GPU Cloud Server Pricing and Features Explained

Cyfuture Cloud offers scalable NVIDIA-powered GPU cloud servers ideal for AI, ML, and rendering workloads. Pricing follows a transparent pay-as-you-go model based on GPU type, usage hours, and add-ons like storage.

Cyfuture Cloud's GPU servers feature NVIDIA H100, A100, A40, RTX 4090/5090 GPUs with NVMe SSD storage, 10Gbps bandwidth, and 99.99% uptime. Pricing starts at equivalent $1-3/hour (₹80-250/hour) per high-end GPU, plus ₹2-5/vCPU-hour, ₹5-10/GB/month storage, with no minimums or hidden fees—20-50% cheaper than global providers.

Key Features

Cyfuture Cloud GPU servers deliver accelerated computing up to 10x faster than CPUs for AI training, inference, graphics rendering, and data analytics. They support NVIDIA-certified drivers, CUDA for frameworks like TensorFlow and PyTorch, and seamless integration with Kubernetes or Terraform for DevOps automation.

High-speed NVMe SSDs provide thousands of IOPS for low-latency data access, preventing bottlenecks in deep learning tasks. Scalable block and S3-compatible object storage handle massive datasets, with options for encrypted, VPC-isolated environments compliant with ISO 27001, GDPR, and Indian DPDP Act.​

Enterprise perks include 99.99% uptime via redundant Tier-3 Indian data centers, 24/7 support, global accessibility, and customizable security like DDoS protection and secure boot. Multi-GPU setups allow on-demand scaling without upfront hardware costs, reducing ownership expenses by up to 70%.

Pricing Breakdown

Pricing is calculated per-second for active GPU usage, factoring GPU model (e.g., premium H100 > entry T4/RTX), vCPUs/RAM bundles, storage, and data transfer. Hourly rates: H100/A100 at ₹80-250 ($1-3), with vCPUs at ₹2-5 each and NVMe at ₹5-10/GB/month; egress beyond free tiers at ₹1-5/GB.

Models include pay-as-you-go (no commitments), reservations for discounts on long-term use, and spot/interruptible instances slashing costs 50-80% for non-critical jobs. No surprise fees for data transfer or OS images; use their online calculator for INR estimates based on 730 hours/month full utilization.

Optimization tips: Right-size GPUs (A10 for inference, H100 for training), monitor dashboards, and leverage high-volume deals. Costs stay 20-50% lower than AWS/GCP due to efficient local infrastructure.​

Use Cases and Benefits

Power AI/ML pipelines with instant provisioning—deploy in hours for model training on large datasets. Graphics pros use RTX series for VFX rendering; gamers leverage it for cloud gaming.

Benefits: Cost savings vs. on-premises (70% lower TCO), effortless collaboration via shared instances/Git, and energy efficiency. API-first design fits hybrid clouds.

Conclusion

Cyfuture Cloud's GPU servers combine NVIDIA power, flexible pricing, and robust features for reliable high-performance computing. Start with their calculator to tailor plans, scaling cost-effectively for any workload while enjoying Indian data center advantages.​

Follow-Up Questions

1. What GPUs does Cyfuture Cloud offer?
NVIDIA H100, A100, A40, RTX 4090/5090, L40S, and T4 for AI, rendering, and analytics.

2. Is there a minimum rental period?
No minimums; pay only for active usage time with per-second billing.​

3. How to estimate monthly costs?
Use Cyfuture's pricing calculator: Input GPUs, hours (e.g., 730/month), storage for instant INR quotes.​

4. What storage options exist?
NVMe SSDs, block storage, S3-compatible object storage; all optimized for GPU I/O.​

5. Does it support AI frameworks?
Yes, full NVIDIA CUDA support for TensorFlow, PyTorch, and more.​