Providing high-performance GPU servers, NVIDIA RTX/Tesla graphics cards, CN2 optimized route to China
Ideal for AI training, deep learning, graphics rendering, large bandwidth support, 10-minute activation
Transparent pricing, high cost-effectiveness
| Plan | GPU | CPU | Memory | Disk | Bandwidth | Price | |
|---|---|---|---|---|---|---|---|
| Entry Plan Ideal for Learning and Testing |
GT750 4GBVRAM | E5-2620 | 32 GB | 1000GB NVMe | 30 Mbps | $264.00/month | Purchase Now |
| Standard PlanPopular Ideal for AI Training |
GT750 4GBVRAM | E5-2690 | 32 GB | 1000GB NVMe | 30 Mbps | $264.00/month | Purchase Now |
| High Performance Plan Ideal for Deep Learning |
GT1050 4GBVRAM | E5-2620*2 | 32 GB | 1000GB NVMe | 30 Mbps | $286.00/month | Purchase Now |
| Enterprise Plan Ideal for Large-scale Training |
GT1050TI 4GBVRAM | E5-2680 | 32 GB | 1000GB NVMe | 30 Mbps | $286.00/month | Purchase Now |
Why Choose SixCVM USA GPU Server
USA GPU Server pricing is relatively affordable, same configuration is 20-30% cheaper than Hong Kong nodes, ideal for projects with limited budgets
50-500Mbps large bandwidth, supports fast upload and download of big datasets, fast model distribution
RTX 4090/3090, Tesla A100 professional graphics cards, thousands of CUDA cores, powerful AI training performance
Pre-installed CUDA, cuDNN, TensorFlow, PyTorch and other mainstream deep learning frameworks, ready to use out of the box
Los Angeles/San Jose nodes, covering North America and Asia Pacific regions, ideal for globalized AI business
Automated deployment, activation within 10 minutes, 7×24 technical support
Los Angeles/San Jose dual nodes, CN2 optimized route to China
CN2 route optimized for China, latency approximately 150-180ms, more stable than regular routes
50-500Mbps dedicated bandwidth, 1Gbps peak, supports big data transmission
Los Angeles/San Jose T3-grade data center, 99.9% power guarantee, professional cooling
Covering North America, Asia Pacific, and Europe regions, ideal for globalized AI business deployment
Covering AI, rendering and other mainstream applications
Large-scale model training, batch data processing, training tasks that are not latency-sensitive
Image recognition, natural language processing, recommendation systems and other ML applications
3D modeling, animation rendering, ray tracing, visual effects production
Video transcoding, batch encoding, AI video enhancement
Molecular simulation, climate prediction, gene sequencing and other high-performance computing
Big data analytics, data mining, business intelligence BI applications
USA GPU Server Complete Technical Specifications
USA GPU Server FAQ Answers
Ideal for AI model training, deep learning, machine learning, graphics rendering, video processing, scientific computing, etc. USA has abundant bandwidth and relatively affordable pricing, ideal for large-scale AI training projects.
Using CN2 optimized routes, mainland China access latency is approximately 150-180ms. Although latency is higher than Hong Kong, bandwidth is larger and pricing is more affordable, ideal for batch training tasks that are not latency-sensitive.
If you need frequent interaction and real-time debugging, we recommend Hong Kong nodes (latency <10ms); if it's batch training or big data processing, we recommend USA nodes (large bandwidth, excellent pricing).
We provide NVIDIA RTX 4090, RTX 3090, RTX 3060, Tesla A100 and other professional graphics cards.
Supports TensorFlow, PyTorch, Keras, Caffe, MXNet and all other mainstream deep learning frameworks.
USA GPU Server pricing is 20-30% cheaper than Hong Kong nodes, with larger bandwidth, ideal for large-scale training projects with limited budgets.
USA GPU Server is a high-performance computing server deployed in USA data centers (Los Angeles, San Jose, etc.) and equipped with NVIDIA professional graphics cards. As the birthplace of the global internet, the USA has the most abundant bandwidth resources and the most mature data center infrastructure. Compared to Hong Kong and other Asian nodes, the biggest advantages of USA GPU Server are large bandwidth and high cost-effectiveness. The same configuration is 20-30% cheaper, and bandwidth can reach 500Mbps-1Gbps, making it particularly ideal for large-scale AI training, batch data processing and other scenarios that are not latency-sensitive but have higher requirements for cost and bandwidth.
Although USA GPU Server access to mainland China has a latency of approximately 150-180ms, higher than Hong Kong nodes (10ms) and Japan nodes (50ms), for batch training tasks, latency is not a critical factor. AI model training typically involves submitting a training task once, after which the model runs autonomously on the server for hours or even days, with no need for frequent interaction during this period. In this scenario, network latency has minimal impact on training speed, while large bandwidth can significantly accelerate training data uploads and model weight downloads.
Another major advantage of USA GPU Server is cost-effectiveness. Because USA bandwidth costs are far lower than in Asian regions, GPU servers with the same configuration are 20-30% cheaper. For example, an RTX 4090 configuration costs $1499/month at Hong Kong nodes, while USA nodes only require $1199/month. For individual developers, startups, and research teams with limited budgets, USA GPU Server is a more economical choice.
1. Large-scale Model Training: When training large models like GPT, BERT, ViT, etc., it typically requires continuous training for days or even weeks, with no need for frequent interaction during this period. USA GPU Server's large bandwidth can quickly upload TB-grade training datasets, and low pricing can significantly reduce long-term training costs.
2. Batch Data Processing: Batch tasks such as image recognition, video analysis, natural language processing, etc., can submit large amounts of data for processing at once, with no need for real-time interaction. USA node's large bandwidth and high cost-effectiveness make it an ideal choice for batch processing.
3. Model Inference Services: For AI inference services for global users (such as image generation, voice recognition APIs), USA nodes can cover North America, Europe and other regions with lower latency. Multi-node deployment strategy can be used: Hong Kong nodes serve Asian users, USA nodes serve European and American users.
4. Scientific Computing: Scientific computing tasks such as molecular simulation, climate prediction, gene sequencing, etc., typically run for a long time with large data volumes. USA GPU Server's large bandwidth and low pricing can significantly reduce computing costs.
Choosing USA or Hong Kong GPU Server depends on your specific requirements:
Select Hong Kong GPU Server Scenarios: Need frequent interaction and debugging (like Jupyter Notebook real-time programming), small-scale rapid experiments, real-time inference services (for China users), latency-sensitive applications.
Select USA GPU Server Scenarios: Large-scale long-term training, batch data processing, limited budget, need large bandwidth for uploads and downloads, inference services for global users.
For enterprise AI teams, we recommend using a hybrid deployment strategy: Use Hong Kong GPU Server during development and debugging phase (low latency, fast iteration), use USA GPU Server during formal training phase (low cost, large bandwidth), and select multi-node deployment based on user distribution during inference service phase.