{"id":697,"date":"2026-07-07T13:07:42","date_gmt":"2026-07-07T02:07:42","guid":{"rendered":"https:\/\/prology.net\/blog\/?p=697"},"modified":"2026-07-07T15:15:55","modified_gmt":"2026-07-07T04:15:55","slug":"msi-edgexpert-ms-c931-unboxing","status":"publish","type":"post","link":"https:\/\/prology.net\/blog\/msi-edgexpert-ms-c931-unboxing\/","title":{"rendered":"MSI EdgeXpert MS-C931 Unboxing &amp; First Look | Prology"},"content":{"rendered":"<h1><strong>MSI EdgeXpert MS-C931 Unboxing: A 1-PetaFLOP &#8220;AI Supercomputer&#8221; That Weighs 1.2 kg<\/strong><\/h1>\n<article>\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-698\" src=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-1024x1024.jpg\" alt=\"Front view of the MSI EdgeXpert MS-C931 with its honeycomb mesh grille\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-1024x1024.jpg 1024w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-300x300.jpg 300w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-150x150.jpg 150w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-768x768.jpg 768w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-1536x1536.jpg 1536w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-front-2048x2048.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption style=\"padding-left: 160px;\"><em>The MSI EdgeXpert MS-C931 \u2014 151 x 151 x 52 mm, 1.2 kg. Photo: Prology.<\/em><\/figcaption><\/figure>\n<p>The <a href=\"https:\/\/prology.net\/au\/catalogsearch\/result\/?q=MSI+EdgeXpert+MS-C931\">MSI EdgeXpert MS-C931<\/a> just arrived at the <a href=\"https:\/\/prology.net\/au\">Prology<\/a> warehouse, and the first surprise comes before the box is even open: it barely weighs anything. Inside is a machine MSI unapologetically calls an &#8220;AI supercomputer&#8221; \u2014 1 petaFLOP of performance, capable of running 200-billion-parameter language models, small enough to hold in one hand. This unboxing walks through the details: the design, the rear port cluster, the silicon inside, and the most interesting accessory on the table \u2014 a 200G cable that turns two of these machines into a cluster.<\/p>\n<h2>What is the MSI EdgeXpert MS-C931?<\/h2>\n<p>The <a href=\"https:\/\/prology.net\/au\/catalogsearch\/result\/?q=MSI+EdgeXpert+MS-C931\">EdgeXpert MS-C931<\/a> is MSI&#8217;s entry in the &#8220;personal AI supercomputer&#8221; wave NVIDIA started with the DGX Spark platform. Like its platform siblings from other vendors, it&#8217;s built around the NVIDIA GB10 Grace Blackwell Superchip: a 20-core Arm CPU (10 high-performance Cortex-X925 cores plus 10 Cortex-A725 cores) paired with a Blackwell-architecture GPU on a single chip, linked by NVLink-C2C \u2014 a CPU-GPU interconnect MSI rates at several times the bandwidth of PCIe 5.0.<\/p>\n<p>Notably, MSI files the MS-C931 under its industrial PC (IPC) division rather than consumer hardware. That positioning says a lot about the intended buyer: enterprise AI teams, research labs, and universities \u2014 places that need a device to run steadily day after day, not a high-performance toy.<\/p>\n<p>One thing worth clarifying up front: although machines like this often get called &#8220;AI servers,&#8221; the MS-C931 is not a rack server. It&#8217;s a desktop in the true sense \u2014 a local AI development and inference station that sits between an engineer&#8217;s laptop and real server infrastructure.<\/p>\n<h2>Opening the box: what&#8217;s on the table<\/h2>\n<p>The unit that arrived at <a href=\"https:\/\/prology.net\/au\">Prology<\/a> ships with the machine itself and a 240W USB-C power adapter with its cord \u2014 true to the minimalist spirit of DGX Spark devices: plug in power, connect to the network, start working. There&#8217;s no keyboard, mouse, or display in the box, and in practice most users will SSH in from their own laptop rather than sit at the machine.<\/p>\n<p>For this particular order, <a href=\"https:\/\/prology.net\/au\">Prology<\/a> added one accessory that does not come in the standard box: a 0.5 m QSFP56 200G DAC cable. It becomes important at the end of this article, when we get to linking two units into a cluster.