{"title":"Cloud Ninjas Workstations for Generative AI","description":"\u003cdiv class=\"seo-sections\"\u003e\n \u003csection class=\"seo-section fade-in\"\u003e\n \u003cdiv class=\"seo-content\"\u003e\n \u003ch2\u003eHigh-Performance Workstations for Generative AI\u003c\/h2\u003e\n \u003cp\u003e\n Unlock the full potential of Stable Diffusion, Topaz Labs, and FLUX.2 with workstations built for AI-driven image generation and enhancement. Designed for GPU-intensive workloads, these systems deliver faster model processing, higher-resolution ouputs, and real-time iteration, making them ideal for creators pushing the boundaries of AI.\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\/ai-art-img.webp?v=1774362616\" alt=\"AI-generated artwork displayed\" 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-Proof Your AI Workflow\u003c\/h2\u003e\n \u003cp\u003e\n Stay ahead in the rapidly evolving world of Generative AI with systems engineered for large models, high VRAM requirements, and continous updates. Whether you are using Topaz Studio Pro or advanced AI pipeplines, these workstations ensure scalability, speed, and long-term performance.\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\/neural_network_img.webp?v=1774362861\" alt=\"Abstract visualization of neural networks or AI processing\" 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 Compatibility Across AI image Tools\u003c\/h2\u003e\n \u003cp\u003e\n From Stable Diffusion to Topaz Labs and FLUX.2, our workstations are optimized for smooth integration across AI-powered creative tools. Experience stable performance, faster batch generation and efficient upscaling allowing you to focus on iteration, creativity, and output quality.\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\/Before-and-after_upscaling_example_using_Topaz_tools.webp?v=1774363467\" alt=\"Before-and-after upscaling example using Topaz tools\" 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\u003eWorkstations Built for AI Creators\u003c\/h2\u003e\n \u003cp\u003e\n Maximize productivity with systems designed for high-performance GPUs, fast storage, and large memory capacity. Perfect for AI creatives, designers, and content creators, these workstations handle real-time generation, high-resolution rendering, and intensive upscaling tasks with ease giving you the power to create without limits.\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\/Ultra-high-resolution_AI-generated_artwork_on_a_large_screen.webp?v=1774363720\" alt=\"Ultra-high-resolution AI-generated artwork on a large screen\" 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-topaz-labs-topaz-studio-intel-xeon-edition","title":"Cloud Ninjas Workstations for Topaz Labs Topaz Studio Intel Xeon 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 Topaz Studio Intel Xeon Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eTopaz Studio benefits from CPUs with strong single-core performance and moderate multi-core counts. Multithreading accelerates batch processing, plugin operations, and file exports, while higher clock speeds improve real-time editing responsiveness.\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 Xeon w5-3525\u003c\/td\u003e\n \u003ctd\u003e16C\/32T\u003c\/td\u003e\n \u003ctd\u003e3.20 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w5-3535X\u003c\/td\u003e\n \u003ctd\u003e20C\/40T\u003c\/td\u003e\n \u003ctd\u003e2.90 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w7-3545\u003c\/td\u003e\n \u003ctd\u003e24C\/48T\u003c\/td\u003e\n \u003ctd\u003e2.70 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w7-3555\u003c\/td\u003e\n \u003ctd\u003e28C\/56T\u003c\/td\u003e\n \u003ctd\u003e2.70 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w7-3565X\u003c\/td\u003e\n \u003ctd\u003e32C\/64T\u003c\/td\u003e\n \u003ctd\u003e2.50 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w9-3575X\u003c\/td\u003e\n \u003ctd\u003e44C\/88T\u003c\/td\u003e\n \u003ctd\u003e2.20 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 GHz\u003c\/td\u003e\n \u003c\/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eIntel Xeon w9-3595X\u003c\/td\u003e\n \u003ctd\u003e60C\/120T\u003c\/td\u003e\n \u003ctd\u003e2.00 GHz\u003c\/td\u003e\n \u003ctd\u003e4.80 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 Topaz Studio Intel Xeon Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eGPU acceleration is critical for Topaz Studio. AI-powered tools rely heavily on GPU cores and VRAM for fast image enhancement. A modern GPU with ample memory significantly improves AI render times, real-time previews, and processing of high-resolution images.