It feels like a long time since NVIDIA revealed the H200 GPU back in November 2023. Since then, we’ve already learned about AMD’s MI300X and the upcoming Blackwell architecture. Not to mention, NVIDIA stock price has gone through the roof!
You don’t have to wait much longer, you can already pre-order H200 clusters on DataCrunch today.
Let’s go through what you can expect – and most importantly what we can expect from that massive increase to VRAM and memory bandwidth in the H200 in terms of machine learning training and inference use cases.
What is the NVIDIA H200
The NVIDIA H200 is a Tensor Core GPU specifically designed to be used in high performance computing and AI use-cases. It’s based on the Hopper-architecture which was itself was released in the second half of 2022.
The H200 builds upon the success of NVIDIA's previous flagship GPU, the H100, by introducing significant advancements in memory capacity, bandwidth, and energy use performance. These improvements position the H200 as the market-leading GPU for generative AI, large language models, and memory-intensive HPC applications.
Full H200 vs H100 Specs Comparison
Technical Specifications | H100 SXM | H200 SXM |
|---|---|---|
Form Factor | SXM5 | SXM5 |
FP64 | 34 TFLOPS | 34 TFLOPS |
FP64 Tensor Core | 67 TFLOPS | 67 TFLOPS |
FP32 | 67 TFLOPS | 67 TFLOPS |
TF32 Tensor Core* | 989 TFLOPS | 989 TFLOPS |
BFLOAT16 Tensor Core* | 1,979 TFLOPS | 1,979 TFLOPS |
FP16 Tensor Core* | 1,979 TFLOPS | 1,979 TFLOPS |
FP8 Tensor Core* | 3,958 TFLOPS | 3,958 TFLOPS |
INT8 Tensor Core* | 3,958 TFLOPS | 3,958 TFLOPS |
GPU Memory | 80 GB | 141 GB |
GPU Memory Bandwidth | 3.35 TB/s | 4.8 TB/s |
Max Thermal Design Power (TDP) | Up to 700W (configurable) | Up to 700W (configurable) |
Multi-Instance GPUs | Up to 7 MIGs @10GB each | Up to 7 MIGs @16.5GB each |
Interconnect | NVIDIA NVLink®: 900GB/s; PCIe Gen5: 128GB/s | NVIDIA NVLink®: 900GB/s; PCIe Gen5: 128GB/s |
* With sparsity.
Overall, the H200 is expected to be an upgraded version of the H100 retaining a similar range of computational capabilities (FP64 to INT8) with a much faster and more efficient performance due to the VRAM upgrades.
Memory and Bandwidth Upgrade
At the heart of the H200's performance is its 141GB of HBM3e (High-Bandwidth Memory) which is delivered at 4.8TB/s of memory bandwidth. In comparison, the previous-generation H100 GPU featured 80GB of HBM3 memory with a respectable 3.3TB/s of bandwidth.
Expected impact on ML use cases
This massive increase in memory capacity and bandwidth is a big deal for AI and HPC workloads. For example, the H200 can deliver 2x the inference performance on the 70 billion parameter Llama2 model compared to the H100 GPU.
Beyond LLM inference, the H200 also delivers impressive gains in other AI domains, such as generative AI and training throughput. On the new graph neural network (GNN) test based on R-GAT, the H200 delivered a 47% boost on single-node GNN training compared to the H100.
Impact on Thermal Design Power (TDP)
The H200 achieves performance improvements while maintaining the same power profile as the H100. While this doesn’t sound like an upgrade, the expected performance-per-watt for computing power will be significantly better.
NVIDIA estimates that the energy use of the H200 will be up to 50% lower than the H100 for key LL inference workloads, resulting in a 50% lower total cost of ownership over the lifetime of the device.
Bottom line on the H200
If you feel like a kid waiting for Christmas, you’re not alone. The H200 has ideal specifications to advance machine learning and high-performance computing to new levels, and it’s going to be some time before another GPU is available with superior performance and cost-efficiency levels.
The H200 addresses the key compute efficiency issues of the H100, meaning that you will get higher memory bandwidth at a lower performance-per-watt.
The good news is that you don’t have to wait much longer. You can pre-order a cluster of H200s on DataCrunch, or subscribe to get updates on availability.