{"title":"Cloud Ninjas Workstations for Photogrammetry","description":"\u003cdiv class=\"seo-sections\"\u003e\n \u003csection class=\"seo-section fade-in\"\u003e\n \u003cdiv class=\"seo-content\"\u003e\n \u003ch2\u003ePrecision Workstations for 3D Capture \u0026amp; Photogrammetry\u003c\/h2\u003e\n \u003cp\u003e\n Transform images into detailed 3D models with workstations built for photogrammetry workflows and high-resolution image processing. Designed to handle massive datasets and complex reconstruction algorithms, these systems deliver fast processing, accurate results, and reliable performance for professionals capturing the world in 3D.\n \u003c\/p\u003e\n \u003c\/div\u003e\n \u003cdiv class=\"seo-image\"\u003e\n \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Drone_or_camera-captured_aerial_images_being_processed_into_3D_models.png?v=1774450485\" alt=\"Drone or camera-captured aerial images being processed into 3D models\" width=\"700px\" height=\"auto\" loading=\"lazy\"\u003e\n \u003c\/div\u003e\n \u003c\/section\u003e\n\n \u003csection class=\"seo-section fade-in\"\u003e\n \u003cdiv class=\"seo-content\"\u003e\n \u003ch2\u003eFuture-Ready Systems for Large-Scale Photogrammetry Projects\u003c\/h2\u003e\n \u003cp\u003e\n Handle massive datasets, LiDAR scans, and high-resolution imagery with systems engineered for scalability and long-term performance. These workstations ensure efficient data processing and responsiveness, allowing teams to keep pace with growing data demands and evolving project complexity.\n \u003c\/p\u003e\n \u003c\/div\u003e\n \u003cdiv class=\"seo-image\"\u003e\n \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Multi-window_photogrammetry_workflow_showing_images_point_clouds_and_final_model.webp?v=1774450645\" alt=\"Multi-window photogrammetry workflow showing images, point clouds, and final model\" width=\"600px\" height=\"auto\" loading=\"lazy\"\u003e\n \u003c\/div\u003e\n \u003c\/section\u003e\n\n \u003csection class=\"seo-section fade-in\"\u003e\n \u003cdiv class=\"seo-content\"\u003e\n \u003ch2\u003eAdvanced Computing for High-Resolution 3D Reconstruction\u003c\/h2\u003e\n \u003cp\u003e\n Maximize productivity with systems designed for CPU- and GPU-intensive photogrammetry tasks, including dense point cloud generation, 3D modeling, and texture mapping. With fast storage, powerful processors, and ample memory, these workstations deliver the speed, accuracy, and reliability professionals need for mission-critical reconstruction projects.\n \u003c\/p\u003e\n \u003c\/div\u003e\n \u003cdiv class=\"seo-image\"\u003e\n \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Close-up_of_high-performance_GPU_rendering_a_dense_point_cloud.webp?v=1774450748\" alt=\"Close-up of high-performance GPU rendering a dense point cloud\" width=\"600px\" height=\"auto\" loading=\"lazy\"\u003e\n \u003c\/div\u003e\n \u003c\/section\u003e\n\n \u003csection class=\"seo-section fade-in\"\u003e\n \u003cdiv class=\"seo-content\"\u003e\n \u003ch2\u003eSeamless Performance Across Photogrammetry Pipelines\u003c\/h2\u003e\n \u003cp\u003e\n From image capture to 3D modeling and analysis, these workstations are optimized for end-to-end photogrammetry workflows. Professionals can process, refine, and visualize complex models without interruptions, ensuring accuracy and efficiency in every project.\n \u003c\/p\u003e\n \u003c\/div\u003e\n \u003cdiv class=\"seo-image\"\u003e\n \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Workstation_showing_photogrammetry_software_processing_a_large_dataset.webp?v=1774450811\" alt=\"Workstation showing photogrammetry software processing a large dataset.\" height=\"auto\" width=\"600px\" loading=\"lazy\"\u003e\n \u003c\/div\u003e\n \u003c\/section\u003e\n\u003c\/div\u003e\n","products":[{"product_id":"cloud-ninjas-workstations-for-pix4dmatic-large-map-edition","title":"Cloud Ninjas Workstations for Pix4Dmatic Large Map Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n\u003cdiv id=\"cpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas Pix4Dmatic Large Map Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eThe CPU is a key component in a Pix4D workstation, as many photogrammetry processing stages rely heavily on multi-core performance. Higher core counts significantly reduce processing times, while strong single-core performance improves interactive tasks and project management, making CPU selection critical for Pix4D performance.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"cpu-compatibility-table\"\u003e\n\u003ctable class=\"data-table\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCPU\u003c\/th\u003e\n\u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n\u003cth\u003eBase Clock\u003c\/th\u003e\n\u003cth\u003eTurbo Clock\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7965WX\u003c\/td\u003e\n\u003ctd\u003e24C\/48T\u003c\/td\u003e\n\u003ctd\u003e4.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.30 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7975WX\u003c\/td\u003e\n\u003ctd\u003e32C\/64T\u003c\/td\u003e\n\u003ctd\u003e4.00 GHz\u003c\/td\u003e\n\u003ctd\u003e5.30 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7985WX\u003c\/td\u003e\n\u003ctd\u003e64C\/128T\u003c\/td\u003e\n\u003ctd\u003e3.