![Cloud GPU Pricing Comparison in India [2026]](data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMTIwMCA2MjgiIHdpZHRoPSIxMjAwIiBoZWlnaHQ9IjYyOCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj48L3N2Zz4=)
AI is moving from pilots to production and GPU spend is fast becoming a board-level line item. Hence, we have compared cloud GPU providers in India (INR) like AceCloud, AWS, Google Cloud, Microsoft Azure, DigitalOcean and E2E Networks.
Our aim is practical, not theoretical. We want you to match workloads to GPU classes (H100/A100/L40S/L4/A30/RTX) and understand the budget impact of hourly and monthly Cloud GPU pricing options.
So, read this as a TCO starting point, i.e., figures reflect listed prices in INR*, excluding taxes, network egress, sustained use or commitment discounts and Spot/Preemptible variability.
We highly recommend you use it to set envelopes for FY25-26 planning, negotiate supplier terms and choose the right mix of cost, performance and control for each workload. Letโs get started!
AceCloud (Hourly Pricing)
AceCloud provides pay-as-you-go GPU servers aimed at AI training, fine-tuning, inference, rendering and data science.
You can match GPUs to workload needs (from high-end H100 to cost-savvy A2/L4) and size CPU/RAM alongside them.
| Model | Flavor Name | GPUs | vCPUs | RAM (GB) | Hourly* |
|---|---|---|---|---|---|
| NVIDIA H100 โ HGX | N.HGXH100.250 | 1 | 26 | 250 | โน315.07 |
| NVIDIA A100 | N.A100.128 | 1 | 16 | 128 | โน184.93 |
| NVIDIA A30 | N.A30.32 | 1 | 8 | 32 | โน71.92 |
| NVIDIA A2 | N.A2.32 | 1 | 8 | 32 | โน23.01 |
| RTX A6000 | N.RTXA6000.64 | 1 | 16 | 64 | โน59.08 |
| NVIDIA RTX 6000 Ada | N.RTX6000ADA.64 | 1 | 16 | 64 | โน84.28 |
| NVIDIA L4 | N.L4.32 | 1 | 8 | 32 | โน41.92 |
| NVIDIA L40S | N.L40S.64 | 1 | 16 | 64 | โน123.29 |
Instances can be spun up quickly, scaled or paused as projects evolve and paired with containers or your preferred ML frameworks.
The goal is predictable performance with transparent INR pricing so teams can budget experiments and production runs without surprises.
*You can avail these instances at hourly rates if your billing reaches 200+ hours. Connect with AceCloudโs Cloud GPU consultant using free consultation to learn more.
Amazon AWS (Hourly Pricing)
AWS Cloud GPU services deliver managed, on-demand accelerators for training, inference and visualization, integrating with EC2, EKS, autoscaling and spot pricing.
| Model | Storage | vCPU | Memory | Hourly Billing |
|---|---|---|---|---|
| (H100) P5.4xlarge | 1 x 3840 GB SSD | 16 | 256 GiB | โน720.33 |
| (A100) P4d.24xlarge | 8 x 1000 SSD | 96 | 1152 GiB | โน2298.52 |
| (L4) G6.xlarge | 1 x 250 GB NVMe SSD | 4 | 16 GiB | โน84.32 |
Choose H100 for cutting-edge training, A100 for large multi-GPU workloads and L4 for cost-efficient inference or graphics. Management is via familiar AWS tooling.
Google GCP (Hourly Pricing)
Google Cloud GPU services provide on-demand accelerators for training, inference and visualization across Vertex AI, GKE and Compute Engine, with flexible pricing, autoscaling and Spot options.
| Model | Region | Hourly Billing |
|---|---|---|
| A100 80GB | Mumbai | โน491.534806 |
| H100 | Mumbai | โน1,061.454025 |
| L4 | Mumbai | โน60.735897 |
You can integrate with Googleโs secure networking, storage and observability stacks and enforce budgets via labels and quotas.
Managed images and NVIDIA MIG profiles simplify right-sizing, tenancy and isolation.
