Performance Enhancement
Choose Dedicated GPU Server Instance Plans
- GPU Card Classify :
- GPU Server Price:
- GPU Use Scenario:
- GPU Memory:
- GPU Card Model:
Lite GPU Dedicated Server - GT710
- 16GB RAM
- Quad-Core Xeon X3440
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce GT710
- Microarchitecture: Kepler
- CUDA Cores: 192
- GPU Memory: 1GB DDR3
- FP32 Performance: 0.336 TFLOPS
Lite GPU Dedicated Server - GT730
- 16GB RAM
- Quad-Core Xeon E3-1230
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce GT730
- Microarchitecture: Kepler
- CUDA Cores: 384
- GPU Memory: 2GB DDR3
- FP32 Performance: 0.692 TFLOPS
Lite GPU Dedicated Server - K620
- 16GB RAM
- Quad-Core Xeon E3-1270v3
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro K620
- Microarchitecture: Maxwell
- CUDA Cores: 384
- GPU Memory: 2GB DDR3
- FP32 Performance: 0.863 TFLOPS
- Ideal for lightweight Android emulators, small LLMs, graphic processing, and more. Powerful than GPU VPS.
Express GPU Dedicated Server - P600
- 32GB RAM
- Quad-Core Xeon E5-2643
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro P600
- Microarchitecture: Pascal
- CUDA Cores: 384
- GPU Memory: 2GB GDDR5
- FP32 Performance: 1.2 TFLOPS
Express GPU Dedicated Server - P620
- 32GB RAM
- Eight-Core Xeon E5-2670
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro P620
- Microarchitecture: Pascal
- CUDA Cores: 512
- GPU Memory: 2GB GDDR5
- FP32 Performance: 1.5 TFLOPS
Express GPU Dedicated Server - P1000
- 32GB RAM
- Eight-Core Xeon E5-2690
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro P1000
- Microarchitecture: Pascal
- CUDA Cores: 640
- GPU Memory: 4GB GDDR5
- FP32 Performance: 1.894 TFLOPS
Basic GPU Dedicated Server - GTX 1650
- 64GB RAM
- Eight-Core Xeon E5-2667v3
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce GTX 1650
- Microarchitecture: Turing
- CUDA Cores: 896
- GPU Memory: 4GB GDDR5
- FP32 Performance: 3.0 TFLOPS
Basic GPU Dedicated Server - T1000
- 64GB RAM
- Eight-Core Xeon E5-2690
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro T1000
- Microarchitecture: Turing
- CUDA Cores: 896
- GPU Memory: 8GB GDDR6
- FP32 Performance: 2.5 TFLOPS
- Ideal for Light Gaming, Remote Design, Android Emulators, and Entry-Level AI Tasks, etc
Basic GPU Dedicated Server - GTX 1660
- 64GB RAM
- Dual 10-Core Xeon E5-2660v2
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce GTX 1660
- Microarchitecture: Turing
- CUDA Cores: 1408
- GPU Memory: 6GB GDDR6
- FP32 Performance: 5.0 TFLOPS
Basic GPU Dedicated Server - K80
- 64GB RAM
- Eight-Core Xeon E5-2690
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Tesla K80
- Microarchitecture: Turing
- CUDA Cores: 4992
- GPU Memory: 24GB GDDR5
- FP32 Performance: 8.73 TFLOPS
- Supports CUDA versions 11.4 and lower. Suitable for small to medium-sized model training, HPC, etc. Does not support the latest AI model optimizations.
