Partner Spotlight: Evaluating NVIDIA H200 Tensor Core GPUs for AI Inference with Baseten

The NVIDIA H200 Tensor Core GPU is a data center-grade GPU designed for large-scale AI workloads, offering more GPU memory while maintaining a similar compute profile as the widely-used NVIDIA H100 GPU. The H200 is highly anticipated for tasks like training, fine-tuning, and long-duration AI processes, but its performance in inference jobs was tested by Baseten. While the H200 GPUs are good choices for large models, large batch sizes, and long input sequences, they offer minimal performance improvements over H100s outside of these situations, making them less cost-efficient for some inference tasks. The GPU's specs include 76% more VRAM at a 43% higher memory bandwidth than the H100 SXM, but its performance in certain workloads is comparable to or better than that of the H100. Baseten tested the H200 GPUs on an 8xH200 cluster and found them to be well-suited for large models, large batch sizes, and long input sequences, offering significant performance improvements in these areas. However, their performance in shorter context and output workloads is comparable or slightly better than that of the H100. Overall, the H200 GPUs are incredibly powerful and capable GPUs for a wide variety of AI/ML tasks, especially training and fine-tuning, but may not be the best choice for all inference tasks due to their higher cost per hour compared to H100s.

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