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  • Nvidia H200 Tensor Core Gpu - 141GB of HBM3e Gpu memory - 4.8TB/s of memory bandwidth

    SKU # HS-NVI-H200
    Condition # New

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    Product Details

    Nvidia H200 Tensor Core Gpu - 141GB of HBM3e Gpu memory - 4.8TB/s of memory bandwidth

    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 Monthsdels (LLMs) while advancing scientific computing For HPC workloads.

    Highlights

    Experience Next-Level Performance

    Llama2 70B Inference: 1.9X Faster

    GPT-3 175B Inference: 1.6X Faster

    High-Performance Computing: 110X Faster

    Benefits

    Higher Performance And 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 Monthsre 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.

    Up To 1.6 Higher Inference Performance With Nvidia H200

    Preliminary measured performance, subject To change.
    Llama2 13B: ISL 128, OSL 2K | Throughput | H100 1x Gpu BS 64 | H200 1x Gpu BS 128
    GPT-3 175B: ISL 80, OSL 200 | x8 H100 GPUs BS 64 | x8 H200 GPUs BS 128
    Llama2 70B: ISL 2K, OSL 128 | Throughput | H100 1x Gpu BS 8 | H200 1x Gpu BS 32.

    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.

    Supercharge High-Performance Computing With Nvidia H200

    Projected performance, subject To change.
    HPC MILC- dataset NERSC Apex Medium | HGX H200 4-GPU | dual Sapphire Rapids 8480
    HPC Apps- CP2K: dataset H2O-32-RI-dRPA-96points | GROMACS: dataset STMV | ICON: dataset r2b5 | MILC: dataset NERSC Apex Medium | Chroma: dataset HMC Medium | Quantum Espresso: dataset AUSURF112 | 1x H100 | 1x H200.

    Better Energy Efficiency And Cost With Nvidia H200

    Preliminary measured performance, subject To change.
    Llama2 70B: ISL 2K, OSL 128 | Throughput | H100 1x Gpu BS 8 | H200 1x Gpu BS 32

    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 Monthsre eco-friendly, deliver an economic edge that propels The AI And scientific community forward.

    Performance

    Perpetual Innovation Brings Perpetual Performance Gains

    GPT-3 175B Inference Performance

    Single-node HGX measured performance | A100 April 2021 | H100 TensorRT-LLM Oct 2023 | H200 TensorRT-LLM Oct 2023

    The Nvidia Hopper architecture delivers an unprecedented performance leap over its predecessor And continues To raise The bar through ongoing software enhancements With The H100, including The recent release of powerful open-source libraries.

    The introduction of The H200 continues The Monthsmentum With Monthsre performance. Investment in it ensures performance leadership now, and—with continued improvements To supported software—the future.

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