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.10 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7995WX\u003c\/td\u003e\n\u003ctd\u003e96C\/192T\u003c\/td\u003e\n\u003ctd\u003e2.50 GHz\u003c\/td\u003e\n\u003ctd\u003e5.10 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9965WX\u003c\/td\u003e\n\u003ctd\u003e24C\/48T\u003c\/td\u003e\n\u003ctd\u003e4.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9975WX\u003c\/td\u003e\n\u003ctd\u003e32C\/64T\u003c\/td\u003e\n\u003ctd\u003e4.00 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9985WX\u003c\/td\u003e\n\u003ctd\u003e64C\/128T\u003c\/td\u003e\n\u003ctd\u003e3.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9995WX\u003c\/td\u003e\n\u003ctd\u003e96C\/192T\u003c\/td\u003e\n\u003ctd\u003e2.50 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"subsection gpu-subsection\"\u003e\n\u003cdiv id=\"gpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas Pix4Dmatic Large Map Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eThe GPU accelerates several Pix4D processing steps, particularly during dense reconstruction and visualization. A modern GPU with sufficient memory improves performance and stability when working with high-resolution imagery and large datasets, making GPU capability an important factor for efficient Pix4D photogrammetry workflows.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"gpu-compatibility-table\"\u003e\n\u003ctable class=\"data-table\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eGPU\u003c\/th\u003e\n\u003cth\u003eVRAM\u003c\/th\u003e\n\u003cth\u003eBase Clock\u003c\/th\u003e\n\u003cth\u003eBoost Clock\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n\u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2617 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n\u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2280 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n\u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2377 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n\u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2407 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n\u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2407 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e24GB GGDR7\u003c\/td\u003e\n \u003ctd\u003e1590 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1875 MHz\u003c\/td\u003e\n\u003ctd\u003e2617 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2452 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n\u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2512 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2572 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n\u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n\u003ctd\u003e1462 MHz\u003c\/td\u003e\n\u003ctd\u003e1500 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n\u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n\u003ctd\u003e1762 MHz\u003c\/td\u003e\n\u003ctd\u003e1500 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Iron Bull","offer_id":42070933307438,"sku":"Cloud Ninjas WATRG-4N8S-3G-Large-Map-Edition-Pix4D Pix4Dmatic","price":2139.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WATRG-4N8S-3G-8.jpg?v=1771955073"},{"product_id":"cloud-ninjas-workstations-for-epic-games-realityscan-large-project-edition","title":"Cloud Ninjas Workstations for Epic Games RealityScan Large Project Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n\u003cdiv id=\"cpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas RealityScan Large Project Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eThe CPU plays a significant role in a RealityScan workstation, handling image preprocessing, alignment, and data management. Strong multi-core performance improves processing efficiency, while good single-core speed enhances responsiveness during interactive tasks, making CPU selection an important factor for overall RealityScan performance.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"cpu-compatibility-table\"\u003e\n\u003ctable class=\"data-table\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCPU\u003c\/th\u003e\n\u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n\u003cth\u003eBase Clock\u003c\/th\u003e\n\u003cth\u003eTurbo Clock\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7965WX\u003c\/td\u003e\n\u003ctd\u003e24C\/48T\u003c\/td\u003e\n\u003ctd\u003e4.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.30 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7975WX\u003c\/td\u003e\n\u003ctd\u003e32C\/64T\u003c\/td\u003e\n\u003ctd\u003e4.00 GHz\u003c\/td\u003e\n\u003ctd\u003e5.30 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7985WX\u003c\/td\u003e\n\u003ctd\u003e64C\/128T\u003c\/td\u003e\n\u003ctd\u003e3.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.10 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 7995WX\u003c\/td\u003e\n\u003ctd\u003e96C\/192T\u003c\/td\u003e\n\u003ctd\u003e2.50 GHz\u003c\/td\u003e\n\u003ctd\u003e5.10 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9965WX\u003c\/td\u003e\n\u003ctd\u003e24C\/48T\u003c\/td\u003e\n\u003ctd\u003e4.