Quick Overview
Compute from
₹1,642/mo
E2E Networks
Compute from
Calculator-led
Google Cloud
GPU from
$0.57/hr
E2E L4
GPU from
Region-specific
Google Cloud
Feature Comparison
| Feature | E2E E2E Networks | GCP Google Cloud |
|---|---|---|
| Provider focus | Indian GPU cloud and AI infrastructure | Global data/AI cloud with Vertex AI, BigQuery and GKE |
| GPU pricing clarity | Public E2E GPU table with hourly rates | Official GPU pricing exists but final VM cost is SKU and region based |
| H100 options | $2.90/hr public H100 price | A3 H100 SXM machine families with 1/2/4/8 GPU shapes |
| AI platform | TIR inference/model endpoints and GPU cloud | Vertex AI, BigQuery, GKE, TPUs and integrated ML services |
| India regions | India-focused local GPU cloud | Mumbai and Delhi Google Cloud regions |
| Data transfer | Validate per E2E service | Network egress charges apply by route/destination |
| Billing simplicity | Straightforward public GPU table | Powerful but SKU-heavy billing model |
| Best fit | AI teams seeking Indian GPU price clarity | Data/AI teams built around Google Cloud services |
Highlighted rows show the stronger fit for that category. Tie means both providers can be valid depending on workload and contract terms.
Pricing Comparison
E2E
E2E Networks Pricing| Cloud VM reference | ₹1,642/mo |
| C2.12GB · 4 vCPU · 12 GB RAM · 100 GB SSD | |
| NVIDIA L4 | $0.57/hr |
| 24 GB vRAM · 25 vCPU · 110 GB RAM | |
| NVIDIA L40S | $1.20/hr |
| 48 GB vRAM · 60 vCPU · 220 GB RAM | |
| NVIDIA H100 | $2.90/hr |
| 80 GB vRAM · 26 vCPU · 250 GB RAM | |
Public GPU table · per-minute GPU billing · hourly/monthly/annual options
GCP
Google Cloud Pricing| Compute Engine | Calculator-led |
| Machine, disk, OS and region dependent | |
| GPU pricing | USD SKU-led |
| Separate GPU plus VM charges may apply | |
| A3 H100 | 1/2/4/8 GPU shapes |
| A3 High/Mega/Edge family docs | |
| Data transfer | Charged by route |
| Validate egress architecture | |
Provider prices can change. Validate final SKU, region, taxes, bandwidth and support terms.
⚠️ Note: Public prices can vary by region, GPU count, commitment term, OS, IPs, storage and network usage. Treat this page as a comparison draft and verify every production quote with the provider.
Our Verdict
E2E
E2E Networks wins for GPU-led AI infrastructure
E2E Networks is stronger for price-led GPU buyers who want a simpler Indian GPU cloud comparison before dealing with quota and complex SKU pricing.
Public GPU pricingH100/H200/L40S/L4Indian cloud
GCP
Google Cloud wins for its strongest-fit use cases
Google Cloud wins where the workload depends on Vertex AI, BigQuery, GKE, global data services or Google-native AI pipelines.
🌍 HyperscalerUse-case specific winner
| Use case | E2E Networks | Google Cloud |
|---|---|---|
| GPU price-led AI workloads | ★★★ | ★ |
| Vertex AI / BigQuery stack | ★ | ★★★ |
| Global regions | ★★ | ★★★ |
| India regions | ★★ | ★★★ |
| Simpler GPU procurement | ★★★ | ★ |
| Kubernetes/data platform depth | ★★ | ★★★ |
Data Notes
E2E pricing uses public E2E pages. Google Cloud details use official Compute Engine GPU documentation and GPU pricing pages. Final cost depends on machine family, region, disk, network and commitment terms.