Power Your AI Training with
NVIDIA V100 GPU Servers

Enhance model training, simulations, and large-scale data workflows with NVIDIA V100 GPU Servers, available from $0.43 per hour. Cyfuture AI makes it easy to rent NVIDIA V100 GPU resources when you need them, giving you access to dependable Volta-architecture performance without the upfront cost of hardware.

Whether you're running small experiments or scaling multi-GPU clusters for production work, the NVIDIA V100 for AI training offers strong FP16/FP32 compute power, high-bandwidth HBM2 memory, and stable multi-GPU communication. Combined with Cyfuture AI's optimized infrastructure and technical support, it delivers a fast and efficient environment for deep learning, research, and high-performance computing.

Train Faster with NVIDIA V100 GPU Servers

Accelerate model training and simulations with NVIDIA V100 servers optimized for TensorFlow, PyTorch, and CUDA.

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Why Choose NVIDIA V100 GPU Servers

The NVIDIA V100 GPU is engineered for demanding AI and HPC workloads. It offers a proven balance of compute, memory, and interconnect performance - making it ideal when you want to rent NVIDIA V100 GPU instances that reliably complete long-running training jobs.

Key V100 Advantages:

High compute density

5,120 CUDA cores and 640 Tensor Cores

Strong FP32 & FP16 throughput

~15.7 TFLOPS (FP32); up to 125 TFLOPS (FP16)

HBM2 memory

16GB or 32GB options with 900 GB/s bandwidth for large datasets

NVLink support

Fast GPU-to-GPU communication for multi-GPU scaling

These capabilities make the V100 ideal for accelerating experiments, reducing time-to-result, and running production inference at scale.

NVIDIA V100 GPU Plans and Pricing

Cyfuture AI offers a range of NVIDIA V100 GPU configurations so you can choose the right balance of performance and cost for your project. Pricing starts at $0.57 per hour, with additional savings available on monthly and long-term reservations. Through our GPU-as-a-Service platform you can quickly rent GPU resources and scale compute capacity as your workload grows. Whether you're exploring models, running production workloads, or building multi-GPU clusters, Cyfuture AI gives you the flexibility to expand without the expense or complexity of owning hardware.

Dollar $ INR

NVIDIA V100 Instances

Instance Name	Compute unit Model	AI Compute memory (GB)	Performa FP32	Performa FP16	vCPU	Instance memory(GB)	Peer to Peer Bandwidth (GB/s)	Network Bandwidth (GB/s)	Peak/Benchmark Memory Bandwidth (GB/s)	On Demand Price/hour	1 Month Reserved Price/hr	6 Month Reserved Price/hr	12 Month Reserved Price/hr	Action
1V100.16v.256m	NVIDIA 1xV100 (1X)	32	15.7	125	16	256	-	100	900	₹ 54	₹ 48 (10.20% Discount)	₹ 43 (20.41% Discount)	₹ 39 (28.57% Discount)	Reserve Now
2V100.32v.512m	NVIDIA 2xV100 (2X)	64	31.4	250	32	512	300	200	900	₹ 107	₹ 95 (11.11% Discount)	₹ 83 (22.01% Discount)	₹ 74 (30.71% Discount)	Reserve Now
4V100.64v.1024m	NVIDIA 4xV100 (4X)	128	62.8	500	64	1024	600	400	900	₹ 211	₹ 188 (11.12% Discount)	₹ 165 (22.03% Discount)	₹ 146 (30.74% Discount)	Reserve Now
8V100.128v.2048m	NVIDIA 8xV100 (8X)	256	125.6	1000	128	2048	1200	800	900	₹ 418	₹ 372 (11.13% Discount)	₹ 326 (22.05% Discount)	₹ 290 (30.78% Discount)	Reserve Now
1xV100.32v.32m	NVIDIA 1xV100 (1X)	74	145	286	32	74	566	429	219	₹ 46	₹ 41	₹ 37	₹ 32	Reserve Now
1V100.8v.64m	NVIDIA 2xV100 (1X)	1536	1304	10456	128	1536	3600	3200	580	₹ 45	₹ 41	₹ 33	₹ 23	Reserve Now
16V100.64v.128m	NVIDIA 4xV100 (4X)	1536	1304	10456	128	1536	3600	3200	580	₹ 93	₹ 83	₹ 74	₹ 65	Reserve Now
8V100.128v.2048m	NVIDIA 8xV100 (8X)	1536	1304	10456	128	1536	3600	3200	580	₹ 357	₹ 318	₹ 280	₹ 242	Reserve Now

