High-performance GPU server, fast deployment, optimized for AI, rendering, training, machine learning and workloads that require graphics processing power.
7-day money-back guarantee if you are not satisfied
Explore GPUs listed in VPTS server configurations, compare memory and choose for AI, rendering or compute.
NVIDIA · Ada Lovelace
AI, image generation and rendering with 24 GB per card.
NVIDIA · Ampere
A 24 GB option for CUDA, AI and rendering projects.
NVIDIA · Ada Lovelace
A 48 GB GPU for AI, video processing and professional graphics.
NVIDIA · Ampere
48 GB of memory for rendering, graphics and compute environments.
NVIDIA · Ada Lovelace
A professional 48 GB RTX GPU for design, AI and rendering.
NVIDIA · Ada Lovelace
A 48 GB RTX Ada GPU for large render scenes and professional applications.
NVIDIA · Ampere
40 GB and 80 GB memory options for AI and intensive computing.
NVIDIA · Hopper
An 80 GB Hopper GPU for AI workloads and memory-intensive models.
NVIDIA · Ampere
24 GB HBM2 for inference, enterprise AI and HPC.
NVIDIA · Volta
A 32 GB V100 with SXM2/NVLink in a dedicated server configuration.
NVIDIA · Pascal
A 24 GB Pascal GPU for compatible CUDA and inference workloads.
VRAM is per GPU and differs from server RAM. Multiple GPUs require software support for workload distribution; configuration and deployment availability are confirmed during consultation.
Price list for 1 month and 12 months is reduced by 15%, including popular GPU configurations for AI, rendering, model training and workloads that require graphics processing power.
Private server with 2 Nvidia Tesla P40 cards
Private server with 2 Nvidia RTX 3090 cards
Enjoy dedicated performance & resource optimization
Private server with 8 Nvidia RTX3090 cards
Private server with 1 Nvidia A30 card
New generation powerful Tensor Core server
New generation powerful Tensor Core server
SXM2 GPU Server - Nvlink Support
New generation powerful Tensor Core server
New generation powerful Tensor Core server
New generation powerful AI server
New generation powerful Tensor Core server
New generation server with L40S GPU
New generation powerful AI server
New generation powerful Tensor Core server
New generation server with A100 40GB GPU
New generation server with A100 80GB GPU
New generation server with H100 80GB GPU
Choose a GPU to explore its architecture, memory, strengths and matching server configurations.
NVIDIA · Ada Lovelace
RTX 4090 combines CUDA with fourth-generation Tensor Cores and third-generation RT Cores. Use it for inference, image processing or GPU rendering, with model size and batch size sized for each card’s VRAM.
NVIDIA · Ampere
RTX 3090 has third-generation Tensor Cores and second-generation RT Cores. VPTS lists servers with 2, 4 or 8 cards; your software must support multiple GPUs to use the configuration effectively.
NVIDIA · Ada Lovelace
L40S combines ECC GDDR6 memory, fourth-generation Tensor Cores and third-generation RT Cores. This data-center GPU serves AI and graphics workloads, with more memory capacity for models and render scenes than the 24 GB group.
NVIDIA · Ampere
A40 offers third-generation Tensor Cores and second-generation RT Cores for data-center visual computing. Consider it for VRAM capacity, rendering or remote workstations; software and related licenses depend on your needs.
NVIDIA · Ada Lovelace
RTX 5880 Ada combines fourth-generation Tensor Cores, third-generation RT Cores and ECC memory. It serves professional graphics, content processing and AI work needing substantial memory on one card.
NVIDIA · Ada Lovelace
RTX 6000 Ada features fourth-generation Tensor Cores and third-generation RT Cores. This is the 48 GB Ada model listed by VPTS; select it for design, simulation, rendering or AI and verify your software’s compatibility.
NVIDIA · Ampere
A100 40 GB uses HBM2, while the 80 GB model uses HBM2e. The GPU offers third-generation Tensor Cores and MIG. VPTS lists both memory sizes; PCIe/SXM variants and CPU, RAM and storage are confirmed for your chosen server.
NVIDIA · Hopper
H100 includes fourth-generation Tensor Cores and a Transformer Engine. The 80 GB PCIe model uses HBM2e and the 80 GB SXM model uses HBM3; confirm the variant, connectivity and server configuration. Memory capacity is one factor alongside software, batch size and model partitioning.
NVIDIA · Ampere
A30 provides 933 GB/s memory bandwidth, third-generation Tensor Cores and MIG. The server catalog includes 1, 2 or 4 A30 cards; VPTS advises on configuration for inference load, data and deployment needs.
NVIDIA · Volta
V100 introduced first-generation Tensor Cores for deep learning and HPC. VPTS lists a four-card V100 32 GB SXM2 server with NVLink. Validate software, frameworks and workload partitioning for your project.
