{"product_id":"nvidia-rtx-6000-ada-48gb-gddr6-professional-gpu-ai-rendering-amp-simulation","title":"NVIDIA RTX 6000 Ada 48GB GDDR6 Professional GPU – AI, Rendering \u0026amp; Simulation","description":"\u003ch2\u003e\u003cstrong\u003ePart Numbers Supported (Same Specs \u0026amp; Performance):\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003ch2\u003e\u003cstrong\u003e900-5G133-0150-001\u003c\/strong\u003e\u003c\/h2\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003ch2\u003e\u003cstrong\u003e8KCT1 (Dell OEM)\u003c\/strong\u003e\u003c\/h2\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cblockquote\u003e\n\u003cp\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003cstrong\u003e\u003cem\u003eAll above PNs refer to the same NVIDIA RTX 6000 Ada 48GB GPU with identical specifications and capabilities.\u003c\/em\u003e\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/blockquote\u003e\n\u003chr\u003e\n\u003cp\u003eThe \u003cstrong\u003eNVIDIA RTX 6000 Ada 48GB GPU\u003c\/strong\u003e is a high-performance professional graphics solution built on the Ada Lovelace architecture, engineered for AI development, 3D rendering, simulation, and data-intensive workflows. With 48GB of GDDR6 ECC memory, 18,176 CUDA Cores, and advanced ray-tracing and Tensor Core capabilities, it delivers unmatched performance for enterprise workstations, data science teams, and GPU-accelerated environments.\u003c\/p\u003e\n\u003chr\u003e\n\u003ch2\u003e⭐ \u003cstrong\u003eKey Features\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eNext-gen \u003cstrong\u003eAda Lovelace architecture\u003c\/strong\u003e for extreme performance gains\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003e48GB GDDR6 ECC Memory\u003c\/strong\u003e for large datasets, AI models \u0026amp; complex scenes\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003e18,176 CUDA Cores\u003c\/strong\u003e, 568 Tensor Cores \u0026amp; 142 RT Cores\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePCIe Gen 4.0 x16\u003c\/strong\u003e interface for high-bandwidth workloads\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eSupports \u003cstrong\u003eNVIDIA Omniverse, CUDA, RTX, AI \u0026amp; ML frameworks\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eQuad DisplayPort 1.4a\u003c\/strong\u003e outputs with HDR and 8K support\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eBuilt for \u003cstrong\u003eworkstations, media studios, AI labs, and enterprise R\u0026amp;D\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003chr\u003e\n\u003ch2\u003e📊 \u003cstrong\u003eTechnical Specifications \u003cbr\u003e\u003ca href=\"https:\/\/www.nvidia.com\/content\/dam\/en-zz\/Solutions\/design-visualization\/quadro-product-literature\/proviz-print-nvidia-rtx-a6000-datasheet-us-nvidia-1454980-r9-web%20(1).pdf\" title=\"NVIDIA RTX 6000 Ada 48GB GDDR6 Professional GPU – Specs Sheet\" rel=\"noopener\" target=\"_blank\"\u003eCLICK HERE FOR SPECS SHEET\u003c\/a\u003e\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eSpecification\u003c\/th\u003e\n\u003cth\u003eDetails\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eArchitecture\u003c\/td\u003e\n\u003ctd\u003eNVIDIA Ada Lovelace\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCUDA Cores\u003c\/td\u003e\n\u003ctd\u003e18,176\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTensor Cores\u003c\/td\u003e\n\u003ctd\u003e568\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eRT Cores\u003c\/td\u003e\n\u003ctd\u003e142\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGPU Memory\u003c\/td\u003e\n\u003ctd\u003e48GB GDDR6 ECC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory Interface\u003c\/td\u003e\n\u003ctd\u003e384-bit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory Bandwidth\u003c\/td\u003e\n\u003ctd\u003e960 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFP32 Performance\u003c\/td\u003e\n\u003ctd\u003e~91 