Technical Specifications of NVIDIA V100 GPU Server

GPU Specifications

GPU Model: NVIDIA Tesla V100
Architecture: NVIDIA Volta
GPU Memory: 16 GB / 32 GB HBM2 (per GPU)
Memory Bandwidth: 900 GB/s
CUDA Cores: 5,120
Tensor Cores: 640
Single Precision (FP32): 15.7 TFLOPS
Double Precision (FP64): 7.8 TFLOPS
Tensor Performance (FP16): Up to 125 TFLOPS
NVLink Bandwidth: Up to 300 GB/s (Multi-GPU)
Supported APIs: CUDA, DirectCompute, OpenCL, Vulkan, OpenGL

Real-World Use Cases

The NVIDIA V100 GPU Server performs consistently across a wide range of AI, HPC, and analytics workloads. Whether you're building new models or powering production pipelines, it helps move projects from idea to deployment more efficiently.

Deep Learning & AI Training

The V100 handles popular architectures like ResNet, EfficientNet, and transformer models with strong performance, reducing training time and improving iteration speed.

High-Performance Computing (HPC)

Scientific simulations, fluid dynamics, genomics, and other compute-heavy workloads benefit from the V100's FP64 capability and stable parallel performance.

Natural Language Processing (NLP)

The V100 supports medium to large transformer models, enabling faster training and inference for chatbots, summarization systems, and language understanding.

Computer Vision & Imaging

From image classification to video analytics, the V100 delivers high throughput and steady performance, especially in multi-GPU setups.

Data Analytics & Machine Learning Pipelines

With RAPIDS and CUDA acceleration, the V100 helps process large datasets faster, improving ETL, feature engineering, and real-time analytics.

Security, Stability, and Reliability

Cyfuture AI ensures each NVIDIA V100 GPU server delivers consistent uptime and secure operation - essential for mission-critical AI workloads.

What You Get

Redundant hardware and power pathways to minimize downtime

Encryption in transit and at rest for data protection

Multi-layered security including firewalls and DDoS safeguards

Compliance-ready infrastructure aligned with ISO 27001 and SOC 2

Advanced monitoring tools such as NVIDIA DCGM and system-level BMC dashboards

Compare NVIDIA V100 vs Other GPUs

Feature	V100	A100	H100
Architecture	Volta	Ampere	Hopper
Memory	16-32 GB HBM2	40-80 GB HBM2e	80 GB HBM3
Tensor Cores	3rd Gen / 640	432 (3rd Gen)	4th Gen
FP32 Performance	15.7 TFLOPS	19.5 TFLOPS	26 TFLOPS
FP16 / Tensor	Up to 125 TFLOPS	Up to 156 TFLOPS	Higher
NVLink	Up to 300 GB/s	Up to 600 GB/s	Higher
Ideal Use	Cost-effective multi-GPU training & HPC	Advanced AI workloads, larger models	Cutting-edge LLMs & generative AI

The V100 provides excellent performance-per-dollar for many production and research workloads - a practical choice when balancing cost, availability, and scalability.

NVIDIA V100 for AI Training and Research

If you're building or training AI models that require consistent performance and strong multi-GPU scaling, the NVIDIA V100 for AI training provides a dependable foundation. It integrates smoothly with frameworks like TensorFlow, PyTorch, CUDA, Keras, MXNet, and ONNX Runtime, making it a versatile choice for researchers, engineers, and enterprise AI teams.

Key Benefits

Faster Model Training

The V100's Tensor Cores and high memory bandwidth help shorten training cycles for deep learning models, giving you more room to experiment and refine architectures.

Reliable Multi-GPU Scaling

With NVLink and PCIe support, you can scale from a single V100 to multi-GPU systems or full clusters, unlocking higher throughput for large datasets and complex workloads.

Mixed Precision Support

FP32, FP16, and INT8 precision modes enable faster compute while preserving model accuracy, making the V100 ideal for training, fine-tuning, and inference workflows.

Cost-Effective GPU Access

Flexible NVIDIA V100 rental options make it easier for teams to access high-performance compute without the need for large upfront hardware investments. For research groups, startups, and enterprise teams, the V100 makes GPU-powered AI more accessible and budget-friendly.

