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
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
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.
VPSTTT 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 todayVPSTTT 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 VPSTTT.
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 VPSTTT 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 VPSTTT 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.
Monitor CPU configuration, RAM, disk, IP address, network, operating system and Cloud Server operating status to control resources and plan operations more accurately.
Key numbers that help customers choose VPSTTT VPS, proxy, hosting, server and digital infrastructure services with confidence.
years deploying and operating digital infrastructure
customers and partners trust the VPSTTT ecosystem
technical support throughout the service lifecycle
uptime target for business-critical infrastructure
high-speed connectivity for diverse workloads
Feedback from customers running websites, VPS, proxy, hosting and server systems with VPSTTT.
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 VPSTTT 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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VPSTTT.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 VPSTTT 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 VPSTTT 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 VPSTTT 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 VPSTTT 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 VPSTTT 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.
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.
VPSTTT 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.
VPSTTT 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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