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eRT Performance\u003c\/td\u003e\n\u003ctd\u003e~210 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTensor Performance\u003c\/td\u003e\n\u003ctd\u003e~1,466 TFLOPS (with sparsity)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMax Power Consumption\u003c\/td\u003e\n\u003ctd\u003e300W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSystem Interface\u003c\/td\u003e\n\u003ctd\u003ePCI Express 4.0 x16\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDisplay Outputs\u003c\/td\u003e\n\u003ctd\u003e4 × DisplayPort 1.4a\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eForm Factor\u003c\/td\u003e\n\u003ctd\u003eDual-slot, 10.5\"\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCooling\u003c\/td\u003e\n\u003ctd\u003eActive Air Cooling\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eVR Ready\u003c\/td\u003e\n\u003ctd\u003eYes\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSupported APIs\u003c\/td\u003e\n\u003ctd\u003eDirectX 12, OpenGL 4.6, Vulkan, CUDA, OpenCL\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003chr\u003e\n\u003ch2\u003e🧩 \u003cstrong\u003eIdeal Use Cases\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003cp\u003eThis GPU is designed for mission-critical, high-compute workflows such as:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAI training \u0026amp; inference\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eRendering \u0026amp; VFX Production (Cinema 4D, Maya, Blender, Unreal Engine)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDigital Twins \u0026amp; NVIDIA Omniverse\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eData Science, Simulation \u0026amp; Engineering Workloads\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eMedical Imaging, CAD, CAM \u0026amp; Scientific Modeling\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eEnterprise Workstations \u0026amp; GPU Virtualization\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003chr\u003e\n\u003ch2 data-start=\"174\" data-end=\"235\"\u003e🆚 \u003cstrong data-start=\"180\" data-end=\"235\"\u003eRTX 6000 Ada vs RTX A6000 vs RTX A5000 - Comparison\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003cp data-start=\"237\" data-end=\"385\"\u003eChoosing the right NVIDIA workstation GPU depends on your AI, 3D, and rendering workload requirements. Here’s a quick comparison to help you decide:\u003c\/p\u003e\n\u003cdiv class=\"_tableContainer_1rjym_1\"\u003e\n\u003cdiv class=\"group _tableWrapper_1rjym_13 flex w-fit flex-col-reverse\" tabindex=\"-1\"\u003e\n\u003ctable data-start=\"387\" data-end=\"1188\" class=\"w-fit min-w-(--thread-content-width)\"\u003e\n\u003cthead data-start=\"387\" data-end=\"470\"\u003e\n\u003ctr data-start=\"387\" data-end=\"470\"\u003e\n\u003cth data-start=\"387\" data-end=\"405\" data-col-size=\"sm\"\u003eFeature \/ Model\u003c\/th\u003e\n\u003cth data-start=\"405\" data-end=\"431\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"407\" data-end=\"430\"\u003eRTX 6000 Ada (48GB)\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth data-start=\"431\" data-end=\"450\" data-col-size=\"sm\"\u003eRTX A6000 (48GB)\u003c\/th\u003e\n\u003cth data-start=\"450\" data-end=\"470\" data-col-size=\"sm\"\u003eRTX A5000 (24GB)\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody data-start=\"555\" data-end=\"1188\"\u003e\n\u003ctr data-start=\"555\" data-end=\"617\"\u003e\n\u003ctd data-start=\"555\" data-end=\"570\" data-col-size=\"sm\"\u003eArchitecture\u003c\/td\u003e\n\u003ctd data-start=\"570\" data-end=\"598\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"572\" data-end=\"597\"\u003eAda Lovelace (Latest)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"598\" data-end=\"607\" data-col-size=\"sm\"\u003eAmpere\u003c\/td\u003e\n\u003ctd data-start=\"607\" data-end=\"617\" data-col-size=\"sm\"\u003eAmpere\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"618\" data-end=\"662\"\u003e\n\u003ctd