<\/p>\n<h2>Design up close: serious, minimal, very &#8220;industrial&#8221;<\/h2>\n<p>Where ASUS went with silver-grey for its GB10 machine, MSI took the opposite road: the MS-C931 is matte black and squared-off, with almost no decoration beyond the MSI logo on the front corner. The one flourish is the honeycomb mesh grille spanning the entire front face \u2014 both the air intake and the only visual personality on an otherwise reserved design.<\/p>\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-699\" src=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-1024x1024.jpg\" alt=\"MSI EdgeXpert MS-C931 seen from a three-quarter angle\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-1024x1024.jpg 1024w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-300x300.jpg 300w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-150x150.jpg 150w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-768x768.jpg 768w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-1536x1536.jpg 1536w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-top-2048x2048.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption style=\"padding-left: 120px;\"><em>Matte black and squared-off \u2014 unmistakably industrial hardware. Photo: Prology.<\/em><\/figcaption><\/figure>\n<p>The measurements: 151 x 151 x 52 mm \u2014 a volume of just 1.19 liters \u2014 at 1.2 kg. For scale, it takes up about as much desk space as a lunchbox and weighs less than most 14-inch laptops. Both sides and the rear carry exhaust vents; air flows from the front honeycomb through to the back, a familiar layout in industrial machines built to run continuously. MSI rates the operating range at 0\u201335\u00b0C with smart fan control.<\/p>\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-701\" src=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-1024x1024.jpg\" alt=\"Side of the MS-C931 showing its exhaust vents\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-1024x1024.jpg 1024w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-300x300.jpg 300w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-150x150.jpg 150w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-768x768.jpg 768w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-1536x1536.jpg 1536w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-right-2048x2048.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption style=\"padding-left: 120px;\"><em>Side exhaust vents \u2014 airflow runs from the front grille to the rear. Photo: Prology.<\/em><\/figcaption><\/figure>\n<p>In hand, the unit feels solid: panels fit tightly, nothing flexes \u2014 the build quality you&#8217;d expect from hardware sold under an IPC catalog.<\/p>\n<h2>The rear panel: a machine room&#8217;s worth of ports<\/h2>\n<p>All of the MS-C931&#8217;s connectivity gathers at the back, and the port density on a 15 cm chassis will make anyone who works with servers look twice:<\/p>\n<ul>\n<li>4x USB 3.2 Type-C at 20Gbps \u2014 one PD-in port takes power from the 240W adapter, one supports PD-out to power external devices, and the ports carry DisplayPort 1.4a video. The machine drives up to 4 independent displays.<\/li>\n<li>1x HDMI 2.1a with multichannel audio.<\/li>\n<li>1x RJ-45 10GbE \u2014 10-gigabit networking built in, no add-in card.<\/li>\n<li>An NVIDIA ConnectX-7 SmartNIC block with 2 QSFP cages at up to 200Gbps \u2014 the most &#8220;data center&#8221; detail on the whole device, with &#8220;ConnectX-7 200G&#8221; printed right on the chassis.<\/li>\n<li>Wi-Fi 7 and Bluetooth 5.4 for wireless.<\/li>\n<\/ul>\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-702\" src=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-1024x1024.jpg\" alt=\"Rear panel of the MS-C931: USB-C 20Gbps, HDMI, 10G LAN, ConnectX-7 200G\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-1024x1024.jpg 1024w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-300x300.jpg 300w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-150x150.jpg 150w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-768x768.jpg 768w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-1536x1536.jpg 1536w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/MSI-underside-2048x2048.