NVIDIA · Pascal
P40 provides 3,840 CUDA cores and 24 GB of GDDR5 memory. VPTS lists a two-card P40 server. For this Pascal-generation GPU, verify the framework, driver and CUDA versions your project requires.
| GPU | Architecture | VRAM per GPU | Memory type | Acceleration |
|---|---|---|---|---|
| GeForce RTX 4090 | Ada Lovelace | 24 GB | GDDR6X | 16,384 CUDA |
| GeForce RTX 3090 | Ampere | 24 GB | GDDR6X | 10,496 CUDA |
| NVIDIA L40S | Ada Lovelace | 48 GB | GDDR6 ECC | 18,176 CUDA |
| NVIDIA A40 | Ampere | 48 GB | GDDR6 ECC | 10,752 CUDA |
| RTX 5880 Ada | Ada Lovelace | 48 GB | GDDR6 ECC | 14,080 CUDA |
| RTX 6000 Ada | Ada Lovelace | 48 GB | GDDR6 ECC | 18,176 CUDA |
| NVIDIA A100 | Ampere | 40 / 80 GB | HBM2 / HBM2e | 3rd-gen Tensor Cores |
| NVIDIA H100 | Hopper | 80 GB | HBM2e / HBM3 | Transformer Engine |
| NVIDIA A30 | Ampere | 24 GB | HBM2 | 3rd-gen Tensor Cores |
| Tesla V100 SXM2 | Volta | 32 GB | HBM2 | 1st-gen Tensor Cores |
| Tesla P40 | Pascal | 24 GB | GDDR5 | 3,840 CUDA |
VRAM is per GPU and differs from server RAM. Multiple GPUs require software support for workload distribution; configuration and deployment availability are confirmed during consultation.
Optimized for AI, deep learning, video rendering, image processing and problems that require GPU acceleration.
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Consulting CPU, RAM and storage according to the right workload to avoid lack of resources or wasted costs.
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Prepare a quick user environment, support installing drivers, frameworks or software as needed.
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The technical team accompanies the implementation, optimization and troubleshooting of operational problems.
Buy nowA GPU server is a server equipped with specialized graphics cards to accelerate parallel computing, AI, rendering and large data processing tasks.
Unlike regular CPU servers, GPU servers are suitable for problems that require thousands of cores to process simultaneously such as model training, inference, video rendering or simulation.
VPTS wants to bring the best operating experience to customers. For more detailed information, you can contact us via Fanpage or ZaloOA.
GPU servers are suitable for AI, machine learning, rendering, simulation and workloads that need continuous graphics processing power. Dedicated GPU resources help shorten job run times, proactively control the software environment, and operate more stably when workloads last many hours.
Train models, run notebooks, process large datasets and test AI algorithms with CUDA, PyTorch or TensorFlow. GPU server helps reduce training time and proactively allocate resources for many testing sessions.
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Accelerate 3D rendering, video, animation or professional graphics workflows. Suitable for studios, design teams and projects that need to export multiple frames, scenes or high-resolution videos.
Buy today Deploying AI services needs to respond quickly, handle many requests and operate stably. Can be used for chatbots, computer vision, OCR, image generation or backend AI production.
Buy today Suitable for simulation, big data analysis, research lab or problems that require GPUs according to the project. Customers can choose the appropriate configuration to balance performance, cost and rental time.
Buy todayVPTS advises on GPU configuration according to the right workload, supports fast deployment and optimizes usage costs.
Configuration is compared with model, scene render, batch size and framework to limit memory shortage at runtime.
Can advise on drivers, CUDA, PyTorch, TensorFlow or rendering software suitable for card and workload.
CPU, RAM and NVMe are considered with GPU to reduce data read and preprocessing latency.
Suitable for testing, training, inference or rendering without investing in a separate GPU hardware.
Rent GPU Server should be chosen according to operational goals, user locations, security requirements and scalability, not just based on lowest price.
Suitable for large databases, game servers, virtualization, storage, proxy nodes or high load workloads requiring long-term stable performance.
Prioritize CPU/RAM according to main workload, NVMe for high I/O and large bandwidth if transferring data frequently.
Prepare OS, IP, firewall, backup, administrative rights, monitoring and troubleshooting procedures before official deployment.
| Situation | Rent GPU Server | Should consider further |
|---|---|---|
| Workload load is continuously high | Private hardware, better predictable performance | VPS is suitable for small loads or needs to scale quickly |
| Needs deep control | Proactive BIOS/IPMI/KVM, RAID, OS and network | Managed server if there is a lack of internal operations team |
| There are many important services | Separate database, app, backup, firewall according to separate architecture | Colocation if hardware is available |
Common questions when using server services at VPTS.
Have. GPU servers are suitable for training, inference, machine learning, deep learning and workloads that need GPU acceleration.
