Google's cloud platform - Compute Engine, GKE, BigQuery, Vertex AI, H100/A100/TPU compute, and Mumbai & Delhi regions. Built on Google's own global fibre network, with automatic Sustained Use Discounts and the deepest AI/ML tooling of any cloud.
Google Cloud Platform (GCP), launched as App Engine in 2008 and headquartered in Mountain View, California, is the cloud division of Alphabet/Google. Powered by the same infrastructure that runs Google Search, Gmail, YouTube, and Maps, it now holds roughly 13% of global cloud market share - third behind AWS (31%) and Azure (21%) - and generated $58.7 billion in revenue in 2025, its first full year of sustained profitability.
For Indian teams, Google Cloud operates two full-scale regions: asia-south1 (Mumbai) and asia-south2 (Delhi). Both offer Compute Engine, GKE, Cloud SQL, BigQuery, Vertex AI, and Cloud Storage. Mumbai is one of the few regions globally with H100 GPU (A3 instances) and A100 availability. The Delhi region is newer and growing in service coverage. Google has committed $2 billion in India infrastructure investment.
GCP's strongest differentiators are its AI/ML ecosystem - Vertex AI (managed ML platform), Gemini models via Vertex AI Model Garden, TPUs (Tensor Processing Units) for extreme-scale training, and BigQuery for petabyte-scale serverless analytics. It also leads on Kubernetes - Google invented K8s, and GKE (Google Kubernetes Engine) remains the gold standard managed K8s service. Its global private fibre network delivers some of the lowest global latencies of any hyperscaler.
GCP's unique pricing advantages include automatic Sustained Use Discounts (SUDs) - up to 30% off for instances running more than 25% of a month with no commitment - and Spot VMs with up to 91% discount. Committed Use Discounts (CUDs) offer 37-55% savings over 1-3 years. These stack to make GCP highly competitive for long-running steady workloads.
All prices in USD per month, on-demand. Mumbai region typically adds ~15-20% premium over us-central1. Per-second billing (1-minute minimum). Persistent disk storage billed separately ($0.08โ0.17/GB-month). Auto-applied SUDs where eligible.
Full price, no commitment. Per-second with 1-minute minimum. Best for dev, testing, and unpredictable workloads.
Up to 30% off automatically for N1/N2/M-series instances running 25%+ of a month. Unique to GCP - zero action required.
37-55% savings. Flexible spend-based CUDs cover compute across families. Resource CUDs lock to specific families for deeper discounts.
| Machine type | vCPU | RAM | On-Demand / hr | ~Monthly | Spot VM |
|---|---|---|---|---|---|
| e2-micro | 2 (shared) | 1 GB | $0.0084 | ~$6 | Always Free* |
| e2-small | 2 (shared) | 2 GB | $0.0168 | ~$12 | ~$3 |
| e2-standard-2 | 2 | 8 GB | $0.067 | ~$48 | ~$10 |
| e2-standard-4 | 4 | 16 GB | $0.134 | ~$97 | ~$20 |
* e2-micro always free in us-west1, us-central1, us-east1 only - not Mumbai. Mumbai e2-micro billed at standard rate.
| Machine type | vCPU | RAM | On-Demand / hr | ~Monthly | With SUD (30%) |
|---|---|---|---|---|---|
| n2-standard-2 | 2 | 8 GB | $0.097 | ~$70 | ~$49 |
| n2-standard-4 | 4 | 16 GB | $0.194 | ~$140 | ~$98 |
| n2-standard-8 | 8 | 32 GB | $0.388 | ~$280 | ~$196 |
| Instance / Type | Accelerator | Count | VRAM | Region | On-Demand / hr |
|---|---|---|---|---|---|
| โก GPU A3 Mega (a3-megagpu-8g) | H100 (Mega) | 8ร | 640 GB | ๐ฎ๐ณ Mumbai | ~$112 |
| โก GPU A2 Ultra (a2-ultragpu-8g) | A100 (80 GB) | 8ร | 640 GB | ๐ฎ๐ณ Mumbai | ~$53 |
| โก GPU G2 Standard (g2-standard-4) | NVIDIA L4 | 1ร | 24 GB | Multiple regions | $0.70 |
| ๐ง TPU TPU v5e (single chip) | Google TPU v5e | 1ร | 16 GB HBM | US / EU | $1.20 |
| ๐ง TPU Ironwood TPU (v6e - preview) | Google Ironwood | 1ร | 32 GB HBM | US (preview) | Contact sales |
| Service | Starting price | Notes |
|---|---|---|
| Cloud Storage (GCS) | $0.02/GB-mo | Standard class in Mumbai. 5GB free. Egress $0.12/GB after 1TB. |
| Cloud SQL (PostgreSQL/MySQL) | ~$18/mo | db-f1-micro, 10 GB SSD. HA doubles cost. Automatic backups included. |
| GKE (Kubernetes) | $0.10/hr/cluster | $73/mo control plane. One Autopilot cluster free. Pay for nodes separately. |
| BigQuery | $6.25/TB queried | First 1TB/month free. Storage: $0.02/GB-month. Serverless - no clusters to manage. |
| Vertex AI (Gemini Pro) | Pay per token | Gemini 1.5 Pro: $1.25/M input tokens. Access Llama, Mistral, and open models too. |
| Cloud Run (Serverless) | Free tier | 2M requests/mo free. $0.40/M beyond. Pay only when handling requests. |
| Cloud CDN + Load Balancing | $0.008/GB | Cache egress in India. LB: $0.025/hr + $0.008/GB processed. Cheaper than CloudFront. |
| Region | City | Code | Zones | GPU / AI |
|---|---|---|---|---|
| ๐ฎ๐ณ Asia South | Mumbai | asia-south1 | 3 | โ H100 (A3), A100, L4, Cloud Run GPU* |
| ๐ฎ๐ณ Asia South | Delhi | asia-south2 | 3 | L4, Cloud Run GPU* (invite-only) |
| ๐ธ๐ฌ Asia Southeast | Singapore | asia-southeast1 | 3 | โ A100, L4 |
| ๐ฏ๐ต Asia Northeast | Tokyo | asia-northeast1 | 3 | โ H100 (A3), A100 |
| + 36 more regions across USA, Europe, Middle East, South America, Africa | ||||
* Cloud Run GPU in Mumbai and Delhi is currently invitation-only - contact your Google account team. A3 Mega (H100) and A2 Ultra (A100) in Mumbai available as standard Compute Engine instances. Full list at cloud.google.com/about/locations.
Compare Google Cloud against other providers popular with Indian teams:
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Developer cloud with Bangalore DC and Droplets from $4/mo. Better DX, simpler pricing, and no complexity tax vs GCP. Best for startups that don't need BigQuery or Vertex AI.
European cloud with a Mumbai DC and H100/A100 in European regions. Better raw VPS/GPU pricing than GCP; no Vertex AI or BigQuery equivalent. Good for GDPR workloads.
Get $300 in credits for your first 90 days - valid on all GCP products including Compute Engine, GKE, BigQuery, Vertex AI, and Cloud Storage.
Claim $300 Free Credit โGCP bills in USD and is not MeitY-empanelled. GPU in Mumbai costs ~4-5ร more than Indian providers. Use GCP when you need Vertex AI, BigQuery, or GKE - use Indian providers for raw compute cost savings and INR billing.
See how GCP stacks up against AWS, Azure, and Indian cloud providers.
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