Nvidia A100 H100 Cloud Servers

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NVIDIA A100 & H100 GPU specifications

Compare the technical specifications of our NVIDIA Ampere A100 and Hopper H100 GPU servers to find the perfect match for your AI and HPC workloads.

NVIDIA A100

The Nvidia A100 GPUs offers the performance, scalability, and efficiency necessary for AI and deep learning applications, making it an excellent option for businesses and researchers looking for cutting-edge computational power.

Architecture

Ampere

Video memory

40GB / 80GB HBM2

CUDA cores

6912 pcs.

Max Bandwidth

1.6 TB/s

NVIDIA H100

The latest released NVIDIA H100 GPU offers unprecedented performance, scalability, and security for various workloads. It is at least two times faster than its predecessor, the A100 GPU.

Architecture

Hopper

Video memory

80GB HBM3

CUDA cores

8448 pcs.

Max Bandwidth

3 TB/s

Perfect for AI, deep learning, and visualization

Enterprise-grade NVIDIA GPU servers built on Ampere and Hopper architectures, delivering exceptional performance for deep learning, AI inference, and HPC workloads.

Ampere infrastructure

With 54 billion transistors, the NVIDIA Ampere architecture is one of largest 7 nanometer chips ever built.

High-bandwidth memory

HBM2 is designed to offer quick and effective data access, with memory bandwidth of up to 1.6 TB/s.

AI and Deep Learning

The Nvidia A100 is specifically designed for artificial intelligence and deep learning applications, delivering up to 20 times the performance of previous-generation GPUs.

Ray tracing

Experience real-time ray tracing, ideal for demanding visualization tasks. The A100 GPU delivers the rendering power needed for realistic and immersive visuals.

NVLink support

Utilize the capabilities of 3rd-generation NVLink for lightning-fast data transfers up to 10x to 20x faster than PCI-Express.

Multi-interface GPU

Empower each A100 GPU to simultaneously run seven distinct and isolated applications or user sessions.

FAQ about NVIDIA A100 H100 GPU servers

Common questions about deploying and managing your NVIDIA A100 H100 GPU-accelerated servers for AI, machine learning, and deep learning workloads.

What makes NVIDIA A100 and H100 GPUs ideal for AI and machine learning?

NVIDIA A100 and H100 GPUs are purpose-built for AI, machine learning, and deep learning workloads. The A100, powered by Ampere architecture, delivers up to 20x the performance of previous generations with Tensor Cores optimized for mixed-precision training. The H100, featuring Hopper architecture, provides 2x faster performance than A100 with enhanced Transformer Engine for large language models and advanced tensor operations for training and inference at scale.

How long does it take to deploy an A100 or H100 GPU server?

Instant A100 configurations are delivered within 5 minutes with your verified payment. Your GPU dedicated server includes instant OS reload capabilities, allowing you to iterate quickly without re-opening support tickets. Our network routes are optimized for always-on workloads and high-throughput data transfer, ensuring immediate productivity.

What is the difference between A100 and H100 GPUs?

The A100 features 40GB/80GB HBM2 memory, 6912 CUDA cores, and 1.6 TB/s bandwidth with Ampere architecture. The H100 offers 80GB HBM3 memory, 8448 CUDA cores, and 3 TB/s bandwidth with next-generation Hopper architecture. H100 delivers 7x higher HPC performance and 2x faster AI training compared to A100, with advanced features like Transformer Engine, second-generation MIG technology, and support for connecting up to 256 GPUs via NVLink Switch System.

What connectivity and scalability options are available?

Our NVIDIA GPU servers support NVLink technology for high-speed GPU-to-GPU communication - 3rd-generation NVLink on A100 provides 10x-20x faster transfers than PCIe, while H100 supports advanced NVLink Switch System for connecting up to 256 GPUs. Both A100 and H100 feature Multi-Instance GPU (MIG) technology, allowing secure partitioning into up to seven isolated instances for maximum resource utilization and workload flexibility.