Comparison

NVIDIA H100 vs NVIDIA H200

Same compute, 76% more memory

The H200 upgrades the H100's 80GB HBM3 to 141GB HBM3e while maintaining identical 990 FP16 TFLOPS compute. The H200 excels at memory-bound workloads like large model inference.

Pricing Comparison

Specifications

Specification	NVIDIA H100	NVIDIA H200
Manufacturer	NVIDIA	NVIDIA
Architecture	Hopper	Hopper
Accelerator Type	GPU	GPU
Primary Use	training	training
Memory (VRAM)	80 GB	141 GB
FP16 Performance	990 TFLOPS	990 TFLOPS
TDP	700W	700W
Perf per Watt	1.41 TFLOPS/W	1.41 TFLOPS/W

Detailed Analysis

The H200 is not a new architecture — it's a memory-upgraded H100. Both GPUs share the same Hopper architecture and deliver identical 990 FP16 TFLOPS. The difference is entirely in memory: 141GB HBM3e vs 80GB HBM3, with bandwidth increasing from 3.35 TB/s to 4.8 TB/s.

This memory upgrade has significant practical implications. Large language models that required multi-GPU setups on H100 (e.g., 70B parameter models) can fit on fewer H200 GPUs, reducing both cost and inter-GPU communication overhead.

For training, the H200 offers modest improvements through better memory utilisation and bandwidth, but the compute bottleneck remains the same. The real advantage is in inference, where the entire model must reside in GPU memory for efficient serving.

The H200 commands a premium over the H100 but can deliver better total cost of ownership for memory-intensive workloads by reducing the number of GPUs required per deployment.

Verdict

Best for Training

H100 is sufficient for most training. H200 helps when training memory-bound models or using very large batch sizes.

Best for Inference

H200 wins for serving large models (30B+ parameters) where its extra memory reduces the GPU count needed.

Best Value

H100 for compute-bound workloads. H200 when memory is the bottleneck — the memory premium pays for itself through fewer GPUs.

Frequently Asked Questions

Is the H200 faster than the H100?

They have identical compute (990 FP16 TFLOPS). The H200 is faster only on memory-bandwidth-bound workloads due to its 43% higher memory bandwidth (4.8 vs 3.35 TB/s).

How much more memory does the H200 have?

The H200 has 141GB of HBM3e memory vs the H100's 80GB of HBM3 — a 76% increase. This allows it to handle larger models without multi-GPU configurations.