NVIDIA’s GPUs continue to shape the future of artificial intelligence (AI) and high-performance computing (HPC).
The H100, based on the Hopper architecture, has powered the world’s largest AI models since 2022.
Now, the H200 takes that same foundation further - delivering a major boost in memory capacity and bandwidth to meet the growing demands of large-scale AI.
H100 - Built for high-performance AI
The NVIDIA H100 Tensor Core GPU introduced Hopper architecture and redefined what enterprise AI hardware could do.
It features 80 GB of high-speed HBM3 memory and up to 3.35 TB/s memory bandwidth, allowing exceptional performance in AI training, HPC workloads, and data analytics.
The H100 also supports NVLink (900 GB/s) for multi-GPU scaling and Multi-Instance GPU (MIG), making it ideal for data centers and cloud environments.
Key specs (SXM version):
- Architecture: Hopper
- Memory: 80 GB HBM3
- Memory Bandwidth: 3.35 TB/s
- Interconnect: NVLink up to 900 GB/s
- Power: Up to 700 W
H200 - Hopper enhanced
The H200 builds on the same Hopper architecture but focuses on removing the biggest performance bottleneck: memory.
It is the first GPU to use HBM3e memory, delivering 141 GB capacity and 4.8 TB/s bandwidth - nearly double the memory and about 40 % faster bandwidth compared to H100.
This means faster training, smoother inference, and better efficiency for large-language models (LLMs) and advanced HPC simulations.
Key specs:
- Architecture: Enhanced Hopper
- Memory: 141 GB HBM3e
- Memory Bandwidth: 4.8 TB/s
- Interconnect: NVLink up to 900 GB/s
- Power: ~700 W (SXM version)
Real-world performance
While the H100 and H200 share the same compute architecture, the H200’s expanded memory and faster bandwidth deliver up to 40-45 % higher throughput in large-model inference tasks, such as Llama 2 70B.
This makes it ideal for organizations running memory-intensive AI or multi-GPU training clusters where bandwidth efficiency drives total cost of ownership.
Which GPU fits your workload?
Use case |
Recommended GPU |
|
Medium-sized model training |
H100 |
|
Large-scale inference and LLMs (70B+) |
H200 |
|
Multi-tenant or cloud environments |
Both |
|
Cost-efficient deployments |
H100 |
|
Maximum performance at scale |
H200 |
Summary
The NVIDIA H200 doesn’t replace the H100 - it extends its capability.
With almost double the memory and a significant bandwidth increase, it’s designed for next-generation AI workloads that demand faster data movement and greater model capacity.
Both GPUs remain fully compatible with NVIDIA’s Hopper software stack, making upgrades simple and seamless.
At Epoka, we help organizations source, configure, and deploy enterprise GPUs - including the latest NVIDIA H100 and H200 - to power AI, HPC, and data-driven innovation. If you’d like to learn more or discuss your next project, contact us here.