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9975WX\u003c\/td\u003e\n\u003ctd\u003e32C\/64T\u003c\/td\u003e\n\u003ctd\u003e4.00 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9985WX\u003c\/td\u003e\n\u003ctd\u003e64C\/128T\u003c\/td\u003e\n\u003ctd\u003e3.20 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAMD Ryzen Threadripper PRO 9995WX\u003c\/td\u003e\n\u003ctd\u003e96C\/192T\u003c\/td\u003e\n\u003ctd\u003e2.50 GHz\u003c\/td\u003e\n\u003ctd\u003e5.40 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"subsection gpu-subsection\"\u003e\n\u003cdiv id=\"gpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas RealityScan Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eThe GPU accelerates reconstruction, texturing, and real-time visualization in RealityScan workflows. A modern GPU with sufficient memory improves processing speed and stability when working with high-resolution images and detailed scans, making GPU capability essential for efficient RealityScan photogrammetry performance.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"gpu-compatibility-table\"\u003e\n\u003ctable class=\"data-table\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eGPU\u003c\/th\u003e\n\u003cth\u003eVRAM\u003c\/th\u003e\n\u003cth\u003eBase Clock\u003c\/th\u003e\n\u003cth\u003eBoost Clock\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n\u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2617 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n\u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2280 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n\u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2377 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n\u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e2407 MHz\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e24GB GGDR7\u003c\/td\u003e\n \u003ctd\u003e1590 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n\u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2407 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1875 MHz\u003c\/td\u003e\n\u003ctd\u003e2617 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2452 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n\u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2512 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n\u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\u003ctd\u003e2572 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n\u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n\u003ctd\u003e1462 MHz\u003c\/td\u003e\n\u003ctd\u003e1500 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n\u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n\u003ctd\u003e1762 MHz\u003c\/td\u003e\n\u003ctd\u003e1500 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Iron Bull","offer_id":42072645107758,"sku":"Cloud Ninjas WATRG-4N8S-3G-Large-Project-Edition-Epic Games RealityScan","price":2139.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WATRG-4N8S-3G-8.jpg?v=1771955073"},{"product_id":"cloud-ninjas-workstations-for-pix4dmatic-models-small-maps-edition","title":"Cloud Ninjas Workstations for Pix4Dmatic Models \u0026 Small Maps Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n\u003cdiv id=\"cpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' Models \u0026amp; Small Maps Edition Pix4Dmatic Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003ePix4Dmatic utilizes the CPU heavily during image alignment, preprocessing, and portions of the reconstruction pipeline. Multi-threading and higher core counts significantly improve throughput in these stages, while strong single-core performance helps maintain responsiveness and coordination efficiency. A modern multi-core CPU ensures the workstation can process image sets efficiently while supporting parallel photogrammetry tasks.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285T\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e1.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285K\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e3.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265T\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e1.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265KF\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265K\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265F\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245KF\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245K\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235T\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e2.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225F\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"subsection gpu-subsection\"\u003e\n\u003cdiv id=\"gpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' Models \u0026amp; Small Maps Edition Pix4Dmatic Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003ePix4Dmatic leverages GPU acceleration extensively during point cloud densification and certain reconstruction stages. A capable professional GPU improves processing speed and reduces total project time, particularly when working with higher image counts. Adequate VRAM is important for handling dense reconstructions and larger textures. While the CPU remains important for early pipeline stages, a well-matched GPU significantly accelerates the most compute-intensive photogrammetry workloads.