Rent GPUs at VPSTTT for model training, fine-tuning and experiments. Compare VRAM, dataset requirements, frameworks and billing-cycle prices.
7-day money-back guarantee if you are not satisfied
Explore GPUs listed in VPSTTT 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.
Prices show the total for the entire billing cycle. Discounts vary by configuration; see each plan's full billing price list.
NVIDIA GTX 1080 Ti 11GB
NVIDIA Tesla T10 16GB
NVIDIA A10 24GB
NVIDIA RTX 4090 TURBO 24GB
NVIDIA RTX PRO 4500 BLACKWELL 32GB
NVIDIA RTX 5090 32GB
NVIDIA L40 GPU 48GB
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. VPSTTT 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 VPSTTT; 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. VPSTTT 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; VPSTTT advises on configuration for inference load, data and deployment needs.
NVIDIA · Volta
V100 introduced first-generation Tensor Cores for deep learning and HPC. VPSTTT 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. VPSTTT 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.
Account for weights, activations, gradients and optimizer state. Per-GPU VRAM is not automatically pooled.
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Balance preprocessing workers, CPU, RAM and SSD throughput to reduce input stalls.
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Check GPU architecture against driver, CUDA and framework versions, particularly on older GPUs.
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Six cycles are available: 1, 3, 6, 12, 24 and 36 months. The seven plans from GPU-11GB to GPU-48GB Big use separately listed cycle prices. Other configurations receive 5/10/15/20/25% off for 3/6/12/24/36 months. Each plan shows its actual total and discount.
Buy nowGPU model training rental provides a GPU-equipped server for learning from project data, with control over code, datasets and the software environment.
Training from scratch, full fine-tuning and LoRA/QLoRA have different memory requirements. Sequence length, batch size, precision and optimizer affect required VRAM.
Prepare the model name, parameter count, training method, framework versions, dataset size, measured VRAM and expected runtime.
VPSTTT wants to bring the best operating experience to customers. For more detailed information, you can contact us via Fanpage or ZaloOA.
Rent GPUs at VPSTTT for model training, fine-tuning and experiments. Compare VRAM, dataset requirements, frameworks and billing-cycle prices.
Measure VRAM and step time using a representative batch before processing the full dataset.
Buy today Reserve SSD capacity for the base model, training data and checkpoint versions.
Buy today Save checkpoints and experiment configuration, test restoration and maintain an independent backup.
Buy today Measure quality on held-out data and resources on your actual job.
Buy todayThe pricing section shows specifications and stock availability. Test software compatibility and performance using your actual workload.
Account for weights, activations, gradients and optimizer state. Per-GPU VRAM is not automatically pooled.
Balance preprocessing workers, CPU, RAM and SSD throughput to reduce input stalls.
Check GPU architecture against driver, CUDA and framework versions, particularly on older GPUs.
Six cycles are available: 1, 3, 6, 12, 24 and 36 months. The seven plans from GPU-11GB to GPU-48GB Big use separately listed cycle prices. Other configurations receive 5/10/15/20/25% off for 3/6/12/24/36 months. Each plan shows its actual total and discount.
Appropriate administrative access lets you install frameworks, libraries and tools and manage the software versions your project needs.
Our technical team helps check configuration, connectivity and the GPU environment and works with you to resolve operational issues.
Explore configuration guidance for training, rendering, inference and GPU infrastructure.
Research & experimentsBuild a deep learning environment, run notebooks and compare AI experiments against your workload.
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Compute infrastructureCompare GPU, CPU, RAM and storage to balance performance, budget and rental duration.
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Graphics & creationSelect a GPU for your scenes, software and memory requirements across 3D, video and animation projects.
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AI application deploymentSize resources for model memory, latency and request volume across chatbots, image processing and AI APIs.
Explore solutionGPU Rental for Model Training and Fine-Tuning should be chosen according to operational goals, user location, 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 | GPU Rental for Model Training and Fine-Tuning | 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.
It depends on model size, batch size, sequence length, precision and training method. Measure a representative job before choosing.
Check model, software and GPU compatibility and VRAM requirements before selecting a plan.
No. Each GPU has separate memory. Splitting the model or data requires supported distributed software.
Model name, training method, framework, dataset, estimated VRAM and rental duration.
Each plan includes its listed SSD capacity. Additional storage or backup requires a separate consultation.
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 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
VPSTTT GROUP - Technology infrastructure, the foundation for digital growth | Business highlights 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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Rent GPUs at VPSTTT for model training, fine-tuning and experiments. Compare VRAM, dataset requirements, frameworks and billing-cycle prices.
Prepare the model name, parameter count, training method, framework versions, dataset size, measured VRAM and expected runtime.
Order ngayPrepare the model name, parameter count, training method, framework versions, dataset size, measured VRAM and expected runtime.
Share required GPU/VRAM, CPU, RAM, SSD capacity and rental duration with VPSTTT. Select available configurations; out-of-stock plans cannot currently be ordered.
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