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption style=\"padding-left: 120px;\"><em>The rear port cluster \u2014 &#8220;ConnectX-7 200G&#8221; printed on the chassis. Photo: Prology.<\/em><\/figcaption><\/figure>\n<p>For infrastructure people, the ConnectX-7 block alone tells the story: this is the class of network card normally found in the GPU nodes of AI training clusters, here on a desktop machine that runs off USB-C power.<\/p>\n<h2>Inside: the GB10 and the official numbers<\/h2>\n<table style=\"width: 100%; border-collapse: collapse; border: 1px solid #dcdcdc; font-family: Arial,sans-serif; font-size: 16px; margin: 20px 0;\">\n<thead>\n<tr style=\"background: #f5f5f5;\">\n<th style=\"border: 1px solid #dcdcdc; padding: 12px 16px; text-align: left;\">Component<\/th>\n<th style=\"border: 1px solid #dcdcdc; padding: 12px 16px; text-align: left;\">Specification<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Architecture<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">NVIDIA Grace Blackwell GB10<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>CPU<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">20-core Arm (10 Cortex-X925 + 10 Cortex-A725)<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>GPU<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">NVIDIA Blackwell, integrated on the superchip<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>AI Performance<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">1000 AI TOPS (FP4, sparse) \u2248 1 petaFLOP<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Memory<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">128GB LPDDR5x unified, 256-bit bus, 273 GB\/s bandwidth<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Storage<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">M.2 NVMe 1TB or 4TB, self-encrypting, single slot<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Networking<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">10GbE, ConnectX-7 @200Gbps (2 QSFP cages), Wi-Fi 7, BT 5.4<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Display Out<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">HDMI 2.1a + 3\u00d7 DisplayPort 1.4a via USB-C, up to 4 displays<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Power<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">~240W via USB-C, external adapter<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Size \/ Weight<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">151 \u00d7 151 \u00d7 52 mm (1.19L) \/ 1.2 kg<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Operating Temperature<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">0\u201335\u00b0C<\/td>\n<\/tr>\n<tr style=\"background: #fafafa;\">\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\"><strong>Operating System<\/strong><\/td>\n<td style=\"border: 1px solid #dcdcdc; padding: 12px 16px; vertical-align: top;\">NVIDIA DGX OS<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Three numbers deserve a pause. <strong>128GB of unified memory<\/strong> \u2014 shared between CPU and GPU, so AI models aren&#8217;t capped by the 16\u201332GB VRAM ceiling of discrete graphics cards. <strong>273 GB\/s of memory bandwidth<\/strong> \u2014 enough for smooth inference on large models loaded fully into RAM. And the <strong>self-encrypting NVMe drive<\/strong> \u2014 a detail few vendors in this segment highlight, yet one that matters to exactly the buyer this machine targets: businesses that choose local AI precisely to keep their data in the building.<\/p>\n<p>The machine runs NVIDIA DGX OS \u2014 a customized Linux build with NVIDIA&#8217;s full AI software stack preinstalled. Per MSI, models developed on the MS-C931 move to DGX Cloud or NVIDIA-accelerated data centers with minimal code changes. In other words: the same workflow as the big DGX systems, just at desk scale.<\/p>\n<h2>The 200G cable: from one machine to a cluster<\/h2>\n<p>The accessory <a href=\"https:\/\/prology.net\/au\">Prology<\/a> added to this order \u2014 a 0.5 m QSFP56 <a href=\"https:\/\/prology.net\/au\/catalogsearch\/result\/?q=200G+QSFP56+Passive+DAC+Cable+0.5m+ConnectX-7+Technology+NVIDIA+DGX+AI+Cluster\">200G DAC cable<\/a> \u2014 is the key to the DGX Spark platform&#8217;s most valuable trick: joining two machines into a cluster over the ConnectX-7 ports.