NVIDIA HGX H100
and H200 Tensor Core GPUs

These GPUs excel in:

• AI model training & inference
• Natural language processing (NLP)
• Large-scale data analytics
• Scientific computing
• High-performance computing
• High-frequency trading (HFT)

Yes, Vultr offers on-demand NVIDIA H100 GPUs, allowing businesses and developers to scale AI workloads without investing in expensive hardware.

You can deploy NVIDIA H100 GPUs in just a few clicks via Vultr’s cloud platform. Simply choose the GPU instance that fits your needs and start running your AI or HPC workloads immediately.

• H100 GPU: Up to 80GB HBM3 memory
• H200 GPU: Features higher memory bandwidth and more capacity than the H100, making it even more powerful for large-scale AI applications

These GPUs offer low-latency inference performance with FP8 Tensor Cores, making them ideal for real-time AI applications like chatbots, voice assistants, and recommendation engines.

Yes, Vultr supports multi-GPU clusters using NVIDIA H100 & H200 GPUs, enabling faster AI model training and inference across multiple nodes.

NVIDIA H100 and H200 GPUs are high-performance GPUs designed for AI, deep learning, and high-performance computing (HPC). They feature Tensor Cores optimized for machine learning workloads, offering superior speed and efficiency compared to previous generations.

Tensor Cores are specialized AI cores in NVIDIA GPUs that accelerate matrix multiplications, a key operation in deep learning. This technology enables faster AI model training and inference, significantly boosting performance for machine learning applications.

The NVIDIA H100 introduces FP8 precision and the Transformer Engine, which deliver up to 4x faster training and inference for transformer-based models like GPT and BERT. FP8 enables smaller data formats with minimal accuracy loss, while the Transformer Engine dynamically chooses the optimal precision for each layer – ideal for large-scale deep learning on Vultr’s cloud infrastructure.

The H100 offers exceptional performance for training large AI models, while the H200 builds on that with expanded memory and bandwidth, which is ideal for inference at scale. On Vultr, H100 instances start at $2.30/GPU/hour, making them a cost-efficient option for training workloads. The H200 justifies its premium for memory-bound inference tasks with higher throughput and latency reduction.

Both H100 and H200 support Multi-Instance GPU (MIG), allowing up to seven isolated GPU instances per physical GPU. This enables better utilization, isolation, and security across AI, ML, and HPC workloads. On Vultr’s cloud GPU hosting platform, MIG makes it easy to allocate right-sized GPU resources without overprovisioning.

Yes – paired with Vultr’s globally distributed infrastructure, H100 and H200 GPUs deliver low-latency AI inference capabilities close to end-users. These GPUs are well-suited for edge inference workloads such as video analytics, recommendation engines, and speech recognition, where real-time performance and availability across global regions are critical.