{"product_id":"amd-radeon-pro-w7900-48gb","title":"AMD Radeon PRO W7900 (48GB)","description":"\u003cp\u003eThe AMD Radeon PRO W7900 is AMD’s flagship workstation graphics card. Its defining feature is 48GB of ECC-protected memory on the full RDNA 3 Navi 31 die, in a dual-slot form factor that fits real workstation chassis. It suits studios and engineering teams running large AI models, professional rendering pipelines or scientific visualization workloads that outgrow a 24GB consumer card.\u003c\/p\u003e\n\u003ch2\u003eWho it's for\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eRunning 30B-parameter class LLMs and keeping several models resident for a production inference pipeline\u003c\/li\u003e\n\u003cli\u003eFine-tuning mid-size open-weight models without chunking datasets or offloading to system memory\u003c\/li\u003e\n\u003cli\u003eArchitectural and product visualization, full-resolution VFX shots and simulation caches held entirely in GPU memory\u003c\/li\u003e\n\u003cli\u003eEngineering firms standardizing on one ECC-protected, ISV-certified card per seat\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eKey features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003e48GB ECC GDDR6:\u003c\/strong\u003e the full Navi 31 memory configuration on a 384-bit bus, with error-correcting protection for professional reliability, for LLMs, production scenes and massive point-cloud, 3D scan or CAD datasets on-card.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e96 Compute Units, 6,144 Stream Processors:\u003c\/strong\u003e the full Navi 31 die, set up for workstation workloads rather than gaming clocks.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e96 second-generation Ray Accelerators, 192 AI Accelerators:\u003c\/strong\u003e dedicated hardware for professional ray-traced rendering and AI-assisted workflows.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e864GB\/s memory bandwidth:\u003c\/strong\u003e keeps the compute units fed when working with the large datasets this memory capacity allows.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e61 TFLOPS FP32 \/ 122 TFLOPS FP16:\u003c\/strong\u003e strong compute for rendering, simulation and mixed-precision AI workloads.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDual-slot workstation design:\u003c\/strong\u003e a more space-efficient footprint than earlier triple-slot professional cards, so integrators can fit up to four W7900s in one multi-GPU workstation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROCm certified:\u003c\/strong\u003e validated for professional AI and ML development, with ISV-certified drivers for major CAD, DCC and simulation applications.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eQuad DisplayPort 2.1 outputs:\u003c\/strong\u003e three full-size DisplayPort 2.1 plus one mini-DisplayPort 2.1, each capable of 54Gbps, for high-resolution multi-monitor CAD and visualization.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eSpec\u003c\/th\u003e\n\u003cth\u003eDetail\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eArchitecture\u003c\/td\u003e\n\u003ctd\u003eAMD RDNA 3 (full Navi 31 die)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCompute units\u003c\/td\u003e\n\u003ctd\u003e96 (6,144 Stream Processors, 192 AI Accelerators, 96 Ray Accelerators)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory\u003c\/td\u003e\n\u003ctd\u003e48GB ECC GDDR6, 384-bit bus\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory bandwidth\u003c\/td\u003e\n\u003ctd\u003e864GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCompute performance\u003c\/td\u003e\n\u003ctd\u003e61 TFLOPS FP32 \/ 122 TFLOPS FP16\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eClocks\u003c\/td\u003e\n\u003ctd\u003e1,855MHz core \/ 2,495MHz boost\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eTotal board power\u003c\/td\u003e\n\u003ctd\u003e295W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower connectors\u003c\/td\u003e\n\u003ctd\u003e2x 8-pin PCIe\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eInterface\u003c\/td\u003e\n\u003ctd\u003ePCIe 4.0 x16\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eForm factor\u003c\/td\u003e\n\u003ctd\u003eDual-slot workstation card, 280mm length\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDisplay outputs\u003c\/td\u003e\n\u003ctd\u003e3x DisplayPort 2.1 + 1x mini-DisplayPort 2.1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSoftware\u003c\/td\u003e\n\u003ctd\u003eROCm certified, ISV-certified professional drivers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch2\u003eGood to know\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eROCm is officially supported and certified for this card, but the CUDA ecosystem still has a head start in framework coverage, especially for bleeding-edge AI research code that assumes NVIDIA hardware.\u003c\/li\u003e\n\u003cli\u003eTeams already standardized on PyTorch and mainstream inference frameworks have a well-supported path on ROCm.\u003c\/li\u003e\n\u003cli\u003eOne W7900 replaces what would otherwise take two or more 24GB cards, without the extra system complexity, driver overhead or PCIe lane contention of a multi-GPU build.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eChoose the W7900 when memory headroom is the problem and your workflows are rendering-, CAD- or mainstream-AI-first. It is a low-risk, high-capacity upgrade; if your code needs CUDA, look elsewhere.\u003c\/p\u003e","brand":"AMD","offers":[{"title":"Default Title","offer_id":58232537940350,"sku":"AMD-W7900","price":3999.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1022\/4468\/0062\/files\/gpu-w7900.jpg?v=1792094037","url":"https:\/\/computahardware.net\/products\/amd-radeon-pro-w7900-48gb","provider":"ComputaHardware","version":"1.0","type":"link"}