H200 GPU: Technical Specifications, Memory, Bandwidth, MIG Support

The NVIDIA H200 GPU is a cutting-edge, high-performance GPU designed for advanced AI, HPC, and generative AI workloads. It boasts 141GB of HBM3e memory, an extraordinary 4.8 TB/s memory bandwidth, and a configurable thermal design power (TDP) up to 700W in the SXM form factor. The H200 supports Multi-Instance GPU (MIG) technology, allowing partitioning into up to 7 instances with 16.5GB memory each, enabling flexible, scalable deployments. Integrated into Cyfuture AI's cloud infrastructure, the H200 delivers unparalleled speed and efficiency for deep learning, large language models, and data-intensive applications, making it ideal for enterprises and researchers targeting high throughput and optimized multi-GPU performance.

Overview of NVIDIA H200 GPU

The NVIDIA H200 GPU is the latest in NVIDIA’s Hopper architecture lineup, designed to deliver exceptional AI and HPC performance. It features the first integrated HBM3e memory, which provides much higher memory speeds and improves power efficiency substantially compared to previous models. The H200 is especially optimized for large language model training, generative AI, and scientific computing, pushing the frontier of next-gen AI applications with over 32 petaFLOPS in FP8 tensor core operations.

Technical Specifications

Specification	H200 SXM	H200 NVL
GPU Memory	141GB HBM3e	141GB HBM3e
Memory Bandwidth	4.8 TB/s	4.8 TB/s
FP64 Performance	34 TFLOPS	34 TFLOPS
FP32 Performance	67 TFLOPS	67 TFLOPS
TF32 Tensor Core	989 TFLOPS	989 TFLOPS
BFLOAT16 Tensor Core	1,979 TFLOPS	1,979 TFLOPS
FP16 Tensor Core	1,979 TFLOPS	1,979 TFLOPS
FP8 Tensor Core	3,958 TFLOPS	3,958 TFLOPS
INT8 Tensor Core	3,958 TFLOPS	3,958 TFLOPS
Multi-Instance GPUs (MIG)	Up to 7 instances @16.5 GB each	Up to 7 instances @16.5 GB each
Thermal Design Power (TDP)	Up to 700W (configurable)	Up to 600W (configurable)
Interconnect	NVIDIA NVLink 900GB/s, PCIe Gen5 128GB/s	NVLink bridge 900GB/s, PCIe Gen5 128GB/s
Form Factor	SXM (High performance)	PCIe (standard server use)

These specifications underline the GPU’s ability to handle highly parallel workloads efficiently, making it suitable for cutting-edge AI workflows and HPC environments.?

Memory and Bandwidth Details

The 141GB of HBM3e memory on the H200 delivers a memory bandwidth of 4.8 TB/s, a critical factor in accelerating AI-model training and large-scale data analytics. HBM3e provides higher speed, greater density, and improved power efficiency compared to HBM2, facilitating real-time processing of massive datasets common in generative AI and scientific simulations.?

Multi-Instance GPU (MIG) Support

MIG technology on the H200 allows partitioning the GPU into up to 7 isolated instances, each with 16.5GB of memory, enabling multiple workloads to run concurrently without interference. This functionality boosts resource utilization efficiency and is ideal for cloud service providers and enterprises looking to maximize GPU resource distribution across users and tasks.?

Comparison with Previous Generation GPUs

Compared to the NVIDIA H100, the H200 introduces HBM3e memory and increased memory bandwidth, along with architectural improvements that lower power consumption while boosting performance in tensor operations. These enhancements make the H200 particularly suited for large language model inference and training, scientific computations, and other AI-intensive workloads.?

(FAQs):

Q1: What applications benefit most from the NVIDIA H200 GPU?
A1: Large-scale AI training, generative AI, scientific simulations, high-performance computing, and big data analytics benefit significantly from the H200’s enhanced memory, bandwidth, and compute power.?

Q2: How does Cyfuture AI integrate the H200 GPU in its services?
A2: Cyfuture AI offers NVIDIA H200 GPUs as part of its cloud GPU clusters, providing scalable, high-throughput AI training and inferencing services to enterprises globally, coupled with flexible pricing and robust multi-GPU management.?

Q3: Can the H200 GPU be used in existing PCIe servers?
A3: Yes, the H200 is available both as an SXM module for high-performance servers and as a PCIe adapter, making it adaptable to different data center infrastructures.?

Q4: What is the power consumption of the H200 GPU?
A4: The H200 has a configurable TDP of up to 700W for the SXM form factor and up to 600W for the PCIe version, optimized for performance and power efficiency balance.?

Conclusion

The NVIDIA H200 GPU sets a new benchmark for AI compute power with its massive 141GB HBM3e memory, extraordinary 4.8 TB/s bandwidth, and flexible Multi-Instance GPU support. Integrated within Cyfuture AI’s cloud infrastructure, it empowers enterprises and researchers with the computational muscle required for advanced AI, deep learning, and HPC workloads. Whether deployed in SXM or PCIe form factors, the H200 ensures scalable, efficient, and robust performance to meet the evolving demands of modern AI-driven applications.

This makes the NVIDIA H200 GPU a pivotal technology for any organization looking to stay at the forefront of AI innovation with flexible access through Cyfuture AI’s cloud GPU solutions.

Feel free to explore Cyfuture AI’s offerings for GPU as a Service to harness this power without upfront hardware investments and enjoy global cloud accessibility.