Microsoft Azure (Hourly Pricing)
Microsoft Azure GPU services provide on-demand NVIDIA accelerators via NC/ND-series VMs, integrated with Azure Machine Learning, AKS, VM Scale Sets, Spot capacity and reservation pricing.
| Model | vCPUs | RAM | Temp storage | GPU | Hourly Billing |
|---|---|---|---|---|---|
| H100 NC40ads v5 | 40 | 320 GiB | 3,576 GiB | 1ร H100 | โน848.4050 |
| A100 NC24ads v4 | 24 | 220 GiB | 958 GiB | 1ร A100 | โน446.4284 |
Management hooks include Azure Policy, budgets/tags and role-based access control, with images and (where available) MIG to right-size inference and training.
DigitalOcean (Hourly Pricing)
DigitalOcean GPU Droplets offer straightforward, hourly pricing and a simple developer experience.
Spin up single-GPU instances for training, fine-tuning, inference or graphics, then scale with DOKS (Kubernetes), VPC networking, block storage and monitoring.
| Model | GPU memory (total) | Droplet memory | vCPUs | Boot disk | Hourly Billing |
|---|---|---|---|---|---|
| H200 | 141 GB | 240 GiB | 24 | 720 GiB NVMe | โน300.15 |
| H100 | 80 GB | 240 GiB | 20 | 720 GiB NVMe | โน588.09 |
| RTX 6000 Ada | 48 GB | 64 GiB | 8 | 500 GiB NVMe | โน136.99 |
| L40S | 48 GB | 64 GiB | 8 | 500 GiB NVMe | โน136.99 |
Teams can use projects, tags and budgets to track spend; snapshots and reserved IPs ease lifecycle management.
E2E Networks (Hourly Pricing)
E2E Networks offers India-based GPU Dedicated Compute with simple, INR-denominated hourly pricing, which is handy for teams training, fine-tuning or running inference close to users in the region.
Plans span cutting-edge H200/H100 to value options like L4 and A30.
| Model | GPU Memory | vCPUs | Ded RAM (GB) | Disk Space | Hourly Billing |
|---|---|---|---|---|---|
| H200 Plans | 141 GB | 30 | 375 | 3750 GB NVMe | โน183 |
| H100 Plans | 80 GB | 26 | 250 | 3000 GB NVMe | โน175 |
| A100 80GB | 4 ร 80 GB | 64 | 460 | 250 GB SSD | โน400 |
| L40S | 1 ร 48 GB | 25 | 220 | 250 GB SSD | โน83 |
| A30 | 1 ร 24 GB | 16 | 90 | 640 GB SSD | โน96 |
| L4 | 1 ร 24 GB | 25 | 110 | 250 GB SSD | โน50 |
You can choose single-GPU nodes for experiments or multi-GPU A100 for heavier training.
The specs are straightforward (fixed vCPUs, RAM and NVMe/SSD), so itโs easy to estimate cost and performance without surprises.
If you want a complete bill estimate beyond GPU-hour pricing (compute, storage, and network/egress), follow our step-by-step cloud cost estimation guide.
Cloud GPU Monthly Pricing Comparison in India
Below is a side-by-side comparison of cloud GPU pricing, organized by GPU model across major providers.
NVIDIA H100 (Monthly Pricing)
For an 8ร H100 (80 GB each) monthly setup, AceCloud costs โน16 lakh. AWS is ~โน42.9 lakh, Azure ~โน38.6 lakh and Google Cloud ~โน58.8 lakh.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| GPUs | 8 | 8 | 8 | 8 | 8 | 8 |
| vCPU | 208 | 200 | 208 | 192 | 96 | 160 |
| RAM | 2000GB | 1800GB | 1872GB | 2040GB | 1900GB | 1920GB |
| vRAM | 8 * 80GB | 8 * 80GB | 8 * 80GB | 8 * 80GB | 8 * 80GB | 8 * 80GB |
| Monthly Billing | โน16,00,000 (No hidden fees) | โน16,76,000 | โน58,79,378 | โน42,92,377 | โน38,58,540 | โน16,42,751 |
| Support | 24/7 Dedicated Human Support (No Bots) | Limited support | Paid support plans | Paid support plans | Paid support plans | Paid support plans |
| Free Credits | โน20,000 Free credits | โน17,000 | โน25,000 | โน17,000 | โน17,000 | โน17,000 |
That makes AceCloud roughly 63% cheaper than AWS, 59% cheaper than Azure and 73% cheaper than GCP, saving about โน27 lakh vs AWS, โน22.6 lakh vs Azure and โน42.8 lakh vs GCP each month.
