Price for 6000 Blackwell series cards have stabilized after 3 consecutive 30% baseline hikes by Nvidia in 2026 and are expected to maintain through the rest of 2026. Supply remains strained. Please note that compliance is mandatory on all AI enterprise compute GPUs and Servers and end-user forms must be filled out before we can share any quotes. Please note Credit Card payments will only work if USD or AED currency is selected on top right corner of the website. HGX B200/B300 lead times are now between 8-14 weeks for Golden Sku, with custom BOMs exceed 20 weeks. For DRAM and SSD bulk orders, please inquire in the chat.
The NVIDIA A100 Tensor Core GPU delivers unprecedented acceleration—at every scale—to power the world’s highest performing elastic data centers for AI, data analytics, and high-performance computing (HPC) applications.
2-year manufacturer repair or replace warranty included.
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Update 06.01.2024: Please note the production of this product ceased in February, 2024, and is now EOL (end-of-life). Remaining stock is limited. Nvidia has recommended the L40/L40S line as a replacement in the meantime, budget-friendly RTX A6000 ADA, or the significantly pricier and performant H100. The true successor has not been disclosed, but we suspect Nvidia will focus on the new Blackwell/GH200 chips for HPC going forward into 2025 and beyond. Given the EOL, there is a mix of old new stock from different OEMs (PNY, Foxconn, HPE), including custom SXM to PCI-E conversions to accommodate the extreme demand we continue to experience. We cannot guarantee which version will be sent, but are committed in doing our best to fulfill orders based on the buyer’s preference.
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The NVIDIA A100 Tensor Core GPU delivers unprecedented acceleration—at every scale—to power the world’s highest performing elastic data centers for AI, data analytics, and high-performance computing (HPC) applications. As the engine of the NVIDIA data center platform, A100 provides up to 20x higher performance over the prior NVIDIA Volta generation. A100 can efficiently scale up or be partitioned into seven isolated GPU instances, with Multi-Instance GPU (MIG) providing a unified platform that enables elastic data centers to dynamically adjust to shifting workload demands.

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