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e24GB GGDR7\u003c\/td\u003e\n \u003ctd\u003e1590 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e \n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Arctic Falcon Air Cooled","offer_id":42086356647982,"sku":"Cloud Ninjas WIUG-3N4S-1G-A-AC-Models-Small-Maps-Edition-Pix4Dmatic","price":1169.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_Mini-WIUG-3N4S-1G-A-1-AC.jpg?v=1771954168"},{"product_id":"cloud-ninjas-workstations-for-agisoft-metashape-intel-ultra-edition","title":"Cloud Ninjas Workstations for Agisoft Metashape Intel Ultra Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n\u003cdiv id=\"cpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' Intel Ultra Edition Enscape Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eEnscape relies on the CPU for scene preparation, geometry processing, and coordination with host applications such as CAD and BIM platforms. The Standard Edition workstation’s high-frequency multi-core processor ensures responsive scene updates, efficient data handling, and smooth operation when working with large architectural models and live design changes.\n\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285T\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e1.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285K\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e3.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265T\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e1.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265KF\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265K\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265F\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245KF\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245K\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235T\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e2.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225F\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"subsection gpu-subsection\"\u003e\n\u003cdiv id=\"gpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' Intel Ultra Edition Enscape Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eEnscape is primarily GPU-driven for real-time ray tracing, lighting, reflections, and immersive walkthrough performance. The Standard Edition workstation’s professional GPU with ample VRAM delivers smooth frame rates, high-quality real-time rendering, and strong performance with complex scenes and high-resolution displays, enabling fluid client presentations and interactive design visualization.\n\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n\t \u003ctr\u003e\n\t \u003ctd\u003eNVIDIA RTX PRO 4000 Blackwell\u003c\/td\u003e\n\t \u003ctd\u003e24GB GGDR7\u003c\/td\u003e\n\t\t\u003ctd\u003e1590 MHz\u003c\/td\u003e\n\t\t\u003ctd\u003e1750 MHz\u003c\/td\u003e\n\t\u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Neon Fox Liquid Cooled","offer_id":42109786685486,"sku":"Cloud Ninjas WIUG-2N2S-1G-LC-Intel-Ultra-Edition-Metashape","price":1809.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WIUU-5N4S-2G_Liquid_Cooled.jpg?v=1776692291"},{"product_id":"cloud-ninjas-workstations-for-epic-games-realityscan-standard-edition","title":"Cloud Ninjas Workstations for Epic Games RealityScan Standard Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n\u003cdiv id=\"cpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas's Standard Edition RealityScan Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eRealityScan benefits from strong multi-core CPU performance for image alignment, reconstruction calculations, and project management tasks. The Standard Edition workstation’s high-frequency multi-core processor ensures efficient processing of large photo sets while maintaining responsive system performance during heavy computational workloads.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9700X\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e3.80 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9800X3D\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e4.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X3D\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X3D\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"subsection gpu-subsection\"\u003e\n\u003cdiv id=\"gpu-subsection-toggle\" class=\"sub-section-head\"\u003e\u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas's Standard Edition RealitScan Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eRealityScan leverages GPU acceleration for depth map generation, mesh processing, and real-time visualization. The Standard Edition workstation’s professional GPU with ample VRAM significantly improves processing speed, shortens reconstruction times, and enables smooth interaction with dense point clouds and high-resolution meshes, making the GPU a key driver of performance in modern photogrammetry workflows.