In 2025, GPU-accelerated cloud instances will become the backbone of modern computing—fueling everything from machine learning and video rendering to virtual desktops and game streaming. As per a recent IDC report, over 60% of AI and deep learning workloads now rely on cloud GPUs, with AWS leading the market in flexibility and global reach.
Among its many GPU-powered offerings, the AWS g4dn.xlarge instance stands out as a popular, cost-efficient option for developers and businesses running light to moderate GPU workloads.
But how much does it really cost per hour to run this instance? And are there more economical alternatives available in India or elsewhere? This blog breaks it all down, including comparisons with Cyfuture Cloud and practical tips for choosing the right cloud GPU server at the right price.
The g4dn.xlarge instance is part of AWS’s G4 series, built specifically for graphics-intensive and machine learning workloads. It provides a great balance of price and performance for tasks that require GPU acceleration without going overboard.
GPU: 1 NVIDIA T4 Tensor Core GPU
vCPUs: 4 Intel Cascade Lake processors
RAM: 16 GB
Storage: 125 GB NVMe SSD
Networking: Up to 25 Gbps
It’s commonly used for:
AI inference (e.g., NLP, computer vision)
Low-latency game streaming
Video encoding and rendering
Virtual workstations
The g4dn.xlarge offers the best entry-level GPU instance on AWS for those who want to harness NVIDIA T4 capabilities without investing in heavier, pricier options like p3 or p4 instances.
The hourly pricing for g4dn.xlarge varies depending on the AWS region. Below are the updated pay-as-you-go prices (on-demand) for key markets:
Region |
Price/Hour (USD) |
Approx INR/hr |
US East (N. Virginia) |
$0.526 |
₹43.80 |
Asia Pacific (Mumbai) |
$0.654 |
₹54.50 |
Europe (Frankfurt) |
$0.578 |
₹48.10 |
Note: Prices can be reduced by opting for Reserved Instances or Savings Plans.
For long-term GPU-based workloads, running on-demand can quickly get expensive. Over a month (720 hours), the Mumbai pricing amounts to ₹39,240/month just for one instance.
This is where alternative cloud providers like Cyfuture Cloud become highly relevant—especially for startups, developers, and SMBs in India looking to reduce infrastructure costs without compromising on performance.
Cyfuture Cloud offers GPU-optimized cloud instances for AI inference, training, rendering, and more. While AWS delivers global infrastructure, Cyfuture Cloud caters specifically to Indian workloads, ensuring low latency and cost-effective computation.
Here’s a quick comparison:
Feature |
AWS g4dn.xlarge |
Cyfuture Cloud GPU Node |
GPU Type |
NVIDIA T4 |
NVIDIA T4 / A10 / A100 |
RAM |
16 GB |
16–64 GB |
Price/hour (INR) |
₹54.50 (Mumbai) |
Starts at ₹39/hour |
Storage |
125 GB SSD |
Custom (SSD/NVMe options) |
Hosting Location |
Mumbai DC |
Noida, Jaipur, Bangalore |
Uptime SLA |
99.99% |
99.95% |
Support |
Basic (AWS tiered) |
24/7 India-based support |
Data sovereignty – All data remains within India.
Cost-effective plans – Especially ideal for extended AI model testing and batch inference.
Instant provisioning – No long wait times to spin up instances.
Indian billing and support – No FX conversion hassles or international tax issues.
Deploying AI models that need T4 acceleration for inference
Real-time video rendering with moderate GPU power
Running small-to-medium ML workloads that don't require multi-GPU scaling
Cost-sensitive dev and test environments
GPU training of large AI/LLM models (use p3/p4 or A100-based instances)
High-frame-rate game streaming (requires more GPU memory)
Long-term hosting unless under Reserved Instance pricing
If you need greater control over costs, consider shifting workloads to a local cloud hosting provider with predictable billing—like Cyfuture Cloud.
If you decide to stay with AWS or any other cloud GPU provider, here are some ways to reduce your monthly bill:
Spot Instances – Can reduce costs by up to 80%, but may be interrupted.
Reserved Instances – Commit for 1–3 years and save 30-50%.
Auto-shutdown scripts – Avoid idle compute time.
Instance scheduling – Use AWS Lambda or third-party tools to schedule start/stop.
Move to Cyfuture Cloud – Pay in INR with no hidden fees, and get comparable GPU performance.
Whether you're using AWS or Cyfuture cloud, always factor in:
Uptime SLA: Aim for 99.9% or more.
Support availability: 24/7 human support helps during downtimes.
Storage IOPS: Don’t overlook performance of SSDs attached to your instance.
Data center proximity: Local data centers (e.g., Noida, Jaipur) offer faster latency for Indian users.
For short bursts of compute or light GPU inference workloads, the AWS g4dn.xlarge instance delivers reliable NVIDIA T4 performance and is easy to provision. But for long-running processes or tight budgets, costs can escalate quickly.
That’s where Cyfuture Cloud enters the frame—offering competitive GPU cloud hosting in India with local support, predictable pricing in INR, and performance comparable to AWS.
If you're an Indian business or developer team looking for cloud-native GPU infrastructure without breaking the bank, it’s time to explore hosting your workloads with Cyfuture Cloud. Not only do you get scalable servers and reliable uptime, but you also enjoy full control over your GPU resource consumption.
Let’s talk about the future, and make it happen!
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