<\/p>\n<figure><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-714 size-large\" src=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m-1024x1024.jpg\" alt=\"0.5 m QSFP56 200G DAC cable\" width=\"1024\" height=\"1024\" srcset=\"https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m-1024x1024.jpg 1024w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m-300x300.jpg 300w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m-150x150.jpg 150w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m-768x768.jpg 768w, https:\/\/prology.net\/blog\/wp-content\/uploads\/2026\/07\/cable-qsfp-200g-cu0.5m.jpg 1448w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption style=\"padding-left: 80px;\"><em>QSFP56 200G passive DAC, 0.5 m \u2014 used to link two units over ConnectX-7. Photo: Prology.<\/em><\/figcaption><\/figure>\n<p>A single MS-C931 runs models of up to 200 billion parameters. Connect two units with this cable and the two-node cluster handles models of up to 405 billion parameters \u2014 Llama 3.1 405B territory, per MSI and NVIDIA. When demand grows, the upgrade cost is a second machine and one cable, not a forklift replacement. For a business starting its AI journey, that &#8220;buy one, link two&#8221; path takes real risk out of the initial investment.<\/p>\n<h2>Where does the MS-C931 sit among DGX Spark machines?<\/h2>\n<p>Several devices now share the GB10 platform \u2014 NVIDIA&#8217;s own DGX Spark, the ASUS Ascent GX10 that Prology has <a href=\"https:\/\/prology.net\/blog\">covered in detail<\/a>, and versions from other vendors. Their core hardware is identical: same GB10, same 128GB of unified memory, same 1 petaFLOP. The differences live in the details.<\/p>\n<p>Against the ASUS Ascent GX10, the MSI is lighter (1.2 kg vs. 1.48 kg), offers 1TB or 4TB of self-encrypting storage, carries Bluetooth 5.4, and wears industrial matte black instead of silver-grey. The GX10 answers with a middle 2TB option alongside its comparable 10G LAN and ConnectX-7. In day-to-day use the two are near-equivalent \u2014 the choice usually comes down to storage configuration, price at the time of purchase, and which brand your IT team already trusts.<\/p>\n<h2>Who should put one on their desk?<\/h2>\n<p>MSI targets three distinct groups. First, enterprise AI engineers \u2014 fine-tune and run inference locally, then push to the company data center or cloud. Second, education \u2014 universities equipping AI classrooms and labs, where a 1.2 kg device is far easier to manage than a server room. Third, independent developers \u2014 experimenting with models and building local AI assistants without a monthly cloud bill.<\/p>\n<p>What the three share: a need to run large models locally, a premium on data control, and no desire (or budget) to stand up server infrastructure on day one. If your needs stop at calling commercial model APIs \u2014 or at the other extreme, training models from scratch at scale \u2014 this isn&#8217;t your machine yet.<\/p>\n<h2>Frequently asked questions<\/h2>\n<p><strong>Is the MS-C931 a server?<\/strong><br \/>\nNot in the traditional sense. It&#8217;s a desktop AI supercomputer \u2014 a desk-side machine for local AI development and inference. It doesn&#8217;t rack-mount, has no redundant power, and isn&#8217;t designed to replace production servers.<\/p>\n<p><strong>What OS does it run? Can it run Windows?<\/strong><br \/>\nIt runs NVIDIA DGX OS (Linux-based) with the AI software stack preinstalled. It&#8217;s a dedicated AI machine, not a general-purpose PC for Windows.<\/p>\n<p><strong>How large a model can one unit handle?<\/strong><br \/>\nPer MSI: up to 200 billion parameters on a single machine, and up to 405 billion parameters with two units linked over ConnectX-7.<\/p>\n<p><strong>Is power or cooling complicated?<\/strong><br \/>\nNo. It draws ~240W over USB-C from an external adapter \u2014 a normal office outlet is enough. With a 0\u201335\u00b0C operating range and smart fan control, it&#8217;s built for offices and classrooms.<\/p>\n<p><strong>How much does it cost?<\/strong><br \/>\nPricing varies by storage configuration (1TB\/4TB) and market. Contact <a href=\"https:\/\/prology.net\/au\/\">Prology<\/a> for current pricing and availability.