Dual GPUs, 24GB GDDR5 total (12GB per GPU)
Professional GPU Dedicated Server - RTX 2060
- 128GB RAM
- Dual 10-Core E5-2660v2
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce RTX 2060
- Microarchitecture: Ampere
- CUDA Cores: 1920
- Tensor Cores: 240
- GPU Memory: 6GB GDDR6
- FP32 Performance: 6.5 TFLOPS
- Powerful for Gaming, OBS Streaming, Video Editing, Android Emulators, 3D Rendering, etc
Advanced GPU Dedicated Server - RTX 2060
- 128GB RAM
- Dual 20-Core Gold 6148
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce RTX 2060
- Microarchitecture: Ampere
- CUDA Cores: 1920
- Tensor Cores: 240
- GPU Memory: 6GB GDDR6
- FP32 Performance: 6.5 TFLOPS
Basic GPU Dedicated Server - RTX 4060
- 64GB RAM
- Eight-Core E5-2690
- 120GB SSD + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce RTX 4060
- Microarchitecture: Ada Lovelace
- CUDA Cores: 3072
- Tensor Cores: 96
- GPU Memory: 8GB GDDR6
- FP32 Performance: 15.11 TFLOPS
Basic GPU Dedicated Server - RTX 5060
- 64GB RAM
- 24-Core Platinum 8160
- 120GB SSD + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia GeForce RTX 5060
- Microarchitecture: Blackwell 2.0
- CUDA Cores: 4608
- Tensor Cores: 144
- GPU Memory: 8GB GDDR7
- FP32 Performance: 23.22 TFLOPS
Professional GPU Dedicated Server - P100
- 128GB RAM
- Dual 10-Core E5-2660v2
- 120GB + 960GB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Tesla P100
- Microarchitecture: Pascal
- CUDA Cores: 3584
- GPU Memory: 16 GB HBM2
- FP32 Performance: 9.5 TFLOPS
- Suitable for AI, Data Modeling, High Performance Computing, etc.
Advanced GPU Dedicated Server - RTX 3060 Ti
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: GeForce RTX 3060 Ti
- Microarchitecture: Ampere
- CUDA Cores: 4864
- Tensor Cores: 152
- GPU Memory: 8GB GDDR6
- FP32 Performance: 16.2 TFLOPS
Advanced GPU Dedicated Server - V100
- 128GB RAM
- Dual 12-Core E5-2690v3
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia V100
- Microarchitecture: Volta
- CUDA Cores: 5,120
- Tensor Cores: 640
- GPU Memory: 16GB HBM2
- FP32 Performance: 14 TFLOPS
- Cost-effective for AI, deep learning, data visualization, HPC, etc
Advanced GPU Dedicated Server - A4000
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro RTX A4000
- Microarchitecture: Ampere
- CUDA Cores: 6144
- Tensor Cores: 192
- GPU Memory: 16GB GDDR6
- FP32 Performance: 19.2 TFLOPS
Advanced GPU Dedicated Server - A5000
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro RTX A5000
- Microarchitecture: Ampere
- CUDA Cores: 8192
- Tensor Cores: 256
- GPU Memory: 24GB GDDR6
- FP32 Performance: 27.8 TFLOPS
Enterprise GPU Dedicated Server - A40
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia A40
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 37.48 TFLOPS
- Ideal for hosting AI image generator, deep learning, HPC, 3D Rendering, VR/AR etc.
Enterprise GPU Dedicated Server - RTX 4090
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: GeForce RTX 4090
- Microarchitecture: Ada Lovelace
- CUDA Cores: 16,384
- Tensor Cores: 512
- GPU Memory: 24 GB GDDR6X
- FP32 Performance: 82.6 TFLOPS
Enterprise GPU Dedicated Server - RTX A6000
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro RTX A6000
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 38.71 TFLOPS
Enterprise GPU Dedicated Server - A100
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 40GB HBM2
- FP32 Performance: 19.5 TFLOPS
- Good alternativeto A800, H100, H800, L40. Support FP64 precision computation, large-scale inference/AI training/ML.etc
Enterprise GPU Dedicated Server - A100(80GB)
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 80GB HBM2e
- FP32 Performance: 19.5 TFLOPS
Enterprise GPU Dedicated Server - H100
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia H100
- Microarchitecture: Hopper
- CUDA Cores: 14,592
- Tensor Cores: 456
- GPU Memory: 80GB HBM2e
- FP32 Performance: 183TFLOPS
Multi-GPU Dedicated Server - 2xRTX 4060
- 64GB RAM
- Eight-Core E5-2690
- 120GB SSD + 960GB SSD
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x Nvidia GeForce RTX 4060
- Microarchitecture: Ada Lovelace
- CUDA Cores: 3072
- Tensor Cores: 96
- GPU Memory: 8GB GDDR6
