What GPU models are available under GPU as a Service?

Cyfuture Cloud's GPU as a Service (GPUaaS) provides on-demand access to a range of high-performance NVIDIA GPUs tailored for AI, machine learning, HPC, and inference workloads. Key models include entry-level options like T4 and V100, mid-range L4 and L40S, and high-end A100, H100, and H200, with additional legacy support for K80, P100, and P4.

Cyfuture Cloud offers the following NVIDIA GPU models under GPU as a Service:

- Entry-level: T4 (16GB GDDR6), V100 (32GB HBM2)

- Mid-range: L4, L40S (48GB GDDR6)

- High-end: A100 (40/80GB HBM2e), H100 (80GB HBM3), H200 (141GB HBM3e)

- Legacy/Specialized: K80, P100, P4

These are available in scalable clusters with up to 8 GPUs per node, NVLink interconnects, and pay-as-you-go pricing.

GPU Tiers Overview

Cyfuture Cloud categorizes its GPU offerings into three tiers to match diverse workloads, ensuring cost-efficiency and performance scaling. Entry-level GPUs like the NVIDIA T4 and V100 handle inference, light training, and analytics with lower power consumption, making them suitable for startups and testing phases. Mid-range options, such as L4 and L40S, support moderate deep learning, rendering, and simulations, offering a balance of efficiency and capability for production inference like AI copilots.

High-end models dominate for intensive tasks: A100 excels in enterprise AI training and HPC simulations; H100 powers large-scale LLM training and GenAI with superior compute; H200 provides massive memory for foundation models. Configurations pair these GPUs with AMD EPYC or Intel Xeon CPUs, up to 2TB DDR5 RAM, and RDMA networking for multi-GPU setups reaching 900GB/s bandwidth.

Use Cases by Model

Each GPU model aligns with specific applications on Cyfuture's GPUaaS platform.

- T4/V100: Ideal for cost-effective inference, data analytics, and model prototyping. V100's HBM2 memory suits ML pipelines reliably.

- L4/L40S: Optimized for scalable inference, multimodal AI, and real-time deployments. L40S handles production-scale apps efficiently.​

- A100/H100/H200: Built for heavy lifting—LLM fine-tuning, GenAI training, and HPC. H100 accelerates enterprises with maximum FP8/FP16 performance; H200's 141GB HBM3e tackles memory-bound tasks.

Legacy GPUs like K80 and P100 support specialized or older workloads without full infrastructure overhauls. Users deploy via flexible instances, from single GPUs to clusters, with 24/7 support and enterprise security.

Infrastructure and Accessibility

Cyfuture's GPUaaS eliminates hardware ownership, offering bare-metal options, pay-per-second billing, and instant provisioning across global data centers. Nodes support 4-8 GPUs with high-speed interconnects, integrated into a secure OCI stack for AI/ML/HPC. Availability spans enterprises, startups, research, and government, with recent expansions highlighting H100, L40S, V100, and A100 as core offerings.

This setup ensures scalability: start small with T4 for proofs-of-concept, scale to H100 clusters for production LLMs. Pricing tiers by performance/budget, with no upfront costs.​

Benefits of Cyfuture GPUaaS

Opting for Cyfuture's service means leveraging NVIDIA's latest without CapEx. Benefits include 99.99% uptime, data sovereignty compliance, and tools for seamless RAG/LLM workflows. Compared to on-prem, it cuts costs by 40-60% via utilization optimization and provides instant access to cutting-edge silicon like H200.

Conclusion

Cyfuture Cloud's GPU as a Service delivers a comprehensive lineup from T4 to H200, empowering users across workload intensities with flexible, high-performance computing. This tiered NVIDIA-focused portfolio, backed by robust infrastructure, positions Cyfuture as a go-to for AI innovation without hardware hassles—deploy today for scalable GPU power.

Follow-Up Questions

Q1: How do I select the right GPU for my workload on Cyfuture Cloud?
Assess needs: Use T4/V100 for inference/light training; L40S/L4 for mid-scale; A100/H100/H200 for large models/HPC. Cyfuture's support team aids via workload profiling and benchmarks.​

Q2: What interconnects and memory options are available?
NVLink up to 900GB/s for multi-GPU; memory from 16GB GDDR6 (T4) to 141GB HBM3e (H200). Nodes offer up to 2TB DDR5 RAM.​

Q3: Are bare metal GPU servers offered?
Yes, bare-metal GPU servers provide dedicated access to full nodes with 4-8 GPUs, ideal for low-latency, high-security workloads.​

Q4: How does pricing work for these GPUs?
Pay-as-you-go per second/hour, tiered by model/performance. Entry-level cheapest; high-end like H100 premium. Contact sales for quotes; no long-term commitments.