The GPU for Generative AI and HPC
The NVIDIA H200 Tensor Core GPU supercharges generative AI and high-performance computing (HPC) workloads with game-changing performance and memory capabilities. As the first GPU with HBM3e, the H200’s larger and faster memory fuels the acceleration of generative AI and large language models (LLMs) while advancing scientific computing for HPC workloads.
Higher Performance With Larger, Faster Memory
Based on the NVIDIA Hopper™ architecture, the NVIDIA H200 is the first GPU to offer 141 gigabytes (GB) of HBM3e memory at 4.8 terabytes per second (TB/s) —that’s nearly double the capacity of the NVIDIA H100 Tensor Core GPU with 1.4X more memory bandwidth. The H200’s larger and faster memory accelerates generative AI and LLMs, while advancing scientific computing for HPC workloads with better energy efficiency and lower total cost of ownership.
Unlock Insights With High-Performance LLM Inference
In the ever-evolving landscape of AI, businesses rely on LLMs to address a diverse range of inference needs. An AI inference accelerator must deliver the highest throughput at the lowest TCO when deployed at scale for a massive user base.
The H200 boosts inference speed by up to 2X compared to H100 GPUs when handling LLMs like Llama2.
Supercharge High-Performance Computing
Memory bandwidth is crucial for HPC applications as it enables faster data transfer, reducing complex processing bottlenecks. For memory-intensive HPC applications like simulations, scientific research, and artificial intelligence, the H200’s higher memory bandwidth ensures that data can be accessed and manipulated efficiently, leading up to 110X faster time to results compared to CPUs.
Reduce Energy and TCO
With the introduction of the H200, energy efficiency and TCO reach new levels. This cutting-edge technology offers unparalleled performance, all within the same power profile as the H100. AI factories and supercomputing systems that are not only faster but also more eco-friendly, deliver an economic edge that propels the AI and scientific community forward.
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