- FP32 Performance: 15.11 TFLOPS
Multi-GPU Dedicated Server - 2xRTX 3060 Ti
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x GeForce RTX 3060 Ti
- Microarchitecture: Ampere
- CUDA Cores: 4864
- Tensor Cores: 152
- GPU Memory: 8GB GDDR6
- FP32 Performance: 16.2 TFLOPS
Multi-GPU Dedicated Server - 2xRTX A4000
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x Nvidia RTX A4000
- Microarchitecture: Ampere
- CUDA Cores: 6144
- Tensor Cores: 192
- GPU Memory: 16GB GDDR6
- FP32 Performance: 19.2 TFLOPS
Multi-GPU Dedicated Server - 2xRTX A5000
- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x Quadro RTX A5000
- Microarchitecture: Ampere
- CUDA Cores: 8192
- Tensor Cores: 256
- GPU Memory: 24GB GDDR6
- FP32 Performance: 27.8 TFLOPS
Multi-GPU Dedicated Server- 2xRTX 4090
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x GeForce RTX 4090
- Microarchitecture: Ada Lovelace
- CUDA Cores: 16,384
- Tensor Cores: 512
- GPU Memory: 24 GB GDDR6X
- FP32 Performance: 82.6 TFLOPS
Multi-GPU Dedicated Server - 3xRTX 3060 Ti
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 3 x GeForce RTX 3060 Ti
- Microarchitecture: Ampere
- CUDA Cores: 4864
- Tensor Cores: 152
- GPU Memory: 8GB GDDR6
- FP32 Performance: 16.2 TFLOPS
Multi-GPU Dedicated Server - 3xV100
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 3 x Nvidia V100
- Microarchitecture: Volta
- CUDA Cores: 5,120
- Tensor Cores: 640
- GPU Memory: 16GB HBM2
- FP32 Performance: 14 TFLOPS
- Expertise in deep learning and AI workloads with more tensor cores
Multi-GPU Dedicated Server - 3xRTX A5000
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 3 x Quadro RTX A5000
- Microarchitecture: Ampere
- CUDA Cores: 8192
- Tensor Cores: 256
- GPU Memory: 24GB GDDR6
- FP32 Performance: 27.8 TFLOPS
Multi-GPU Dedicated Server - 3xRTX A6000
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 3 x Quadro RTX A6000
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 38.71 TFLOPS
Multi-GPU Dedicated Server - 2xA100
- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 40GB HBM2
- FP32 Performance: 19.5 TFLOPS
- Free NVLink Included
- A Powerful Dual-GPU Solution for Demanding AI Workloads, Large-Scale Inference, ML Training.etc. A cost-effective alternative to A100 80GB and H100, delivering exceptional performance at a competitive price.
Multi-GPU Dedicated Server - 4xA100
- 512GB RAM
- Dual 22-Core E5-2699v4
- 240GB SSD + 4TB NVMe + 16TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 4 x Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 40GB HBM2
- FP32 Performance: 19.5 TFLOPS
Multi-GPU Dedicated Server - 8xV100
- 512GB RAM
- Dual 22-Core E5-2699v4
- 240GB SSD + 4TB NVMe + 16TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 8 x Nvidia Tesla V100
- Microarchitecture: Volta
- CUDA Cores: 5,120
- Tensor Cores: 640
- GPU Memory: 16GB HBM2
- FP32 Performance: 14 TFLOPS
Multi-GPU Dedicated Server - 4xRTX A6000
- 512GB RAM
- Dual 22-Core E5-2699v4
- 240GB SSD + 4TB NVMe + 16TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 4 x Quadro RTX A6000
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 38.71 TFLOPS
Multi-GPU Dedicated Server- 2xRTX 5090
- 256GB RAM
- Dual Gold 6148
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 2 x GeForce RTX 5090
- Microarchitecture: Ada Lovelace
- CUDA Cores: 20,480
- Tensor Cores: 680
- GPU Memory: 32 GB GDDR7
- FP32 Performance: 109.7 TFLOPS
Multi-GPU Dedicated Server - 8xRTX A6000
- 512GB RAM
- Dual 22-Core E5-2699v4
- 240GB SSD + 4TB NVMe + 16TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: 8 x Quadro RTX A6000
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 38.71 TFLOPS
4 Benefits of Dedicated Server with Nvidia GPU Rental
Customization
Cost-effective
Scalability
GPU Dedicated Server Rental for Deep Learning
When selecting a dedicated GPU server for deep learning, multiple factors need to be considered. The most important factor is the GPU itself. NVIDIA GPU is the most popular choice for deep learning. Tesla V100 and updated A100 are currently one of the most powerful GPUs. These GPUs provide high internal storage bandwidth, low latency, and support advanced functions such as tensor core.
