NVIDIA H100 vs. NVIDIA H200 Comparison: Which GPU Fits Your AI and Data Center Needs?
NVIDIA’s Hopper architecture has redefined AI and HPC capabilities. The NVIDIA H100 set high standards, and the recently launched H200 takes it further with major upgrades in memory, bandwidth, and efficiency. The following comparison tables highlight the differences to help you decide which GPU is best suited for your advanced AI and data-heavy workloads.
GPU Overview and Architecture: NVIDIA H100 vs. H200
Feature | NVIDIA H100 | NVIDIA H200 |
Architecture | Hopper | Enhanced Hopper |
Release Date | 2022 | 2024 |
CUDA Cores | 16,896 | Estimated 20,000+ |
Tensor Cores | 528 | Enhanced Tensor Cores |
Memory | 80GB HBM3 | 141GB HBM3e |
Memory Bandwidth | 3.35 TB/s | 4.8 TB/s |
Processing Power | Up to 67 TFLOPS (FP32) | Up to 80 TFLOPS (FP32) |
Description | Designed for high-demand applications like large-scale simulations, complex data analytics, and AI model training | Increased memory and bandwidth make it suitable for real-time AI inference, large language models, and HPC tasks |








