{"product_id":"qct-ai-server","title":"QCT QuantaGrid D75F-9U (8× B200, 1,440 GB)","description":"\u003cdiv class=\"puppy-one-fit\" data-catalog=\"2026-09-27\"\u003e\n\u003cp\u003e\u003cstrong\u003ePrivate cloud compute for teams and enterprises.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\u003cli\u003e\n\u003cstrong\u003ePuppy One fit:\u003c\/strong\u003e Not Puppy One (POD \/ private cloud)\u003c\/li\u003e\u003c\/ul\u003e\n\u003c\/div\u003e\u003cp\u003eHyperscale-grade 9U rackmount AI server featuring eight NVIDIA B200 GPUs on an HGX B200 baseboard, equipped with 1.4 TB of HBM3e memory at 64 TB\/s aggregate bandwidth, dual Intel Xeon 6 processors, 32 DDR5 DIMM slots, front hot-swap NVMe bays, and delivering up to 72 PFLOPS of dense FP4 AI performance.\u003c\/p\u003e\u003cp\u003eDesigned to train and serve trillion-parameter-class models on a single node, with fifth-generation NVLink and NVSwitch connecting all eight GPUs at 1.8 TB\/s, one-to-one GPU-to-NIC topology for 400G or 800G InfiniBand and Ethernet scale-out, and full NVIDIA AI Enterprise, CUDA, and Triton support.\u003c\/p\u003e\u003cp\u003eAir-cooled in a standard rack with roughly 10 kW of continuous draw on a three-phase feed, built by the ODM that manufactures much of the world's hyperscale fleet, and able to run a 671-billion-parameter model at FP8 or a 1-trillion-parameter model at FP4 entirely in GPU memory.\u003c\/p\u003e\u003cp\u003ePrice available on request.\u003c\/p\u003e","brand":"QCT","offers":[{"title":"Request a quote","offer_id":52457680666840,"sku":"QCT-D75F-9U-B200","price":0.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0839\/7039\/2280\/files\/may-chu-server-supermicro-hgx-b200-8-gpu-as-a126gs-tnbr.webp?v=1789181107","url":"https:\/\/shop.hussh.ai\/products\/qct-ai-server","provider":"Hussh Shop","version":"1.0","type":"link"}