NVIDIA DGX H100 for high-performance AI training, inference and HPC
NVIDIA H100 SXM5/HBM3 GPU infrastructure with 1 to 8 GPUs, up to 640 GB of VRAM, AMD Genoa or Intel Platinum CPUs and high-speed peer-to-peer interconnect for demanding AI workloads.
H100 Cloud GPU for AI workloads that need consistent performance
NVIDIA DGX H100 is built for AI training, fine-tuning, inference and HPC workloads that need powerful GPUs, large VRAM and multi-GPU scaling.
NVIDIA DGX H100
H100 GPU infrastructure for AI training, fine-tuning, inference, HPC and large-data workloads.
H100 SXM5/HBM3 80 GB
H100 80 GB VRAM options from a single GPU to a full 8-GPU node, covering a range of deployment sizes.
AMD Genoa / Intel Platinum
High-performance CPUs balance the data pipeline, preprocessing and parallel compute tasks.
P2P 900 GB/s
The multi-GPU plans support high-speed peer-to-peer interconnect for distributed training and inference.
Choose an H100 configuration by AI workload scale
| Service plans | Price/month | GPU | CPU | Core | RAM | VRAM | Actions |
|---|---|---|---|---|---|---|---|
| 1H100.80S.30V | 111,583,930 VND/month | 1 GPU | AMD Genoa | 24 Core | 240 GB RAM | 80 GB VRAM | Sign up |
| 2H100.80S.80V | 86,508,000 VND/month | 2 GPU | AMD Genoa | 80 Core | 370 GB RAM | 160 GB VRAM | Sign up |
| 4H100.80S.176V | 173,016,000 VND/month | 4 GPU | AMD Genoa | 176 Core | 740 GB RAM | 320 GB VRAM | Sign up |
| 8H100.80S.176V | 346,032,000 VND/month | 8 GPU | AMD Genoa | 176 Core | 1480 GB RAM | 640 GB VRAM | Sign up |
| Service plans | GPU | CPU | Core | RAM | VRAM | Connectivity | Disk | Notes | Price/month | Actions |
|---|---|---|---|---|---|---|---|---|---|---|
| 1H100.80S.30V | 1 GPU | AMD Genoa | 24 Core | 240 GB RAM | 80 GB VRAM | P2P: No | 3500 GB | Visible product • Single GPU ready | 111,583,930 VND/month | Sign up |
| 2H100.80S.80V | 2 GPU | AMD Genoa | 80 Core | 370 GB RAM | 160 GB VRAM | P2P 900 GB/s | 512 GB Up to | Visible product • Dual GPU ready | 86,508,000 VND/month | Sign up |
| 4H100.80S.176V | 4 GPU | AMD Genoa | 176 Core | 740 GB RAM | 320 GB VRAM | P2P 900 GB/s | 512 GB Up to | Visible product • Training scale | 173,016,000 VND/month | Sign up |
| 8H100.80S.176V | 8 GPU | AMD Genoa | 176 Core | 1480 GB RAM | 640 GB VRAM | P2P 900 GB/s | 512 GB Up to | Visible product • Full-node AI compute | 346,032,000 VND/month | Sign up |
Applies to all plans
- H100 SXM5 80 GB
- AMD Genoa
Optimized for AI, HPC, and compute-intensive workloads
NVIDIA DGX H100 offers options from a single GPU to a full multi-GPU node, so you can scale with each stage of an AI product.
Ready for LLMs
Suited to fine-tuning, inference, RAG, embeddings and large language model experimentation.
Multi-GPU scaling
Choose 1, 2, 4 or 8 H100 GPUs to suit needs from development through to production.
Flexible configuration range
Several HGX, HBM3 and DGX H100 Cloud product groups are available on different billing terms.
Up to 640 GB VRAM
The 8-GPU configurations provide large total VRAM for big batches, large models and high-load inference.
Dedicated GPU
The dedicated products suit environments that need steady performance and isolated resources.
Deployment support
HiTechCloud advises on configuration, runtime environment, drivers and the right AI framework.
Deployment scenarios suited to the NVIDIA DGX H100
Deploy the H100 for chatbots, RAG, embeddings, recommendations and production AI applications.
The 4–8 GPU plans support training, distributed training and large-scale AI pipelines.
Accelerate HPC, rendering, simulation, data analysis and demanding engineering applications.
High-performance GPU instances for a wide range of workloads
Powerful capacity, optimized to accelerate AI/ML and high-performance workloads at any scale.
A broad range of infrastructure options
Training, inference, or fine-tuning - HiTechCloud offers a range of GPUs to match your needs, with transparent pricing and on-demand deployment environments.
