The introduction of artificial intelligence (AI), machine learning (ML), deep learning, and big data analytics has resulted in an insatiable appetite for GPU computing power. Of NVIDIA’s line of products, the Tesla V100 GPU has carved out its niche as a workhorse—offering a reasonable price point for a performance level that is in line with running larger models, performing simulations, or executing inference workloads.

Internationally, Amazon Web Services (AWS) has dominated the GPU cloud service market, offering large-scale applications through its EC2 lineup with the V100. However, in India, many users of AWS—startups, researchers, students, and even enterprises—have a huge problem with cost. AWS pricing is often simply too much for projects with a limited budget.

This is where Webyne Data Center—an India-based provider offering V100 GPU cloud servers at a fraction of AWS’s pricing—shines: this article compares AWS vs Webyne V100 GPU cloud pricing in India, performance, and value, and ultimately helps you decide which vendor’s offering makes sense for your workloads.

AWS V100 GPU Pricing in India

AWS has built its reputation on enterprise reliability, global scale, and integration with a massive cloud ecosystem. Nevertheless, there is a catch to these advantages.

AWS On-Demand Pricing (V100 GPUs)

• p3.2xlarge instance (1 x NVIDIA Tesla V100, 16 vCPUs, 61GB RAM)
• on-demand rate: ₹250 per hour
• Monthly (24/7 use): ~₹180,000+ per GPU instance

AWS Supplementary Payments

Besides the base instance price, AWS customers need to account for:

• EBS Storage cost (if attached, SSDs are paid separately.)
• Data transfers charges (ingress is free; egress is charged per GB).
• Support plans (business/enterprise support adds extra monthly charges).
• Regional variations (Indian regions sometimes have higher effective costs).

For researchers and startups in India, these costs make AWS prohibitive for continuous training or experimentation.

Pricing for Webyne V100 GPU in India

Webyne, an India-based data center and cloud company has taken a radically different approach to H100 GPUs — with an emphasis on affordability, transparency and local-first performance.

Webyne V100 Pricing (updates from 2025)

• Single V100 GPU instance: Starting at just ₹10/hour (~$0.12/hour)
• Monthly (24/7 use): ~₹7,200 per GPU instance
• There are no hidden fees (pricing for storage and data transfer is straight-forward).

What do you get with Webyne’s V100 GPU cloud

• Local data centres in India → Lower latency for India users.
• Pay as you go billing → Get billed based on actual usage.
• Enterprise-grade hardware with NVMe storage & fast networking.
• Customizable solution for indie startups, researchers and enterprises.
• Local support in India ( 1 thing that the global players do not offer).

In simple terms, Webyne delivers the same NVIDIA V100 GPU hardware that AWS does—but at 20x lower cost.

AWS vs Webyne V100 GPU Cloud: Side-by-Side Comparison

Feature / Factor	AWS (EC2 p3 instances)	Webyne V100 GPU Cloud
Pricing (per hour)	~₹250/hour ($3.00/hr)	~₹10/hour ($0.12/hr)
Monthly (24/7 use)	~₹180,000+	~₹7,200
Data Transfer	Charged separately (egress high)	Transparent, lower-cost options
Storage	Billed separately (EBS volumes)	Bundled NVMe storage
Latency in India	Higher (regional dependency)	Low (India-local data centers)
Support	Paid support tiers	Local 24/7 support included
Scalability	Global scale, high availability	Scalable within India & hybrid
Best For	Enterprises needing global SLA	Startups, researchers, SMEs, India-first workloads

Performance & Reliability – Same Hardware, Different Economics

It’s important to note that AWS and Webyne both offer the exact same GPU hardware—the NVIDIA Tesla V100. 

That means:

Performances (TFLOPS, CUDA cores, tensor cores, and HBM2 memory) are the same. 

They can both handle deep learning, AI training, HPC, and inference workloads with equal efficiency.

The true differentiation is economics and access:

AWS, the founder, or the student would think twice about training for extended periods at the higher hourly rate.

Webyne made this experimentation affordable at ₹10/hour, allowing you to fine-tune models, run hyperparameter sweeps, or do research/test plans without fear of going over your financial limit.

AWS’s global scale with SLA-based contracts still better meets the demands of organizations that rely on mission-critical uptime for data across continents, providing more value to the enterprise. Webyne provides the best balance of cost and performance for the remaining 99 percent of AI teams in India.

Who Should Choose Webyne Over AWS?

1. Startups & SMEs

Building an AI product but operating on limited funding? Webyne enables affordable prototyping, experimentation, and scaling without burning capital.

2. Researchers & Students

Academic institutions and individuals can finally access world-class GPUs without international cloud pricing barriers. Perfect for NLP, LLM fine-tuning, and AI coursework.

3. Indian Businesses

Organizations that want to host data locally for compliance, latency, or data sovereignty have options on Webyne’s India-first infrastructure.

4. AI/ML Developers/Freelancers.

Cheap access to GPUs leads to quicker iteration cycles, experimentation, and less downtime.

Why AWS Still Makes Sense

While the economics and local focus of Webyne are appealing, AWS will still be more beneficial in the following cases:

• Global-scale apps: Companies needing redundancy across the globe and multi-region availability.
• Integrated ecosystem: Businesses with a heavy reliance on the AWS ecosystem (S3, Lambda, SageMaker, etc.)
• Enterprise SLAs (service level agreements): If your workload absolutely requires 99.999% uptime across multiple continents.

In practice, AWS remains the gold standard for large, enterprise-grade workloads, but for affordable, India-first, AI workloads, Webyne is the clear leader.

The Bigger Picture: Democratizing AI computation in India

The significantly lower value for compute in India (AWS is ₹10/hr) hints at a larger shift: democratizing AI computation in India. By providing V100 GPU Cloud servers for one-fifth the value of the same instances with AWS, Webyne enables:

• Students to play with LLMs (yes, in Indian languages)
• 2700 or so startups to use SaaS to build AI products without the gnashing of teeth from the cloud bill
• Researchers are to publish cutting-edge research on budgets that don’t require approval.
• Enterprises to pilot AI applications locally so they can scale those applications globally.

A pricing paradigm shift like this could turn India into an AI innovation hub, similar to what internet access did over the last decade!

Conclusion

The question of using AWS or Webyne for V100 GPU cloud servers in India is simply a prioritization decision of AWS or Webyne:

• If your team places high value on “global reach,” “enterprise SLAs,” or “AWS ecosystem integrated services,” you will likely choose AWS (even if it is a crazy price).
• If your team prioritizes “affordable,” “reliable,” and “India local” GPU compute for AI/ML workloads, Webyne’s V100 GPU cloud offers the same NVIDIA V100 GPU compute for 20x lower price (just ₹10/hr).
• Startups, researchers, Indian enterprises, and students looking for cost -effective GPU compute for their workloads should look into Webyne’s V100 GPU Cloud in 2025.