\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 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 \n \u003c\/tbody\u003e\n \u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Primal Gorilla","offer_id":42077395157038,"sku":"Cloud Ninjas WIW35U-5N6S-4G-Intel-Xeon-Edition-Topaz Studio","price":2669.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_XL-WIW35U-5N6S-4G-1.jpg?v=1771955570"},{"product_id":"cloud-ninjas-workstations-for-generative-ai-amd-ryzen-edition","title":"Cloud Ninjas Workstations for Generative AI AMD Ryzen 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 Generative AI AMD Ryzen Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eIn Generative AI workflows, the CPU primarily manages data preprocessing, prompt orchestration, tokenization, and pipeline coordination. Strong single-core performance improves responsiveness in scripting and inference control, while multi-threaded performance accelerates data loading, batching, and parallel preprocessing tasks. Although most heavy computation is GPU-dependent, an underpowered CPU can starve GPUs of data, making balanced multi-core performance essential for maintaining peak workstation efficiency.\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's Generative AI AMD Ryzen Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eGenerative AI workloads are heavily GPU-dependent, particularly for training and running diffusion models, large language models, and real-time AI inference. High VRAM capacity is critical for fitting larger models, higher batch sizes, and longer context windows directly in memory. Multi-GPU configurations further improve scalability by distributing compute workloads and increasing throughput. A workstation-class GPU subsystem with strong tensor and compute performance is essential for delivering the real-time responsiveness and accelerated training speeds required in professional generative AI 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\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 Primal Gorilla","offer_id":42077489889326,"sku":"Cloud Ninjas WIW35U-5N6S-4G-Ryzen-Edition-Generative AI","price":1939.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_XL-WIW35U-5N6S-4G-1.jpg?v=1771955570"},{"product_id":"cloud-ninjas-workstations-for-black-forest-labs-amd-ryzen-edition","title":"Cloud Ninjas Workstations for Black Forest Labs FLUX AMD Ryzen 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 FLUX AMD Ryzen Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eFLUX.2 benefits from CPUs with strong single-core performance and moderate to high core counts. While the model itself is not CPU-bound, multithreading improves performance during data preprocessing, prompt batching, concurrent inference jobs, and overall system responsiveness when running multiple AI tools simultaneously.\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's FLUX AMD Ryzen Edition Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eThe GPU is the most critical component for FLUX.2. Image generation and inference are fully GPU-accelerated, relying on CUDA and tensor-based acceleration for diffusion sampling. A modern GPU with high compute throughput and ample VRAM significantly improves generation speed, supports higher resolutions, enables larger batch sizes, and allows advanced workflows such as upscaling, image-to-image generation, and multi-model experimentation.\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\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\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Cloud Ninjas Primal Gorilla","offer_id":42077527834670,"sku":"Cloud Ninjas WIW35U-5N6S-4G-Ryzen-Edition-Generative AI","price":1939.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_XL-WIW35U-5N6S-4G-1.jpg?v=1771955570"},{"product_id":"cloud-ninjas-workstations-for-stable-diffusion-multi-gpu-edition","title":"Cloud Ninjas Workstations for Stable Diffusion Multi GPU 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' Multi GPU Edition Stable Diffusion Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eStable Diffusion is primarily GPU-accelerated, but the CPU still plays an important supporting role in data preparation, prompt processing, image encoding\/decoding, and multi-instance orchestration. The application does not scale heavily with extreme core counts, but it benefits from strong multi-threaded performance when running multiple jobs, managing complex ComfyUI graphs, or handling parallel preprocessing tasks. This workstation’s CPU configuration is selected to maintain balanced system throughput so the GPUs remain fully utilized during professional generative workflows.