Topic hub
NVIDIA H100, H200, B200 and GB200: The Accelerator Generations
NVIDIA's data-center accelerators set the pace of the AI infrastructure market. This hub explains how the Hopper (H100, H200) and Blackwell (B200, GB200) generations relate, without repeating vendor benchmark claims.
Hopper: H100 and H200
The H100 became the workhorse of large-model training and remains widely available across GPU clouds. The H200 uses the same Hopper architecture but pairs it with more high-bandwidth memory (HBM3e) and higher memory bandwidth, which benefits memory-bound workloads such as large-model inference.
Blackwell: B200 and GB200
Blackwell is the next architecture. The B200 is the GPU itself; GB200 refers to a superchip combining Blackwell GPUs with an NVIDIA Grace CPU, deployed in rack-scale systems such as the GB200 NVL72 with a large NVLink domain.
Rack-scale Blackwell systems require substantially more power and liquid cooling, which is why their rollout is tied closely to data-center readiness.
How buyers choose
The right choice depends on workload, budget and availability rather than the newest part alone.
- Memory needs: larger models and long contexts favour more HBM.
- Scale: multi-node training depends heavily on interconnect.
- Availability and lead time: older generations are usually easier to obtain.
- Facility readiness: rack-scale systems need matching power and cooling.
Frequently asked questions
What is the difference between H100 and H200?
Both use NVIDIA's Hopper architecture. The H200 has more and faster HBM memory, which helps memory-bound workloads.
Is GB200 a GPU?
GB200 is a superchip that combines Blackwell GPUs with a Grace CPU. It is typically deployed in rack-scale systems rather than as a single card.
Cite this page
“NVIDIA H100, H200, B200 and GB200: The Accelerator Generations.” GPU Data Hub. https://gpudatahub.com/topics/nvidia-h100-h200-b200-gb200
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