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"table-section\"\u003e\n\u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e24GB GGDR7\u003c\/td\u003e\n \u003ctd\u003e1590 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Steel Wolf Liquid Cooled","offer_id":42120748793902,"sku":"Cloud Ninjas WARU-4N4S-2G-LC-Standard-Edition-RealityScan","price":1929.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WARU-4N4S-2G_Liquid_Cooled_1.jpg?v=1775674169"},{"product_id":"cloud-ninjas-workstations-for-3df-zephyr-threadripper-edition","title":"Cloud Ninjas Workstations for 3DF Zephyr Threadripper Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' 3DF Zephyr Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance plays a major role in image alignment, sparse point cloud generation, and overall pipeline management in 3DF Zephyr. The AMD Ryzen Threadripper PRO 7995WX delivers exceptional multi-core and multi-threaded performance, enabling faster processing of large datasets and improved efficiency in complex reconstruction workflows. Strong parallel performance is especially beneficial for handling high-volume image sets and large-scale projects.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7965WX\u003c\/td\u003e\n \u003ctd\u003e24C\/48T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7975WX\u003c\/td\u003e\n \u003ctd\u003e32C\/64T\u003c\/td\u003e\n \u003ctd\u003e4.00 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7985WX\u003c\/td\u003e\n \u003ctd\u003e64C\/128T\u003c\/td\u003e\n \u003ctd\u003e3.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7995WX\u003c\/td\u003e\n \u003ctd\u003e96C\/192T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9965WX\u003c\/td\u003e\n \u003ctd\u003e24C\/48T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9975WX\u003c\/td\u003e\n \u003ctd\u003e32C\/64T\u003c\/td\u003e\n \u003ctd\u003e4.00 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9985WX\u003c\/td\u003e\n \u003ctd\u003e64C\/128T\u003c\/td\u003e\n \u003ctd\u003e3.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9995WX\u003c\/td\u003e\n \u003ctd\u003e96C\/192T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' 3DF Zephyr Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eGPU acceleration is a key driver of performance in 3DF Zephyr, particularly during dense point cloud generation and mesh creation. An RTX PRO 6000 Max-Q Edition with 96GB of VRAM enables processing of significantly larger datasets without needing to reduce detail or simplify geometry. Despite its optimized power profile, it delivers notable performance gains over previous generations, improving real-world reconstruction speeds. The blower-style cooling design also makes it ideal for multi-GPU configurations, allowing professionals to scale performance by deploying multiple GPUs for dramatically faster processing in advanced photogrammetry workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Mythical Dragon","offer_id":42254665482286,"sku":"Cloud Ninjas WATRU-6N4S-4G-Threadripper-Edition-3DF Zephyr","price":2999.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/63e5ed60-364b-435d-aa2c-4cdaefce7fe9.jpg?v=1771955098"},{"product_id":"cloud-ninjas-workstations-for-autodesk-recap-intel-edition","title":"Cloud Ninjas Workstations for Autodesk ReCap Intel Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' ReCap Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance is a key factor in Autodesk ReCap Pro. The Intel Core Ultra 9 285K delivers strong single-core performance for responsive navigation and CAD-like interaction, while its multi-core architecture accelerates photogrammetry, indexing, and scan registration tasks. This balance prevents bottlenecks during heavy processing and ensures efficient handling of complex datasets.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285T\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e1.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285K\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e3.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265T\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e1.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265KF\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265K\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265F\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245KF\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245K\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235T\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e2.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225F\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' ReCap Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU performance is essential for smooth visualization of dense point clouds in Autodesk ReCap Pro. An RTX PRO 4500 Blackwell GPU provides the VRAM and compute capability needed to render large datasets with fluid navigation and minimal lag. While not the primary driver of processing tasks, a professional-grade GPU ensures stable viewport performance and reliable operation in demanding visualization workflows.