Dedicated Server with GPU Rental for Scientific Computing
When selecting GPU servers for scientific computing, the selection of GPU is particularly important. NVIDIA GPU is often used in scientific computing because of its high performance and support for advanced functions such as CUDA and Tensor kernel. NVIDIA Tesla V100 is a particularly popular choice for scientific computing because it provides high internal storage bandwidth, low latency and advanced tensor core functions.
Dedicated GPU Server Rental for Virtualization
Please note that GPU virtualization requires special hardware and software support, and may require higher technical level and experience. When using a GPU dedicated server for virtualization, be sure to carefully understand the requirements of virtualization software and GPU drivers.
Dedicated Server with GPU Rental for Gaming
For some games, GPU is not absolutely necessary, especially for games that use simple graphics or are designed to run on low-end hardware. In these cases, a dedicated server with powerful CPU, fast memory and high-quality network connection may be sufficient. For other games, especially those with higher graphics requirements, GPU may be a valuable supplement to dedicated servers. In these cases, NVIDIA GPUs are usually the best choice because they provide high-performance graphics processing and support advanced functions such as CUDA and Tensor cores.
GPU Dedicated Server for Mining and Data Analysis
First of all, GPU model is crucial for data mining and analysis tasks. NVIDIA GPU is popular in the field of data mining and analysis due to its high performance, CUDA support and extensive software ecosystem. In addition, NVIDIA Tesla series and other high-end GPUs provide more memory, kernel and advanced functions, which can significantly improve the performance of data mining and analysis tasks.
Dedicated Server with GPU Rental for Video Editing
GPU model is very important for video rendering task. NVIDIA GPU is popular in the field of video rendering due to its high performance, CUDA support and extensive software ecosystem. In addition, high-end GPUs such as NVIDIA Quadro and Tesla series provide more memory, kernel and advanced functions, which can significantly improve video rendering performance.
How does GPU Dedicated Server Rental Work?
GPU Server Inquiry
FAQs of Dedicated GPU Server Hosting, Nvidia GPU Rental
What is GPU Dedicated Server?
Compared with CPU-only servers, GPU servers have many advantages, including faster processing speed, higher accuracy, shorter latency and the ability to process larger data sets. They are also more energy efficient, enabling organizations to save electricity bills. In general, GPU dedicated servers provide a powerful and scalable platform for high-performance computing applications.
What are the operating systems rented by GPU servers?
What is RTX dedicated servers?
The RTX dedicated server is particularly suitable for applications that require real-time ray tracing or other advanced graphics capabilities. This includes games, video rendering, 3D modeling, and machine learning applications.
How to calculate the cost of GPU server rental?
How to select the best GPU server provider?
What is GPU Server Rental?
What is GTX dedicated servers?
GTX dedicated server can be used for various applications, including game hosting, video streaming, virtual reality experience, etc. They are particularly suitable for tasks that require high-performance graphics, such as games or video rendering.
What are the security issues when renting GPU servers?
Among geforce, quadro, and tesla, which series is more suitable for renting gpu servers?
GeForce graphics cards are mainly designed for games and consumer applications, and are generally cheaper than professional graphics cards. They provide high-performance capabilities and are ideal for games, video rendering, and other high-performance computing applications.
On the other hand, Quadro graphics cards are specially designed for professional use and tailored to meet the needs of 3D modeling, animation and other high-end graphics applications. They provide advanced features, such as higher accuracy, greater memory bandwidth, and support for multiple displays.
Tesla graphics cards are designed for high-performance computing applications such as artificial intelligence, machine learning and scientific simulation. They provide advanced parallel computing capabilities and are optimized for data centers and supercomputing environments.
Finally, the selection of GeForce, Quadro and Tesla graphics cards for GPU server leasing depends on the specific needs and requirements of the task at hand. For example, if your application requires advanced 3D modeling or animation capabilities, the Quadro graphics card may be the best choice. If the application needs advanced parallel computing capabilities for scientific simulation or machine learning, Tesla graphics card may be the best choice. If the application needs high-performance computing for games or other consumer applications, GeForce graphics card may be the best choice.