Support can be provided upon request, including GPU drivers, CUDA, frameworks or project runtime environments.
Price depends on the type of GPU, CPU, RAM, storage, rental time and workload, so VPTS advises on quotes according to specific needs.
Consultation can be made according to actual needs and GPU resource status at the time of registration.
Server GPU packages have a 12-month payment option with a 15% discount on the monthly unit price.
Have. Customers can get appropriate administrative access to install the environment, framework, source code, and tools for the project.
Depends on workload. RTX 3090/4090 is suitable for many common AI and rendering problems, A100/H100 is suitable for intensive training, large models or higher computing needs.
Have. Many configurations already have large capacity NVMe SSDs, and VPTS can advise on additional backup or snapshot options according to operational needs.
Centrally monitor and operate Cloud Server with configuration information, IP, resources, security, operation history and service cycles. Important tasks such as changing passwords, upgrading, renewing and monitoring performance are done clearly and conveniently.
Quickly check packet type, number of IPs, supported protocols, operating status, and deadlines to manage multiple Servers more clearly in the same account.
Key numbers that help customers choose VPTS VPS, proxy, hosting, server and digital infrastructure services with confidence.
years deploying and operating digital infrastructure
customers and partners trust the VPTS ecosystem
technical support throughout the service lifecycle
uptime target for business-critical infrastructure
high-speed connectivity for diverse workloads
VPTS GROUP - Technology infrastructure, the foundation for digital growth | Business highlights Feedback from customers running websites, VPS, proxy, hosting and server systems with VPTS.
Stable service, responsive support and configuration advice closely aligned with real operating needs.
The infrastructure is easy to scale and manage, with flexible options for separating workloads by campaign.
The VPS runs our production systems reliably, with clear support whenever resources need checking or upgrading.
Customers with low-performing websites achieved major gains after moving to VPTS VPS infrastructure. A faster, more stable and SEO-ready platform also helps search engines and AI systems discover, understand and recommend their content.
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VPTS.COM previously scored 36 for performance. After moving to a suitable NVMe VPS and optimizing caching, images, CSS and JavaScript, performance reached 100, with SEO and Best Practices also scoring 100. The faster and more stable platform helps search engines and AI systems crawl, understand and surface service content more effectively.
Before using VPTS VPS, DEVTTT scored only 36 for performance, slowing access to its portfolio and web design services. After migrating and optimizing resources, performance reached 100 while accessibility, Best Practices and SEO improved together, creating a stronger foundation for Google and AI tools to discover and evaluate the content.
MAYCHURIENG.VN previously scored only 32 on its former infrastructure. After moving to VPTS VPS and optimizing images, CSS, JavaScript, caching and priority resources, performance rose to 99 while accessibility, Best Practices and SEO reached 100. Faster responses make its server content easier for search engines and AI systems to find and understand.
Before migrating, THUERACK.VN scored 27 for performance, causing slow service pages and weaker engagement. Running on VPTS VPS with optimized images, code and caching raised performance to 99, while the other three Lighthouse categories reached 100. Better speed and structure help Google and AI systems crawl and evaluate the website more effectively.
THUECHODAT.VN previously scored 32 before moving to VPTS VPS. After upgrading the infrastructure and optimizing assets across devices, performance reached 99, accessibility reached 99, and Best Practices and SEO reached 100. The faster, clearer website gives its service content a stronger foundation for traditional and AI search.
ASENRA.VN presents architecture and interior design and construction services. Before moving to VPTS VPS, the site scored only 31 for performance; after upgrading the infrastructure and optimizing images, JavaScript, CSS and internal links, the score rose to 99. Faster loading, stronger stability and clearer structure help Google, AI Overviews and AI search systems crawl, understand and recommend its content to prospective customers.
After moving to VPTS VPS infrastructure and optimizing page resources, TRANAIL.VN improved performance from 70 to 100, while Accessibility, Best Practices and SEO all reached 100. The nail service website now loads faster and more reliably with a clearer structure across mobile and desktop.
You need a powerful GPU but don't want to invest in the hardware yourself from the beginning or have to handle all the electricity, networking, cooling and maintenance yourself.
Renting a GPU Server helps deploy quickly and flexibly according to workload and budget, especially for AI, rendering or research projects that need strong resources in each stage.
VPTS has a variety of GPU options from RTX, A-series to H100 to suit both testing, production and intensive workload needs.
Order ngayServer GPU helps shorten processing time for heavy computing tasks, especially AI, rendering, model training, inference and big data analysis.
VPTS supports choosing appropriate GPU, CPU, RAM and storage to optimize project costs. Customers can start with a sufficient configuration, then expand to more powerful GPU lines as workload increases.
The technical team can advise on the operating environment, drivers, CUDA, AI framework and storage options to get the GPU server ready to serve work faster.
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