data-start=\"618\" data-end=\"631\" data-col-size=\"sm\"\u003eCUDA Cores\u003c\/td\u003e\n\u003ctd data-start=\"631\" data-end=\"644\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"633\" data-end=\"643\"\u003e18,176\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"644\" data-end=\"653\" data-col-size=\"sm\"\u003e10,752\u003c\/td\u003e\n\u003ctd data-start=\"653\" data-end=\"662\" data-col-size=\"sm\"\u003e8,192\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"663\" data-end=\"731\"\u003e\n\u003ctd data-start=\"663\" data-end=\"678\" data-col-size=\"sm\"\u003eTensor Cores\u003c\/td\u003e\n\u003ctd data-start=\"678\" data-end=\"698\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"680\" data-end=\"697\"\u003e568 (4th Gen)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"698\" data-end=\"714\" data-col-size=\"sm\"\u003e336 (3rd Gen)\u003c\/td\u003e\n\u003ctd data-start=\"714\" data-end=\"731\" data-col-size=\"sm\"\u003e256 (3rd Gen)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"732\" data-end=\"794\"\u003e\n\u003ctd data-start=\"732\" data-end=\"743\" data-col-size=\"sm\"\u003eRT Cores\u003c\/td\u003e\n\u003ctd data-start=\"743\" data-end=\"763\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"745\" data-end=\"762\"\u003e142 (3rd Gen)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"763\" data-end=\"778\" data-col-size=\"sm\"\u003e84 (2nd Gen)\u003c\/td\u003e\n\u003ctd data-start=\"778\" data-end=\"794\" data-col-size=\"sm\"\u003e64 (2nd Gen)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"795\" data-end=\"864\"\u003e\n\u003ctd data-start=\"795\" data-end=\"808\" data-col-size=\"sm\"\u003eGPU Memory\u003c\/td\u003e\n\u003ctd data-start=\"808\" data-end=\"829\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"810\" data-end=\"828\"\u003e48GB GDDR6 ECC\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"829\" data-end=\"846\" data-col-size=\"sm\"\u003e48GB GDDR6 ECC\u003c\/td\u003e\n\u003ctd data-start=\"846\" data-end=\"864\" data-col-size=\"sm\"\u003e24GB GDDR6 ECC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"865\" data-end=\"923\"\u003e\n\u003ctd data-start=\"865\" data-end=\"884\" data-col-size=\"sm\"\u003eMemory Bandwidth\u003c\/td\u003e\n\u003ctd data-start=\"884\" data-end=\"900\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"886\" data-end=\"899\"\u003e~960 GB\/s\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"900\" data-end=\"911\" data-col-size=\"sm\"\u003e768 GB\/s\u003c\/td\u003e\n\u003ctd data-start=\"911\" data-end=\"923\" data-col-size=\"sm\"\u003e600 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"924\" data-end=\"989\"\u003e\n\u003ctd data-start=\"924\" data-end=\"943\" data-col-size=\"sm\"\u003eMax FP32 Compute\u003c\/td\u003e\n\u003ctd data-start=\"943\" data-end=\"960\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"945\" data-end=\"959\"\u003e~91 TFLOPS\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"960\" data-end=\"974\" data-col-size=\"sm\"\u003e38.7 TFLOPS\u003c\/td\u003e\n\u003ctd data-start=\"974\" data-end=\"989\" data-col-size=\"sm\"\u003e27.8 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"990\" data-end=\"1032\"\u003e\n\u003ctd data-start=\"990\" data-end=\"1010\" data-col-size=\"sm\"\u003ePower Consumption\u003c\/td\u003e\n\u003ctd data-start=\"1010\" data-end=\"1017\" data-col-size=\"sm\"\u003e300W\u003c\/td\u003e\n\u003ctd data-start=\"1017\" data-end=\"1024\" data-col-size=\"sm\"\u003e300W\u003c\/td\u003e\n\u003ctd data-start=\"1024\" data-end=\"1032\" data-col-size=\"sm\"\u003e230W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"1033\" data-end=\"1074\"\u003e\n\u003ctd data-start=\"1033\" data-end=\"1050\" data-col-size=\"sm\"\u003eNVLink Support\u003c\/td\u003e\n\u003ctd data-start=\"1050\" data-end=\"1057\" data-col-size=\"sm\"\u003e❌ No\u003c\/td\u003e\n\u003ctd