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We're not just delivering AI infrastructure-we're your trusted AI solutions provider, empowering enterprises to lead the AI revolution and build the future with breakthrough generative AI models.

KPMG optimized workflows, automating tasks and boosting efficiency across teams.

H&R Block unlocked organizational knowledge, empowering faster, more accurate client responses.

TomTom AI has introduced an AI assistant for in-car digital cockpits while simplifying its mapmaking with AI.

Why Choose Cyfuture AI for V100 GPU

Cyfuture AI combines infrastructure, operational know-how, and support to make your NVIDIA V100 rental straightforward and productive.

Proven Experience

We've supported research labs, enterprise ML teams, and HPC projects with V100 clusters and tuned distributed training pipelines.

Purpose-Built Infrastructure

High-speed networking (InfiniBand/10-100GbE), redundant power, and optimized cooling keep V100 servers running at peak performance.

Flexible Rental & Purchase Options

Choose hourly, monthly, or reserved plans. Prefer to own hardware? We also help customers buy NVIDIA V100 GPU servers with procurement and deployment support.

Transparent NVIDIA V100 GPU Price

We provide clear pricing and volume discounts. Contact us for an accurate NVIDIA V100 GPU price based on region, configuration, and term.

24/7 Expert Support

From environment setup to model optimization and troubleshooting, our team supports you throughout the lifecycle.

Trusted by Customers Worldwide

Startups, research institutions, and enterprises choose Cyfuture AI for reliable NVIDIA V100 Cloud compute and managed GPU services.

NVIDIA V100 from Just $0.43/hr

Pay only for what you use with flexible per-hour, monthly, and reserved pricing.

Compare V100 Options

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FAQs - V100 GPU

1. Why is the NVIDIA V100 good for AI training?

Because it combines Tensor Cores, high HBM2 memory bandwidth, and NVLink, making it efficient for mixed-precision training and multi-GPU scaling.

2. Can I rent multiple V100 GPUs for distributed training?

Yes - Cyfuture AI supports single nodes and multi-node clusters with NVLink or InfiniBand interconnects.

3. What is the NVIDIA V100 GPU price?

Pricing depends on configuration, region, and commitment. Contact us for an accurate NVIDIA V100 GPU price and volume discounts.

4. Is the V100 still relevant versus A100 or H100?

Yes - for many workloads the V100 offers a strong price-to-performance ratio and proven stability. For larger LLMs and next-gen workloads, consider A100 or H100.

5. Can I buy NVIDIA V100 GPU servers instead of renting?

Yes - Cyfuture AI can assist with procurement and deployment if you prefer to buy NVIDIA V100 GPU server hardware.

6. Which frameworks are supported?

TensorFlow, PyTorch, MXNet, Keras, ONNX Runtime, and CUDA-accelerated toolkits.

7. How quickly can I deploy a V100 GPU server?

Deployment takes only a few minutes. Once your configuration is selected, your V100 server is spun up and ready for training or production tasks.

8. Does the V100 support multi-precision workloads?

Yes. The V100 handles FP32, FP16, FP64, and INT8 operations, giving you flexibility to optimize for speed or accuracy.

9. Can I upgrade to more GPUs later?

You can start small and scale anytime. Additional V100 GPUs or full clusters can be added as your project grows.

10. Is the V100 suitable for long-running training jobs?

Yes. The V100 is built for continuous, high-load compute. Cyfuture AI ensures stable cooling, power, and monitoring to support long-duration training without interruptions.

Get Started with NVIDIA V100 GPU Servers

Ready to rent V100 GPU instances or explore cluster options? Cyfuture AI offers flexible rental plans, transparent pricing, and hands-on support to help you deploy, optimize, and scale.

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NVIDIA V100 GPU Server

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Power Your AI Training with NVIDIA V100 GPU Servers

Train Faster with NVIDIA V100 GPU Servers

Why Choose NVIDIA V100 GPU Servers

Key V100 Advantages:

High compute density

Strong FP32 & FP16 throughput

HBM2 memory

NVLink support

NVIDIA V100 GPU Plans and Pricing

NVIDIA V100 Instances

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Technical Specifications of NVIDIA V100 GPU Server

GPU Specifications

CPU Configuration

System Memory

Storage

Networking

Expansion & Connectivity

Power & Cooling

Software & OS Support

Security & Monitoring

Performance & Use Cases

Scalability

Compliance & Warranty