Skip to main content
Powered by eight NVIDIA H200 Hopper GPUs, each equipped with 141 GB of ultra-fast HBM3e memory, these instances are purpose-built for memory-intensive AI and HPC workloads. The significant memory per GPU allows for training larger models with bigger batch sizes and longer context windows compared to its predecessor. The GPUs are interconnected with NVIDIA NVLink for a high-speed, unified memory pool within the server. For clustering, they feature NVIDIA ConnectX-7 adapters providing a 400G NDR InfiniBand fabric, making them ideal for large, distributed training jobs that are memory-bound.

​
Specifications

​
Primary use cases

Training and fine-tuning large models (~70B parameters) with high precision, high-throughput inference with long context lengths, and memory-intensive scientific computing. Full precision versions of the latest open-source models such as DeepSeek V4 Flash, Qwen 3.5 397B-A17B, Kimi K2.6, MiniMax M2.7 and other large models requiring substantial GPU memory for a single Node.
Last modified on June 23, 2026