NVIDIA V100 for cost-optimized AI, inference and HPC
NVIDIA Tesla V100 16 GB/32 GB GPU infrastructure in configurations from 1 to 8 GPUs, suited to AI inference, training, HPC and rendering.
V100 Cloud GPU for AI workloads that need consistent performance
The NVIDIA V100 is a good fit for inference, training, HPC and rendering when you need a stable GPU, sufficient VRAM and controlled cost.
NVIDIA V100 GPU
The V100 GPU for AI inference, training, HPC and compute-intensive workloads.
Tesla V100 16 GB/32 GB
V100 16 GB and V100 32 GB configurations are available at various GPU counts.
NVLink P2P
The multi-GPU configurations support NVLink at up to 50 GB/s for fast data exchange.
Up to 128 GB VRAM
Options from 16 GB to 128 GB of VRAM for AI models, rendering and HPC.
Choose a V100 configuration by AI workload scale
| Service plans | Price/month | GPU | CPU | Core | RAM | VRAM | Actions |
|---|---|---|---|---|---|---|---|
| 1V100.6V | 3,110,400 VND/month | 1 GPU | Intel Xeon Gold 6342 | 6 Core | 23 GB RAM | 16 GB VRAM | Sign up |
| 2V100.10V | 6,415,200 VND/month | 2 GPU | Intel Xeon Gold 6342 | 10 Core | 45 GB RAM | 32 GB VRAM | Sign up |
| 4V100.20V | 12,830,400 VND/month | 4 GPU | Intel Xeon Gold 6342 | 20 Core | 90 GB RAM | 64 GB VRAM | Sign up |
| 8V100.48V | 25,660,800 VND/month | 8 GPU | Intel Xeon Gold 6342 | 48 Core | 180 GB RAM | 128 GB VRAM | Sign up |
| V100 32G | 45,489,600 VND/month | 1 GPU | Intel Xeon Gold 6342 | 8 Core | 30 GB RAM | 32 GB VRAM | Sign up |
| V100 32G x2 | 90,979,200 VND/month | 2 GPU | Intel Xeon Gold 6342 | 16 Core | 60 GB RAM | 64 GB VRAM | Sign up |
| V100 32G x4 | 181,958,400 VND/month | 4 GPU | Intel Xeon Gold 6342 | 32 Core | 120 GB RAM | 128 GB VRAM | Sign up |
| Service plans | GPU | CPU | Core | RAM | VRAM | Connectivity | Disk | Notes | Price/month | Actions |
|---|---|---|---|---|---|---|---|---|---|---|
| 1V100.6V | 1 GPU | Intel Xeon Gold 6342 | 6 Core | 23 GB RAM | 16 GB VRAM | P2P: No | 512 GB Up to | NVIDIA Tesla V100 16 GB server | 3,110,400 VND/month | Sign up |
| 2V100.10V | 2 GPU | Intel Xeon Gold 6342 | 10 Core | 45 GB RAM | 32 GB VRAM | NVLink up to 50 GB/s | 512 GB Up to | NVIDIA Tesla V100 16 GB multi-GPU server | 6,415,200 VND/month | Sign up |
| 4V100.20V | 4 GPU | Intel Xeon Gold 6342 | 20 Core | 90 GB RAM | 64 GB VRAM | NVLink up to 50 GB/s | 512 GB Up to | NVIDIA Tesla V100 16 GB multi-GPU server | 12,830,400 VND/month | Sign up |
| 8V100.48V | 8 GPU | Intel Xeon Gold 6342 | 48 Core | 180 GB RAM | 128 GB VRAM | NVLink up to 50 GB/s | 512 GB Up to | NVIDIA Tesla V100 16 GB high-density server | 25,660,800 VND/month | Sign up |
| V100 32G | 1 GPU | Intel Xeon Gold 6342 | 8 Core | 30 GB RAM | 32 GB VRAM | NVLink up to 50 GB/s | 250 GB Up to | NVIDIA V100 32G server | 45,489,600 VND/month | Sign up |
| V100 32G x2 | 2 GPU | Intel Xeon Gold 6342 | 16 Core | 60 GB RAM | 64 GB VRAM | NVLink up to 50 GB/s | 250 GB Up to | NVIDIA V100 32G multi-GPU server | 90,979,200 VND/month | Sign up |
| V100 32G x4 | 4 GPU | Intel Xeon Gold 6342 | 32 Core | 120 GB RAM | 128 GB VRAM | NVLink up to 50 GB/s | 250 GB Up to | NVIDIA V100 32G multi-GPU server | 181,958,400 VND/month | Sign up |
Applies to all plans
- Intel Xeon Gold 6342
Optimized for AI, inference and compute-intensive workloads
NVIDIA V100 offers options from single GPU to multi-GPU, scaling with your AI and HPC deployment needs.
Cost-efficient
The V100 suits workloads that need a powerful GPU on a smaller budget than newer generations.
Various GPU counts
Choose 1, 2, 4 or 8 GPUs based on inference, training and parallel processing needs.
CPU Xeon Gold
The configuration uses Intel Xeon Gold 6342 CPUs, with RAM and storage balanced for GPU workloads.
NVLink cho multi-GPU
The multi-GPU plans include peer-to-peer NVLink to accelerate workloads with GPU-to-GPU traffic.
Flexible billing cycles
Billing cycles from 1 month to 60 months.
Operational support
HiTechCloud advises on drivers, runtime, AI frameworks and the right configuration.
Deployment scenarios suited to the NVIDIA V100
Deploy the V100 for model training, fine-tuning, embeddings and AI applications.
Optimized for inference, batch processing and production AI services at a reasonable cost.
Accelerate simulation, rendering, scientific computing, and data-intensive processing.
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 V100 configuration at HiTechCloud.
Which workloads is the NVIDIA V100 suited for?
Suited to AI training, fine-tuning, inference, HPC, rendering and workloads that need a reliable GPU at controlled cost.
Should you choose the V100 16 GB or the V100 32 GB?
V100 16 GB suits inference, experimentation and small training runs. V100 32 GB suits workloads that need more VRAM.
Is the V100 still suitable for AI today?
Yes. The V100 still suits mid-sized training, inference, HPC, data science, and workloads that need a data center GPU at a lower cost.
When should you choose the V100 over the A100?
Choose the V100 when the workload does not require A100 performance but still needs a stable GPU for AI, HPC, or mid-sized experiments.
Does HiTechCloud support migrating V100 workloads?
Yes. HiTechCloud advises on the CUDA environment, frameworks, containers and how to move workloads onto cloud GPU.
What billing cycles are available?
Plans are available on 1-month, 3-month, 6-month, 12-month, and long-term cycles.
Need configuration advice for NVIDIA V100 AI Workload?
HiTechCloud helps you choose the GPU count, VRAM, CPU cores, storage, runtime, and framework that fit your budget.




























































































