For a detailed buy vs rent breakdown, plus India purchase ranges and where to buy, read our NVIDIA H100 price in India guide.
NVIDIA A100 (Monthly Pricing)
For an A100 monthly setup (per your table), AceCloud costs โน3.6 lakh. AWS is ~โน17.56 lakh and Google Cloud ~โน15.54 lakh; Azure price wasnโt available at the time of writing.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 64 | 64 | 48 | 96 | 96 | – |
| GPUs | 4 | 4 | 4 | 8 | 8 | – |
| RAM | 512GB | 460GB | 680GB | 1152GB | 900GB | – |
| vRAM | 4 * 80GB | 4 * 80GB | 4 * 80GB | 8 * 80GB | 8 * 80GB | – |
| Monthly Billing | โน360,000 (No hidden fees) | โน400,000 | โน15,53,958 | โน17,55,972 | N/A | – |
| Support | 24/7 Dedicated Human Support (No Bots) | Limited support | Paid support plans | Paid support plans | Paid support plans | – |
| Free Credits | โน20,000 Free credits | โน17,000 | โน25,000 | โน17,000 | โน17,000 | – |
That makes AceCloud about 79.5% cheaper than AWS and 76.8% cheaper than GCP, saving roughly โน14.0 lakh vs AWS and โน11.9 lakh vs GCP each month.
Get A100 at Unbeatable Monthly Price on AceCloud
NVIDIA L4 (Monthly Pricing)
For a single NVIDIA L4 (24 GB) monthly setup, AceCloud costs โน27,500. AWS is ~โน102,672 and Google Cloud ~โน76,000.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 16 | 25 | 16 | 16 | – | – |
| GPUs | 1 | 1 | 1 | 1 | – | – |
| RAM | 64GB | 110GB | 64GB | 64GB | – | – |
| vRAM | 1 * 24GB | 1 * 24GB | 1 * 24GB | 1 * 24GB | – | – |
| Monthly Billing | โน27,500 (No hidden fees) | โน31,755 | โน76,000 | โน102,672 | – | – |
| Support | 24/7 Dedicated Human Support (No Bots) | Limited support | Paid support plans | Paid support plans | – | – |
| Free Credits | โน20,000 Free credits | โน17,000 | โน25,000 | โน17,000 | – | – |
That makes AceCloud roughly 73% cheaper than AWS and 64% cheaper than GCP, saving about โน75,172 vs AWS and โน48,500 vs GCP each month.
Spin up L4 Instances with Cost-effective Monthly Plans on AceCloud
NVIDIA L40S (Monthly Pricing)
For a single NVIDIA L40S (48 GB) monthly setup, AceCloud costs โน63,793. AWS is about โน1,94,928 and DigitalOcean about โน1,01,752.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 16 | 25 | – | 16 | – | 8 |
| GPUs | 1 | 1 | – | 1 | – | 1 |
| RAM | 128GB | 220GB | – | 128GB | – | 64GB |
| vRAM | 1 * 48GB | 1 * 48GB | – | 1 * 48GB | – | 1 * 48GB |
| Monthly Billing | โน63,793 (No hidden fees) | โน49,000 | – | 194,928 | – | โน1,01,752 |
| Support | 24/7 Dedicated Human Support (No Bots) | Limited support | – | Paid support plans | – | Paid support plans |
| Free Credits | โน20,000 Free credits | โน17,000 | – | โน17,000 | – | โน17,000 |
That makes AceCloud roughly 67% cheaper than AWS (saving โน1,31,135/mo) and 37% cheaper than DigitalOcean (saving โน37,959/mo). GCP and Azure prices werenโt available at the time of writing.
Deploy L40s at Lowest Monthly Price On AceCloud Today
NVIDIA A30 (Monthly Pricing)
For a single NVIDIA A30 (24 GB) monthly setup, AceCloud costs โน35,000. E2E Networks is โน40,000.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 8 | 16 | – | – | – | – |
| GPUs | 1 | 1 | – | – | – | – |
| RAM | 32GB | 90GB | – | – | – | – |
| vRAM | 1 * 24GB | 1 * 24GB | – | – | – | – |
| Monthly Billing | โน35,000 (No hidden fees) | โน40,000 | – | – | – | – |
| Support | 24/7 Dedicated Human Support (No Bots) | Limited support | – | – | – | – |
| Free Credits | โน20,000 Free credits | โน17,000 | – | – | – | – |
That makes AceCloud 12.5% cheaper, saving โน5,000 per month. Prices for AWS, Azure, GCP and DigitalOcean werenโt available at the time of writing.