Built to NVIDIA reference architecture
HiTechCloud GPU instances combine NVLink/PCIe, InfiniBand (RDMA), and RAIL topology to optimize AI/HPC performance.
Three core connectivity layers for high-performance GPU clusters
A network and GPU fabric designed so AI workloads scale reliably, easing bandwidth bottlenecks and holding performance at scale.
NVLink / PCIe Switch
High-speed GPU-to-GPU connectivity within and between nodes, reducing bottlenecks during model training.
InfiniBand (RDMA)
Low-latency connectivity optimized for distributed training and reduced processing load on the host.
RAIL Topology
A parallel network architecture delivering higher bandwidth, redundancy, and consistent performance at any scale.
GPU auto scaling and utilization optimization
From a single GPU to large clusters, HiTechCloud provisions resources ahead of demand and gets the most out of every instance.
Auto scaling with Kubernetes
Automatically scale GPU resources from small scale to thousands of GPUs, with forecasting and Provisioning capability before you need it.
Security for every access connection
Access over SSH, TCP, and HTTP with built-in protection layers that keep enterprise data safe and access fully controlled.
Optimize GPU utilization with MIG
Partition a single GPU into multiple independent instances to run AI workloads in parallel, improving utilization and lowering infrastructure cost.
Transparent pricing, no hidden fees
From large-scale Training to real-time inference — pay only when you actually run, with a GPU Cloud platform built to serve every AI workload and high performance requirement.
Ready to run your first GPU instance?
From register to GPU instance launch in under 5 minutes — no complex setup, no resource reservation, no idle fees. Just deploy, run, and pay for what you use.
More than just Compute, you can manage, scale and develop entirely within a simple cloud ecosystem.
AgentBase
A complete management platform for deploying and operating AI agents securely at scale on enterprise-grade infrastructure.
Explore AgentBaseAI Platform
A unified platform for training, fine-tuning, and deploying AI models at any scale.
Explore AI PlatformVector Database
Supports fast search, real-time analytics, log and large-scale event data, and vector databases for RAG.
Explore Vector DatabaseKubernetes
Managed Kubernetes for container orchestration, AI services, and GPU cloud workloads.
Explore KubernetesScale with confidence across Southeast Asia
Deploy systems and applications closer to your users, reducing latency and meeting local regulatory requirements.
Bangkok
BKK-01
Ho Chi Minh
HCM-01 · HCM-02 · HCM-03
Ha Noi
HAN-01 · HAN-02
A partner for your digital transformation journey
Large enterprises and fast-growing startups choose HiTechCloud for secure, high-performance AI cloud solutions that let them innovate and scale.
Does your enterprise have a specific challenge? HiTechCloud is ready to support.
The HiTechCloud team advises on GPU architecture, networking, security, and an operating model matched to your real workloads.
FAQ
Quick facts before choosing an NVIDIA DGX H100 configuration at HiTechCloud.
Which workloads is the NVIDIA DGX H100 suited to?
Suited to AI training, fine-tuning, inference, HPC, simulation, rendering and any workload that needs high-performance H100 GPUs.
Should I choose one GPU or several?
1 GPU suits experimentation, small fine-tuning runs and inference. 2, 4 or 8 GPUs suit training, high-load inference and large models.
What billing cycles are available?
Depending on the product, terms of 1 day, 1 week, 1 month, 3 months, 6 months, 12 months and longer are available.
Is the DGX H100 suitable for LLMs and generative AI?
Yes. The DGX H100 suits training, fine-tuning, LLM inference, generative AI, computer vision and HPC workloads that need high performance.
When should you choose the DGX H100 over a standard GPU?
When the workload needs large VRAM, high bandwidth, multiple GPUs, shorter training times, and a stable data center environment.
Which framework environments does HiTechCloud support?
HiTechCloud advises on CUDA, drivers, PyTorch, TensorFlow, containers, storage, and the runtime that fits your AI pipeline.
Can you advise on a configuration to fit our budget?
Yes. HiTechCloud helps you choose the GPU count, CPU cores, RAM, storage and rental term to match both technical goals and budget.
Need consultation on NVIDIA DGX H100 configuration for your AI workload?
HiTechCloud helps you select the GPU count, VRAM, CPU cores, storage, runtime environment, and an operating plan that fits your budget.




























































































































