The NVIDIA A30 for AI inference, HPC and specialized GPU workloads
NVIDIA A30 GPU infrastructure in configurations from 1 to 8 GPUs, suited to AI inference, computer vision, light training and GPU data processing.
Dedicated A30 GPU for AI and high-performance computing
The NVIDIA A30 is a balanced option for workloads that need a dedicated GPU, 24 GB of VRAM per GPU, and room to scale from single-GPU to multi-GPU.
NVIDIA A30 GPU
The NVIDIA A30 suits AI inference, light training, HPC and specialized compute workloads.
24 GB VRAM/GPU
Each GPU has 24 GB of VRAM, supporting mid-sized AI models, computer vision and data pipelines.
Scale to 8 GPUs
Choose configurations from 1 to 8 GPUs to match workload size and deployment budget.
Dedicated GPU
Dedicated plans, suited to steady workloads that need isolated resources and consistent performance.
Choose an A30 configuration by AI and HPC scale
| Service plans | Price/month | GPU | Core | RAM | VRAM | P2P | Actions |
|---|---|---|---|---|---|---|---|
| A30 x1 | 6,415,200 VND/month | 1 GPU | 16 Core | 48 GB RAM | 24 GB VRAM | P2P: No | Sign up |
| A30 x2 | 12,830,400 VND/month | 2 GPU | 30 Core | 96 GB RAM | 48 GB VRAM | P2P: No | Sign up |
| A30 x4 | 25,660,800 VND/month | 4 GPU | 50 Core | 192 GB RAM | 96 GB VRAM | P2P: No | Sign up |
| A30 x8 | 51,321,600 VND/month | 8 GPU | 94 Core | 384 GB RAM | 192 GB VRAM | P2P: No | Sign up |
| Service plans | GPU | Core | RAM | VRAM | P2P | Disk | Type | Notes | Price/month | Actions |
|---|---|---|---|---|---|---|---|---|---|---|
| A30 x1 | 1 GPU | 16 Core | 48 GB RAM | 24 GB VRAM | P2P: No | 256 GB Up to | Dedicated | NVIDIA A30 Dedicated GPU | 6,415,200 VND/month | Sign up |
| A30 x2 | 2 GPU | 30 Core | 96 GB RAM | 48 GB VRAM | P2P: No | 512 GB Up to | Dedicated | NVIDIA A30 Dedicated GPU | 12,830,400 VND/month | Sign up |
| A30 x4 | 4 GPU | 50 Core | 192 GB RAM | 96 GB VRAM | P2P: No | 1024 GB Up to | Dedicated | NVIDIA A30 Dedicated GPU | 25,660,800 VND/month | Sign up |
| A30 x8 | 8 GPU | 94 Core | 384 GB RAM | 192 GB VRAM | P2P: No | 2048 GB Up to | Dedicated | NVIDIA A30 Dedicated GPU | 51,321,600 VND/month | Sign up |
Applies to all plans
- NVIDIA A30
- Dedicated
Optimized for AI inference, HPC and computer vision
The NVIDIA A30 offers flexible dedicated GPU configurations for workloads that need consistent performance at a reasonable cost.
Optimized for AI inference
The A30 handles inference, model serving, computer vision and AI data processing workloads well.
Cost-effective
Suited to projects that need a dedicated GPU but want lower cost than higher-end options.
Multiple GPU tiers
Choose 1, 2, 4 or 8 GPUs to scale parallel capacity as needed.
Large aggregate VRAM
The 8-GPU configuration provides 192 GB of total VRAM for multi-batch or large-data workloads.
Flexible billing cycles
Billing cycles from 1 month to 60 months.
Deployment support
HiTechCloud advises on drivers, CUDA, AI frameworks, and the configuration that fits your workload.
Deployment scenarios suited to the NVIDIA A30
Deploy inference APIs, chatbots, embeddings, OCR and production AI pipelines.
Image processing, video analytics, object detection and computer vision workloads.
Accelerate computation, simulation, data analysis and specialized GPU workloads.
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 A30 configuration at HiTechCloud.
Which workloads is the NVIDIA A30 suited for?
Suited to AI inference, model serving, computer vision, light training, HPC and GPU data processing.
When should you choose A30 x4 or x8?
Choose a multi-GPU configuration when you need parallel processing, large batches, many inference tasks or greater total VRAM.
Is the A30 suitable for model serving?
Yes. The A30 suits model serving, batch inference, computer vision and AI APIs that need high reliability.
How does the A30 differ from the A10G?
The A30 is generally the better fit for data center workloads, inference and steady GPU compute; the A10G is better suited to general-purpose and media workloads.
How should data be prepared for running on the A30?
Keep datasets, model weights and checkpoints on high-speed storage to reduce data loading time and speed up batch processing.
What billing cycles are available?
Plans are available on 1-month, 3-month, 6-month, 12-month, and long-term cycles.
Need consultation on NVIDIA A30 configuration for your workload?
HiTechCloud helps you choose the number of GPUs, cores, RAM, storage, driver, CUDA and framework for your deployment.




























































































