\u003c\/p\u003e\n\n\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Steel Wolf Air Cooled","offer_id":42254713061422,"sku":"Cloud Ninjas WARU-4N4S-2G-LC-Standard-Edition-RealityScan","price":1169.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WARU-4N4S-2G-8.jpg?v=1771954998"},{"product_id":"cloud-ninjas-workstations-for-correlator3d-ryzen-edition","title":"Cloud Ninjas Workstations for Correlator3D Ryzen Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' Correlator3D\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance plays a crucial role in the pre-processing and finalization stages of Correlator3D. The AMD Ryzen 9 9950X3D features 16 high-performance cores that accelerate aerial triangulation and bundle adjustment tasks through multi-threading. Its 3D V-Cache technology reduces latency when handling complex geospatial datasets, improving responsiveness during data preparation. Built on a modern platform, it also provides long-term upgrade flexibility for evolving professional workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9700X\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e3.80 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9800X3D\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e4.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X3D\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X3D\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' Correlator3D\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003e\n GPU acceleration is the primary performance driver in Correlator3D. An RTX 5090 with 32GB of GDDR7 VRAM eliminates one of the biggest bottlenecks in photogrammetry: VRAM limitations, allowing processing of extremely large datasets, including projects exceeding 10,000 images. Its massive core count and high memory bandwidth ensure efficient parallel processing of dense point clouds, textures, and 3D models, significantly reducing processing times and enabling high-fidelity results in professional geospatial workflows.\n\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Steel Wolf Air Cooled","offer_id":42255351349294,"sku":"Cloud Ninjas WARU-4N4S-2G-AC-Ryzen-Edition-Correlator3D","price":1939.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WARU-4N4S-2G-8.jpg?v=1771954998"},{"product_id":"cloud-ninjas-workstations-for-arcgis-reality-threadripper-edition","title":"Cloud Ninjas Workstations for ArcGIS Reality Threadripper Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' ArcGIS Reality Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance must balance multi-threaded processing with strong single-core speed in ArcGIS Reality. The AMD Ryzen Threadripper PRO 7975WX delivers high core counts for accelerating SURE-based photogrammetry tasks such as aerial triangulation and dense reconstruction, while maintaining strong per-core clock speeds for responsive map drawing and interactive editing within ArcGIS Pro. This balance is essential for efficient, end-to-end geospatial workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7965WX\u003c\/td\u003e\n \u003ctd\u003e24C\/48T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7975WX\u003c\/td\u003e\n \u003ctd\u003e32C\/64T\u003c\/td\u003e\n \u003ctd\u003e4.00 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7985WX\u003c\/td\u003e\n \u003ctd\u003e64C\/128T\u003c\/td\u003e\n \u003ctd\u003e3.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 7995WX\u003c\/td\u003e\n \u003ctd\u003e96C\/192T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9965WX\u003c\/td\u003e\n \u003ctd\u003e24C\/48T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9975WX\u003c\/td\u003e\n \u003ctd\u003e32C\/64T\u003c\/td\u003e\n \u003ctd\u003e4.00 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9985WX\u003c\/td\u003e\n \u003ctd\u003e64C\/128T\u003c\/td\u003e\n \u003ctd\u003e3.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen Threadripper PRO 9995WX\u003c\/td\u003e\n \u003ctd\u003e96C\/192T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' ArcGIS Reality Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eGPU acceleration is critical in ArcGIS Reality, particularly for CUDA-based spatial analysis and 3D reconstruction. An RTX PRO 4500 Blackwell GPU provides the compute performance and VRAM capacity required to handle complex 3D scenes and high-resolution imagery without bottlenecks. Adequate VRAM ensures smooth processing of large datasets, while NVIDIA GPU architecture enables full support for advanced geospatial and deep learning workflows\u003c\/p\u003e\n\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Iron Bull","offer_id":42255419637806,"sku":"Cloud Ninjas WATRG-4N8S-3G-Threadripper-Edition-ArcGIS Reality","price":2139.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WATRG-4N8S-3G-8.jpg?v=1771955073"},{"product_id":"cloud-ninjas-workstations-for-photomodeler-intel-edition","title":"Cloud Ninjas Workstations for PhotoModeler Intel Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' PhotoModeler\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance plays a key role in image alignment, referencing, and project setup within PhotoModeler. The Intel Core Ultra 9 285K delivers strong single-core performance for responsive interaction and precise control, while its multi-core architecture accelerates batch processing, point calculations, and data preparation, improving overall efficiency in professional workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285T\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e1.