What Is HBM3e Memory in H200 GPU?

HBM3e memory in the NVIDIA H200 GPU represents the latest advancement in high-bandwidth memory technology, specifically tailored for AI and high-performance computing workloads. It provides 141 GB of capacity and up to 4.8 TB/s bandwidth, nearly doubling the memory of the previous H100 GPU.​
HBM3e is an enhanced version of High Bandwidth Memory (HBM) used in the NVIDIA H200 GPU, offering 141 GB of stacked DRAM at 4.8 TB/s bandwidth. This first-of-its-kind implementation on Hopper architecture boosts generative AI inference by up to 2x and supports larger language models without sharding.​

Core Features

HBM3e stacks multiple DRAM dies vertically using through-silicon vias (TSVs) for ultra-high density and speed, enabling the H200's 141 GB capacity—1.76x more than the H100's 80 GB HBM3. Bandwidth reaches 4.8 TB/s, a 1.4x improvement over H100's 3.35 TB/s, reducing latency in matrix multiplications critical for transformer models. Micron's 24 GB HBM3e modules allow six-stack configurations, replacing H100's five 16 GB stacks plus filler.​

Cyfuture Cloud integrates H200 GPUs to leverage this memory for seamless AI training and inference, powering LLMs like LLaMA-65B with minimal bottlenecks on Delhi-based data centers.​

Performance Benefits

The H200 with HBM3e delivers 1.9x faster AI inference for models like GPT-3 and 110x better HPC physics simulations compared to CPU baselines. Larger memory fits extended contexts in long-sequence LLMs, increasing tokens per second and cutting sharding needs across multi-GPU setups. Energy efficiency improves via optimized power management, lowering TCO for Cyfuture Cloud users scaling generative AI deployments.​

In benchmarks, H200 handles 65B-parameter models 1.6x faster than H100, ideal for Cyfuture's NVLink-enabled clusters.​

Technical Specifications

Cyfuture Cloud's H200 instances exploit this for 1.4x bandwidth gains in real-time AI tasks.​

Cyfuture Cloud Integration

Cyfuture Cloud deploys H200 GPUs in high-density racks, combining HBM3e's speed with local NVLink for multi-node scaling. This setup accelerates customer workloads in AI fine-tuning and scientific simulations, available via Delhi proximity for low-latency access. Users benefit from air-gapped security and elastic provisioning, ensuring HBM3e potential translates to production ROI.​

Conclusion

HBM3e in the H200 GPU transforms AI infrastructure by packing unprecedented memory density and bandwidth into a single accelerator, positioning Cyfuture Cloud as a leader in generative AI hosting. Deploying H200 unlocks 2x inference speedups and efficient scaling for enterprise LLMs, driving innovation with reliable, high-performance cloud resources.​

Follow-Up Questions

1. How does HBM3e differ from HBM3?
HBM3e extends HBM3 with higher clock speeds (up to 9.2 Gbps/pin) and larger 24 GB stacks, yielding 1.4x bandwidth and 1.76x capacity in H200 versus H100.​

2. What workloads benefit most from H200's HBM3e?
Generative AI inference, LLM training with long contexts, and HPC simulations like MILC physics gain most, with 110x CPU speedups and reduced model sharding.​

3. Is HBM3e available on Cyfuture Cloud?
Yes, Cyfuture Cloud offers H200 GPU instances optimized for HBM3e, enhancing AI/HPC tasks with 4.8 TB/s bandwidth and 141 GB memory.​

4. How does H200 compare to Blackwell GPUs?
H200 (Hopper) precedes Blackwell's B200 (with HBM3e at 192 GB), but excels in current Hopper ecosystems; Cyfuture supports both for transitional workloads.​

5. What is the power draw of H200 with HBM3e?
Up to 1000W TDP, with efficiency gains from HBM3e reducing overall cluster power versus H100 for Cyfuture deployments.​