\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' Multi GPU Edition Stable Diffusion Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eStable Diffusion performance is heavily GPU-dependent, with VRAM capacity and tensor compute performance acting as primary bottlenecks. Modern diffusion models often require 12–24GB+ of VRAM for high-resolution or multi-adapter workflows. \u003cstrong\u003eWhile most Stable Diffusion pipelines do not pool VRAM across GPUs, they scale extremely well by running concurrent jobs per GPU, dramatically increasing total workstation throughput for professional AI production environments.\u003c\/strong\u003e\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 Mythical Dragon","offer_id":42088387837998,"sku":"Cloud Ninjas WATRU-6N4S-4G-Multi-GPU-Edition-Stable Diffusion","price":2999.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Cloud_Ninjas_WATRU-4N6S-4G-6.jpg?v=1771955482"},{"product_id":"cloud-ninjas-workstations-for-stable-diffusion-standard-edition","title":"Cloud Ninjas Workstations for Stable Diffusion 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 Stable Diffusion Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eWhile image generation is primarily GPU-driven, the CPU plays an important role in data preparation, prompt processing, image decoding, and workflow coordination. The Standard Edition workstation’s high-frequency multi-core processor ensures efficient pipeline management, responsive UI interaction, and smooth handling of background tasks that support AI generation workflows.\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 Stable Diffusion Workstation\u003c\/span\u003e\u003c\/div\u003e\n\u003cdiv class=\"subsection-information\"\u003e\n\u003cp\u003eStable Diffusion performance is heavily dependent on GPU compute capability and available VRAM. The Standard Edition workstation’s professional GPU with ample VRAM significantly improves image generation speed, enables higher-resolution outputs, supports larger batch sizes, and allows the use of more advanced models and extensions. A capable GPU is the primary driver of performance for modern diffusion-based AI 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 \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 \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":42109825122350,"sku":"Cloud Ninjas WARU-4N4S-2G-LC-Standard-Edition-Stable Diffusion","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-comfyui-intel-edition","title":"Cloud Ninjas Workstations for ComfyUI 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' ComfyUI Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eComfyUI benefits from a balance CPU with strong multi-threading capabilities for handling pre-processing tasks, node execution coordination, and data transfers betweeen components. While GPU acceleration dominates generations, CPU performance impacts workflow responsiveness, image formatting, and VRAM management especially when running multiple pipelines or managing large batches.\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 WIUU-5N4S-2G\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration is the primary driver of ComfyUI performance, as image generation relies heavily on deep learning inference. A workstation GPU with high compute performance and substantial VRAM is critical for handling large diffusion models, high-resolution outputs, and advanced features like ControlNet or upscaling. More VRAM enables larger batch sizes and more complex workflows without memory constraints, directly improving efficiency in professional AI-driven content creation.\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 Neon Fox Air Cooled","offer_id":42231227842606,"sku":"Cloud Ninjas WIUU-5N4S-2G-AC-Intel-Edition-ComfyUI","price":1829.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7-WIUU-5N4S-2G-8.jpg?v=1771955738"},{"product_id":"cloud-ninjas-workstations-for-lmstudio-intel-edition","title":"Cloud Ninjas Workstations for LM Studio 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' LM Studio Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eLM Studio can perform inference on CPU, particularly with quantized models. Strong multi-core and multi-threaded CPU performance improves inference speed and throughput, while high single-core performance enhances UI responsiveness and prompt handling. CPU architecture plays a key role in latency-sensitive 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' LM Studio Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration significantly improves LM Studio performance for supported models. A workstation GPU with high compute performance and ample VRAM enables faster token generation, supports larger models without aggressive quantization, and improves responsiveness in real-time AI interactions. Increased VRAM capacity is especially important for maintaining performance with larger context sizes and concurrent workloads.