NVIDIA H100 PCIe Tensor Core Graphics Card: 80GB HBM2 Memory, 5120-Bit, 1935 GB/s Bandwidth, 14592 Stream Processors, 456 Tensor Cores, PCIe 5.0 x16
SKU:
90SKC000-M7LAN0
In stock
Original price was: AED109,540.00.AED102,530.00Current price is: AED102,530.00. 6% OFF
- High-capacity 80GB HBM2 Memory for seamless performance in AI, data science, and machine learning workloads.
- 5120-Bit Memory Interface: Provides exceptional data handling and processing capabilities.
- Ultra-fast memory speed for high-throughput computing and deep learning tasks.
- Optimized for AI acceleration, enabling faster matrix operations and deep learning performance.
- Ensures ultra-fast data transfer and compatibility with next-generation systems.
- Specifically designed for high-performance AI, deep learning, and HPC applications.
In stock
Original price was: AED109,540.00.AED102,530.00Current price is: AED102,530.00. 6% OFF
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on each productNVIDIA H100 PCIe Tensor Core Graphics Card Description & Specifications:
| Feature | Specification | Description |
|---|---|---|
Graphics Memory | 80GB HBM2 | The NVIDIA H100 PCIe Tensor Core Graphics Card has a massive 80GB of high-bandwidth HBM2 memory. It ensures ultra-fast data retrieval and processing. Also, it comes with such a large memory capacity, it can effortlessly handle complex AI models, massive datasets, and other data-intensive tasks. This makes it an ideal choice for researchers and professionals working in AI and machine learning fields. |
Memory Interface | 5120-Bit | 5120-bit memory interface in the NVIDIA H100 Hopper PCIe 80GB Graphics Card helps to deliver exceptional memory throughput and speed, ensuring that high volumes of data can be processed without bottlenecks. This wide memory interface significantly reduces latency. |
Bandwidth | 1935 GB/s | The NVIDIA H100 PCIe Tensor Core Graphics Card boasts an incredible 1935 GB/s of memory bandwidth, facilitating rapid data transfers between the GPU and memory. This immense bandwidth ensures smooth handling of large-scale AI and deep learning tasks, such as training large neural networks, and optimizes performance for both research and commercial applications that require heavy computation. |
Stream Processors | 14592 | It comes with 14592 stream processors, the NVIDIA H100 Hopper PCIe 80GB Graphics Card is designed to efficiently handle parallel processing for complex workloads. The vast number of processors ensures that multiple tasks can be executed simultaneously, drastically reducing processing time for AI computations, deep learning model training, and high-performance computing tasks. |
Tensor Cores | 456 | The NVIDIA H100 PCIe Tensor Core Graphics Card has 456 advanced tensor cores. It helps to excel at accelerating AI computations, particularly for tasks involving matrix multiplications and deep learning operations. These specialized cores are optimized for tensor operations. Also, it provides an exceptional boost in performance, particularly for training large-scale deep learning models in AI research, data science, and computational fields. |
PCIe Version | PCIe 5.0 x16 | The NVIDIA H100 PCIe Tensor Core Graphics Card supports the latest PCIe 5.0 x16 interface, enabling blazing-fast data transfer rates between the GPU and the system. This next-gen interface ensures the graphics card is fully capable of handling the most demanding tasks, while also ensuring future compatibility with upcoming hardware advancements. |
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We offer the best price for NVIDIA H100 PCIe Tensor Core Graphics Card: 80GB HBM2 Memory, 5120-Bit, 1935 GB/s Bandwidth, 14592 Stream Processors, 456 Tensor Cores, PCIe 5.0 x16 in Dubai, UAE. Buy now with the best price!1 review for NVIDIA H100 PCIe Tensor Core Graphics Card: 80GB HBM2 Memory, 5120-Bit, 1935 GB/s Bandwidth, 14592 Stream Processors, 456 Tensor Cores, PCIe 5.0 x16
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Our refund and returns policy lasts 10 days. If 10 days have passed since your purchase, we can’t offer you a full refund or exchange.To be eligible for a return, your item must be unused and in the same condition that you received it. It must also be in the original packaging.
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