The NVIDIA HGX H100 is one of the most widely deployed GPU platforms in AI. Built on the Hopper architecture, it has been used extensively across enterprise AI, cloud providers, and research institutions for training, inference, and high-performance computing workloads. Its software ecosystem, tooling support, and operational track record are unmatched.
H100 system availability varies based on market conditions. Arc Compute sources and validates systems through trusted secondary market suppliers and partner networks.
At the core of each H100 system is the NVIDIA HGX H100 8-GPU baseboard, built on the Hopper architecture. It is the platform that defined the current era of GPU-accelerated AI, with a proven track record across thousands of production deployments worldwide.
Eight NVIDIA Hopper GPUs per node, optimized for both AI training and inference with strong performance across a wide range of model architectures.
80 GB HBM3 per GPU, providing the memory capacity and bandwidth needed for large models and high-throughput data pipelines.
Fourth-generation NVLink with NVSwitch for high-speed, all-to-all GPU communication within each node, minimizing data movement bottlenecks.
The most battle-tested GPU platform in AI, with an extensive software ecosystem and operational track record across enterprise, cloud, and research environments.
Train large-scale models on a platform with deep software support and a proven operational track record. The H100 remains a strong choice for organizations running established training pipelines and frameworks that are already optimized for Hopper.
Serve models in production with reliable throughput and low latency. The HGX H100 handles real-time inference for LLMs, vision models, and multi-modal pipelines, backed by mature tooling and broad framework compatibility.
Run compute-intensive simulations, molecular dynamics, climate modeling, and other HPC workloads that benefit from dense GPU compute, high memory bandwidth, and the extensive HPC software ecosystem built around Hopper.
