center\"\u003e\u003cimg style=\"border:0px;max-width:100%;box-sizing:border-box;\" title=\"Applications of LattePanda Mu x86 compute module - AI Interaction Robot and Handheld Device\" src=\"https:\/\/ae01.alicdn.com\/kf\/S39a8c326c91241cead0d32610e84dd10I.jpg\" slate-data-type=\"image\" data-src=\"https:\/\/ae01.alicdn.com\/kf\/S39a8c326c91241cead0d32610e84dd10I.jpg\"\u003e\u003c\/p\u003e \n\u003c\/div\u003e\n\u003ch4 style=\"font-family:roboto, -webkit-pictograph;font-size:24px;font-weight:700;letter-spacing:normal;line-height:1.1;text-align:start;white-space:normal;color:rgb(49, 49, 49);background-color:rgb(245, 245, 245);box-sizing:border-box;margin-top:0px;margin-bottom:10px;\" align=\"start\"\u003eSPECIFICATION\u003c\/h4\u003e\n\u003cdiv style=\"font-family:roboto, -webkit-pictograph;font-size:16px;font-weight:400;letter-spacing:normal;text-align:start;white-space:normal;color:rgb(83, 83, 83);background-color:rgb(245, 245, 245);border-bottom:1px solid rgb(201, 201, 201);box-sizing:border-box;padding-bottom:20px;margin-bottom:20px;\" class=\"desCon\" align=\"start\"\u003e \n \u003cp\u003eProcessor: Intel Processor N100 4 Cores up to 3.4GHz\u003c\/p\u003e \n \u003cp\u003eMemory: LPDDR5 4800MT\/s 8GB with IBECC supported\u003c\/p\u003e \n \u003cp\u003eStorage: eMMC 5.1 64GB\u003c\/p\u003e \n \u003cp\u003eDisplay: 3 Ouputs; Max Resolution 4096 x 2160@60Hz\u003c\/p\u003e \n \u003cp\u003eI\/O\u003cbr\u003e         PCIe 3.0: up 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