<\/p>\n<h2>One black box, one AI roadmap<\/h2>\n<p>What sticks after the unboxing isn&#8217;t any single spec \u2014 it&#8217;s the whole: MSI has packed machine-room compute into a 1.2 kg block of black metal that runs on USB-C power, with an upgrade path that costs exactly one cable. For a business weighing its first investment in on-premise AI infrastructure, the MS-C931 is a hard starting point to ignore. If you&#8217;d like to see the unit in person, compare the 1TB and 4TB configurations, or plan a two-unit setup for larger models, the Prology team is ready to help with your actual workload.<\/p>\n<\/article>\n<p>&nbsp;<\/p>\n<div style=\"display:flex;justify-content:center;align-items:center;gap:24px;margin:32px 0;\">\n<p>    <!-- Facebook --><br \/>\n    <a href=\"https:\/\/www.facebook.com\/prology.net\/\"\n       target=\"_blank\"\n       style=\"display:flex;align-items:center;justify-content:center;width:48px;height:48px;border-radius:50%;text-decoration:none;transition:transform .2s ease;\"><br \/>\n        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"38\" height=\"38\" fill=\"#1877F2\" viewBox=\"0 0 24 24\">\n            <path d=\"M24 12a12 12 0 10-13.88 11.85v-8.39H7.08V12h3.04V9.36c0-3 1.79-4.67 4.53-4.67 1.31 0 2.68.23 2.68.23v2.95h-1.51c-1.49 0-1.95.93-1.95 1.87V12h3.33l-.53 3.46h-2.8v8.39A12 12 0 0024 12z\"\/>\n        <\/svg><br \/>\n    <\/a><\/p>\n<p>    <!-- LinkedIn --><br \/>\n    <a href=\"https:\/\/www.linkedin.com\/company\/100887069\/\" target=\"_blank\" style=\"display:flex;align-items:center;justify-content:center;width:48px;height:48px;border-radius:50%;text-decoration:none;transition:transform .2s ease;\" rel=\"noopener\"><br \/>\n        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"38\" height=\"38\" fill=\"#0A66C2\" viewBox=\"0 0 24 24\">\n            <path d=\"M20.45 20.45h-3.56v-5.57c0-1.33-.02-3.05-1.86-3.05-1.87 0-2.16 1.46-2.16 2.96v5.66H9.31V9h3.42v1.56h.05c.48-.9 1.63-1.85 3.35-1.85 3.58 0 4.24 2.36 4.24 5.43v6.31zM5.34 7.43a2.06 2.06 0 110-4.12 2.06 2.06 0 010 4.12zM7.12 20.45H3.56V9h3.56v11.45z\"\/>\n        <\/svg><br \/>\n    <\/a><\/p>\n<p>    <!-- Website --><br \/>\n    <a href=\"https:\/\/prology.net\/\" target=\"_blank\" style=\"display:flex;align-items:center;justify-content:center;width:48px;height:48px;border-radius:50%;text-decoration:none;transition:transform .2s ease;\"><br \/>\n        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"38\" height=\"38\" fill=\"#2B6DF3\" viewBox=\"0 0 24 24\">\n            <path d=\"M12 2a10 10 0 100 20 10 10 0 000-20zm6.93 9h-3.05a15.9 15.9 0 00-1.2-5A8.03 8.03 0 0118.93 11zM12 4c.83 1.2 1.48 3.02 1.73 5h-3.46C10.52 7.02 11.17 5.2 12 4zM5.07 13h3.05c.1 1.76.52 3.44 1.2 5A8.03 8.03 0 015.07 13zm3.05-2H5.07a8.03 8.03 0 014.25-5 15.9 15.9 0 00-1.2 5zm3.88 9c-.83-1.2-1.48-3.02-1.73-5h3.46c-.25 1.98-.9 3.8-1.73 5zm2.41-2a15.9 15.9 0 001.2-5h3.05a8.03 8.03 0 01-4.25 5z\"\/>\n        <\/svg><br \/>\n    <\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>MSI EdgeXpert MS-C931 Unboxing: A 1-PetaFLOP &#8220;AI Supercomputer&#8221; That Weighs 1.2 kg The MSI EdgeXpert MS-C931 \u2014 151 x 151 x 52\u2026<\/p>\n","protected":false},"author":3,"featured_media":716,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,5],"tags":[34,35],"class_list":["post-697","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-products","tag-edgexpert-34sau","tag-mini-pcs"],"_links":{"self":[{"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/posts\/697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/comments?post=697"}],"version-history":[{"count":11,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/posts\/697\/revisions"}],"predecessor-version":[{"id":715,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/posts\/697\/revisions\/715"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/media\/716"}],"wp:attachment":[{"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/media?parent=697"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/categories?post=697"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prology.net\/blog\/wp-json\/wp\/v2\/tags?post=697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}