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.40 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285K\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e3.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 9 285\u003c\/td\u003e\n \u003ctd\u003e24C\/24T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265T\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e1.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265KF\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265K\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e3.90 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265F\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 7 265\u003c\/td\u003e\n \u003ctd\u003e20C\/20T\u003c\/td\u003e\n \u003ctd\u003e2.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.30 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245KF\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245K\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e4.20 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 245\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.50 GHz\u003c\/td\u003e\n \u003ctd\u003e5.10 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235T\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e2.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 235\u003c\/td\u003e\n \u003ctd\u003e14C\/14T\u003c\/td\u003e\n \u003ctd\u003e3.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.00 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225F\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Ultra 5 225\u003c\/td\u003e\n \u003ctd\u003e10C\/10T\u003c\/td\u003e\n \u003ctd\u003e3.30 GHz\u003c\/td\u003e\n \u003ctd\u003e4.90 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications for Cloud Ninjas' PhotoModeler\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration enhances processing speed and visualization performance in PhotoModeler. A GeForce RTX 5090 with high VRAM capacity enables faster dense reconstruction, smoother rendering of complex models, and efficient handling of high-resolution textures. This significantly reduces processing times and improves responsiveness when working with detailed 3D photogrammetry projects.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Neon Fox Liquid Cooled","offer_id":42255467184174,"sku":"Cloud Ninjas WIUU-5N4S-2G-LC-Intel-Edition-PhotoModeler","price":1809.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WIUU-5N4S-2G_Liquid_Cooled.jpg?v=1776692291"},{"product_id":"cloud-ninjas-workstations-for-alicevision-ryzen-edition","title":"Cloud Ninjas Workstations for AliceVision Ryzen Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' Workstation for AliceVision\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance plays a major role in feature extraction, matching, and structure-from-motion stages. The AMD Ryzen 9 9900X delivers strong single-core performance for responsive processing and excellent multi-core throughput for parallelizable stages. This balance improves overall pipeline efficiency, particularly during image alignment and reconstruction phases in photogrammetry workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9700X\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e3.80 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9800X3D\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e4.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X3D\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X3D\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications Cloud Ninjas' Workstation for AliceVision\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration is the most critical performance factor in AliceVision. A GeForce RTX 5090 provides extremely high CUDA core throughput and large VRAM capacity, enabling faster depth map computation, mesh reconstruction, and texture generation. High VRAM is especially important for large image sets, preventing out-of-memory errors and allowing smoother processing of high-resolution photogrammetry datasets.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Steel Wolf Liquid Cooled","offer_id":42283887263790,"sku":"Cloud Ninjas WARU-4N4S-2G-LC-Ryzen-Edition-AliceVision","price":1929.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WARU-4N4S-2G_Liquid_Cooled_1.jpg?v=1775674169"},{"product_id":"cloud-ninjas-workstations-for-3d-survey-ryzen-edition","title":"Cloud Ninjas Workstations for 3D Survey Ryzen Edition","description":"\u003cdiv class=\"subsection cpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"cpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eProcessor Specifications for Cloud Ninjas' Workstation for 3D Survey\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eCPU performance is critical in 3Dsurvey, particularly during image alignment, feature matching, and reconstruction stages. The AMD Ryzen 9 9900X delivers strong single-core performance for responsive processing and excellent multi-core throughput for parallel workloads. While enterprise-scale projects benefit from higher-core workstation CPUs, this configuration provides a balanced foundation for professional drone mapping workflows.