data-start=\"1057\" data-end=\"1065\" data-col-size=\"sm\"\u003e✅ Yes\u003c\/td\u003e\n\u003ctd data-start=\"1065\" data-end=\"1074\" data-col-size=\"sm\"\u003e✅ Yes\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr data-start=\"1075\" data-end=\"1188\"\u003e\n\u003ctd data-start=\"1075\" data-end=\"1086\" data-col-size=\"sm\"\u003eBest For\u003c\/td\u003e\n\u003ctd data-start=\"1086\" data-end=\"1133\" data-col-size=\"sm\"\u003e\u003cstrong data-start=\"1088\" data-end=\"1132\"\u003eAI, Simulation, 3D, LLMs, VFX, Omniverse\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd data-start=\"1133\" data-end=\"1159\" data-col-size=\"sm\"\u003eHigh-end 3D \u0026amp; Rendering\u003c\/td\u003e\n\u003ctd data-start=\"1159\" data-end=\"1188\" data-col-size=\"sm\"\u003eMid-range Rendering \u0026amp; CAD\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 data-start=\"1190\" data-end=\"1212\"\u003e🔍 Quick Summary\u003c\/h3\u003e\n\u003cul data-start=\"1213\" data-end=\"1571\"\u003e\n\u003cli data-start=\"1213\" data-end=\"1357\"\u003e\n\u003cp data-start=\"1215\" data-end=\"1357\"\u003e\u003cstrong data-start=\"1215\" data-end=\"1231\"\u003eRTX 6000 Ada\u003c\/strong\u003e → Best choice if you need maximum performance for \u003cstrong data-start=\"1282\" data-end=\"1354\"\u003eAI, 3D rendering, digital twins, Omniverse, and simulation workloads\u003c\/strong\u003e.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"1358\" data-end=\"1462\"\u003e\n\u003cp data-start=\"1360\" data-end=\"1462\"\u003e\u003cstrong data-start=\"1360\" data-end=\"1373\"\u003eRTX A6000\u003c\/strong\u003e → Still a strong option for \u003cstrong data-start=\"1402\" data-end=\"1459\"\u003erendering, visualization, and multi-GPU NVLink setups\u003c\/strong\u003e.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli data-start=\"1463\" data-end=\"1571\"\u003e\n\u003cp data-start=\"1465\" data-end=\"1571\"\u003e\u003cstrong data-start=\"1465\" data-end=\"1478\"\u003eRTX A5000\u003c\/strong\u003e → Ideal for \u003cstrong data-start=\"1491\" data-end=\"1538\"\u003emid-range VFX, CAD, BIM, engineering design\u003c\/strong\u003e, and budget-conscious workflows.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003chr\u003e\n\u003ch2\u003e\u003cstrong\u003e❓ Frequently Asked Questions\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eQ1: Is the Dell part number (8KCT1) different from the standard NVIDIA retail version?\u003c\/strong\u003e\u003cbr\u003eA: No - both part numbers represent the same RTX 6000 Ada GPU with identical specs and performance. OEM versions may include different packaging or accessories but performance remains unchanged.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ2: Can the RTX 6000 Ada be used for AI model training?\u003c\/strong\u003e\u003cbr\u003eA: Yes, its 48GB ECC memory and Ada Tensor Cores make it highly suitable for LLMs, diffusion models, NLP, and computer vision workloads.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ3: Does it support NVLink?\u003c\/strong\u003e\u003cbr\u003eA: No - NVIDIA removed NVLink support in Ada-based workstation GPUs.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eQ4: Is this GPU compatible with servers and workstations?\u003c\/strong\u003e\u003cbr\u003eA: It is primarily designed for \u003cstrong\u003eprofessional workstations\u003c\/strong\u003e, though some servers support it if PCIe power and airflow requirements are met.\u003c\/p\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":46731774918817,"sku":"NVIDIA-RTX6000ADA-48GB","price":97500.0,"currency_code":"BRL","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/2216\/8673\/files\/NVIDIA-RTX-6000-Ada-48GB-GDDR6-Professional-GPU-AI-Rendering-amp-Simulation.jpg?v=1784705535","url":"https:\/\/www.foxti.com.br\/products\/nvidia-rtx-6000-ada-48gb-gddr6-professional-gpu-ai-rendering-amp-simulation","provider":"FoxTI","version":"1.0","type":"link"}