\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 Ghost Viper Air Cooled","offer_id":42231379787822,"sku":"Cloud Ninjas WIUU-3N4S-1G-AC-Intel-Edition-LM Studio","price":1159.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_Mini-WIUU-3N4S-1G-1-AC.jpg?v=1771954927"},{"product_id":"cloud-ninjas-workstations-for-unifab-ryzen-edition","title":"Cloud Ninjas Workstations for UniFab 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' UniFab Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eThe CPU plays an important role in decoding source media, encoding output files, and managing overall workflow execution. UniFab Video Enhancer AI benefits from multi-core and multi-threaded CPU performance, especially when processing multiple files or running concurrent tasks. Strong CPU architecture improves responsiveness and reduces total processing time 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\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' UniFab Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration is the primary performance driver in UniFab Video Enhancer AI, as AI upscaling and enhancement models run on the GPU. A workstation GPU with high compute capability and ample VRAM is essential for handling high-resolution video, complex enhancement models, and batch processing tasks. Increased VRAM capacity enables smoother processing of 4K and 8K content and reduces limitations during intensive AI-driven video 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":42231410786350,"sku":"Cloud Ninjas WARU-4N4S-2G-AC-Ryzen-Edition-UniFab","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-localai-intel-edition","title":"Cloud Ninjas Workstations for LocalAI 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' LocalAI Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eLocalAI can run inference on CPU when GPU acceleration is unavailable or when using optimized quantized models. As a result, strong multi-core and multi-threaded CPU performance is critical for maintaining acceptable inference speeds. LocalAI also supports concurrent requests for backends that support it, such as llama.cpp and vLLM. CPU architecture directly impacts latency and throughput in professional local AI deployments. Learn more about concurrent requests \u003ca href=\"https:\/\/localai.io\/advanced\/index.html\"\u003ehere\u003c\/a\u003e\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' localAI Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration is critical as it enhances LocalAI performance for supported models, particularly for large language models and multiple-model workloads. A workstation GPU with high compute performance and ample VRAM enables faster inference, supports larger models, and improves response times across concurrent workloads. Increased VRAM is non-negotiable for maintaining performance due to how LocalAI manages models in memory once they are loaded in. Learn more about LocalAI’s VRAM management \u003ca href=\"https:\/\/localai.io\/advanced\/index.html\"\u003ehere\u003c\/a\u003e\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 Ghost Viper Liquid Cooled","offer_id":42231443882030,"sku":"Cloud Ninjas WIUU-3N4S-1G-LC-Intel-Edition-LocalAI","price":1109.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/Define_7_Mini-WIUU-3N4S-1G-1-LQC.jpg?v=1771954936"},{"product_id":"cloud-ninjas-workstations-for-upscayl-ryzen-edition","title":"Cloud Ninjas Workstations for Upscayl 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' Upscayl Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \u003cp\u003eWhile Upscayl relies primarily on GPU acceleration, the CPU is responsible for managing file I\/O, preprocessing, and post-processing. Strong multi-core performance improves efficiency when handling batch jobs, while good single-core performance enhances overall system responsiveness during active 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' Upscayl Workstation\u003c\/span\u003e\n \u003c\/div\u003e\n\n \u003cdiv class=\"subsection-information\"\u003e\n \t\u003cp\u003eGPU acceleration is the primary performance driver in Upscayl, as AI-based image enhancement models run on the GPU. A workstation GPU with strong compute capability and adequate VRAM enables faster upscaling, supports higher-resolution images, and allows for smoother batch processing. Increased VRAM capacity is especially important for handling large images or multiple concurrent tasks without memory limitations, directly improving performance in professional AI-driven imaging workflows.\n\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 Liquid Cooled","offer_id":42233192284206,"sku":"Cloud Ninjas WARU-4N4S-2G-Ryzen-Edition-Upscayl","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-generative-ai\/sw-workflow-ai-upscaling.oembed","provider":"Cloud Ninjas","version":"1.0","type":"link"}