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n \u003cdiv class=\"table-section\"\u003e\n \u003cdiv class=\"cpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eCPU\u003c\/th\u003e\n \u003cth\u003eCores \u0026amp; Threads\u003c\/th\u003e\n \u003cth\u003eBase Clock\u003c\/th\u003e\n \u003cth\u003eTurbo Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9700X\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e3.80 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 7 9800X3D\u003c\/td\u003e\n \u003ctd\u003e8C\/16T\u003c\/td\u003e\n \u003ctd\u003e4.70 GHz\u003c\/td\u003e\n \u003ctd\u003e5.20 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.60 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9900X3D\u003c\/td\u003e\n \u003ctd\u003e12C\/24T\u003c\/td\u003e\n \u003ctd\u003e4.40 GHz\u003c\/td\u003e\n \u003ctd\u003e5.50 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAMD Ryzen 9 9950X3D\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e4.30 GHz\u003c\/td\u003e\n \u003ctd\u003e5.70 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \u003c\/div\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection gpu-subsection\"\u003e\n \u003cdiv class=\"sub-section-head\" id=\"gpu-subsection-toggle\"\u003e\n \u003cspan class=\"sub-section-tl\"\u003eGraphics Card Specifications Cloud Ninjas' Workstation for 3D Survey\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration significantly improves performance in 3Dsurvey, especially for dense reconstruction, point cloud generation, and dataset visualization. A GeForce RTX 5090 provides extremely high CUDA performance and large VRAM capacity, enabling efficient processing of high-resolution imagery and large survey areas. Adequate GPU memory ensures smoother handling of complex reconstructions and reduces bottlenecks in CUDA-accelerated pipeline stages.\u003c\/p\u003e\n \u003c\/div\u003e\n\n \u003c\/div\u003e\n\n \u003cdiv class=\"table-section\"\u003e\n\n \u003cdiv class=\"gpu-compatibility-table\"\u003e\n \u003ctable class=\"data-table\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth\u003eGPU\u003c\/th\u003e\n \u003cth\u003eVRAM\u003c\/th\u003e\n \u003cth\u003eGPU Clock\u003c\/th\u003e\n \u003cth\u003eMemory Clock\u003c\/th\u003e\n \u003c\/tr\u003e\n \u003c\/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 6000 Blackwell Max Q Workstation Edition\u003c\/td\u003e\n \u003ctd\u003e96GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2280 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 5000 Blackwell\u003c\/td\u003e\n \u003ctd\u003e48GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2377 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX PRO 4500 Blackwell\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA 6000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2505 MHz\u003c\/td\u003e\n \u003ctd\u003e2500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5090\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2407 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e32GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2550 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4500 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e24GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2580 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 4000 ADA Generation\u003c\/td\u003e\n \u003ctd\u003e20GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e2175 MHz\u003c\/td\u003e\n \u003ctd\u003e2250 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5080\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1875 MHz\u003c\/td\u003e\n \u003ctd\u003e2617 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2452 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5070\u003c\/td\u003e\n \u003ctd\u003e12GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2512 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX 5060 Ti\u003c\/td\u003e\n \u003ctd\u003e16GB GDDR7\u003c\/td\u003e\n \u003ctd\u003e1750 MHz\u003c\/td\u003e\n \u003ctd\u003e2572 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A1000\u003c\/td\u003e\n \u003ctd\u003e8GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1462 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eNVIDIA RTX A400\u003c\/td\u003e\n \u003ctd\u003e4GB GDDR6\u003c\/td\u003e\n \u003ctd\u003e1762 MHz\u003c\/td\u003e\n \u003ctd\u003e1500 MHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\n \n \u003c\/div\u003e\n \u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Steel Wolf Liquid Cooled","offer_id":42283999428654,"sku":"Cloud Ninjas WARU-4N4S-2G-LC-Ryzen-Edition-3D Survey","price":1929.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WARU-4N4S-2G_Liquid_Cooled_1.jpg?v=1775674169"}],"url":"https:\/\/cloudninjas.com\/collections\/cloud-ninjas-workstations-for-photogrammetry\/sw-size-mid.oembed","provider":"Cloud Ninjas","version":"1.0","type":"link"}