Launch A30 Workloads At AceCloudโs Best Price
NVIDIA A2 (Monthly Pricing)
For NVIDIA A2, AceCloud stands out as the competition doesnโt offer the GPU model.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 8 | – | – | – | – | – |
| GPUs | 1 | – | – | – | – | – |
| RAM | 32GB | – | – | – | – | – |
| vRAM | 1 * 16GB | – | – | – | – | – |
| Monthly Billing | โน12,000 (No hidden fees) | – | – | – | – | – |
| Support | 24/7 Dedicated Human Support (No Bots) | – | – | – | – | – |
| Free Credits | โน20,000 Free credits | – | – | – | – | – |
Try Nvidia A2 GPUs Only on AceCloud
NVIDIA RTX A6000 (Monthly Pricing)
For NVIDIA RTX A6000, only AceCloud is the contender for Cloud GPU service in India.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 16 | – | – | – | – | – |
| GPUs | 1 | – | – | – | – | – |
| RAM | 64GB | – | – | – | – | – |
| vRAM | 1 * 48GB | – | – | – | – | – |
| Monthly Billing | โน37,500 (No hidden fees) | – | – | – | – | – |
| Support | 24/7 Dedicated Human Support (No Bots) | – | – | – | – | – |
| Free Credits | โน20,000 Free credits | – | – | – | – | – |
Rent RTX A6000 At AceCloudโs Lowest Rate
NVIDIA RTX 6000 Ada (Monthly Pricing)
For a single NVIDIA RTX 6000 Ada (48 GB) monthly setup, AceCloud costs โน53,500. DigitalOcean is ~โน1,02,106.
| Feature | AceCloud | E2E Networks | Google Cloud | AWS | Azure | Digital Ocean |
|---|---|---|---|---|---|---|
| vCPU | 16 | – | – | – | – | 8 |
| GPUs | 1 | – | – | – | – | 1 |
| RAM | 64GB | – | – | – | – | 64GB |
| vRAM | 1 * 48GB | – | – | – | – | 1 * 48GB |
| Monthly Billing | โน53,500 (No hidden fees) | – | – | – | – | โน1,02,106 |
| Support | 24/7 Dedicated Human Support (No Bots) | – | – | – | – | Paid support plans |
| Free Credits | โน20,000 Free credits | – | – | – | – | โน17,000 |
That makes AceCloud roughly 48% cheaper, saving about โน48,606 per month. Prices for E2E Networks, Google Cloud, AWS and Azure werenโt available at the time of writing.
Rent RTX 6000 Ada at Unbeatable Pricing with AceCloud
Stay Cost-Effective, Choose AceCloud!
Enterprise buyers should anchor decisions in unit economics (โน/GPU-hour or โน/training run) and operational fit. From the comparison, AceCloud and E2E often deliver the lowest INR prices for equivalent GPUs.
This is particularly true for H100 and L4 while AWS, Azure and GCP command higher rates but offer deeper ecosystems, multi-region scale and managed services.
We suggest a pragmatic path:
- Classify workloads (cutting-edge training, mainstream training or inference/graphics),
- Right-size GPUs (H100/A100 vs L40S/L4/A30),
- Pilot on two providers to baseline performance and stability,
- Model full TCO including storage, inter-AZ traffic, egress, support tiers and commitments, and
- Enforce FinOps, i.e., budgets, tags and cost per request/token.
If lowering โน/GPU-hour is a priority, start a short PoC on AceCloud (e.g., H100 for training, L4/L40S for inference), use the โน20,000 credits noted above and request a tailored INR quote with capacity planning and FinOps guardrails.
Engage AceCloud to benchmark your workloads and lock in predictable monthly spending!
*The hourly and monthly rates in the post are from Feb 2026. The details are subject to changing exchange rates, data center regions and resource availability across Cloud GPU providers.
