E2E vs TensorCloud vs AWS India: Best GPU Cloud for Indian Startups
Head-to-head comparison of E2E Networks, TensorCloud, and AWS India for Indian AI startups. Pricing, platform depth, data residency, and total cost of ownership analysis.
If you're an Indian startup building AI products, you've probably narrowed your GPU cloud options to three categories: India-native providers like E2E Networks and TensorCloud, hyperscalers like AWS India, or global GPU clouds like Lambda and RunPod. Each has tradeoffs that matter depending on your workload, budget, compliance needs, and team size.
This guide compares the three options head-to-head across pricing, platform depth, data residency, support, and real-world use cases — so you can make the right choice for your stage and workload.
Disclosure: TensorCloud is operated by Tensordata. This comparison is written from our perspective, using public provider information and our published pricing. Readers should verify final pricing, availability, quotas, and support terms with each provider before procurement.
Pricing disclaimer: GPU cloud pricing changes frequently due to hardware availability, demand, region, currency movement, taxes, discounts, committed usage plans, and provider-level pricing updates. The prices in this article are indicative and based on publicly available or published rates at the time of writing. Always verify the latest price, availability, quota, and applicable taxes directly with the provider before making a purchase decision.
How we compare: All prices are public on-demand rates unless noted. We compare equivalent GPU configurations where possible. On-demand hourly rates multiplied by 730 hours are estimates, not reserved or monthly committed prices.
TL;DR
- Choose E2E Networks for a mature India-native GPU cloud with broad GPU fleet depth and enterprise familiarity.
- Choose TensorCloud for a bundled full-stack AI cloud experience with GPU, databases, storage, DNS, email, and one-click LLM deployment — built for startups shipping fast.
- Choose AWS India when you already depend on AWS services, credits, contracts, or enterprise governance.
The three options at a glance
| E2E Networks | TensorCloud | AWS India (ap-south-1) | |
|---|---|---|---|
| Headquarters | India (NSE-listed) | India | US (global) |
| GPU types | A100 80GB, H100, H200, B200 | A100 80GB, H100 | A100 40GB (p4d), A100 80GB (p4de), H100 (p5) |
| A100 80GB /hr | ~$2.10 | $1.35–$1.82 | Not directly comparable (see note below) |
| H100 /hr | ~$2.90 | $3.22 | Varies by purchase model |
| Platform depth | GPU cloud with broadening AI platform | Startup-focused full-stack GPU cloud | Full AWS ecosystem |
| Data residency | India | India | India (ap-south-1) |
| Billing | INR with GST | INR with GST | USD (INR via marketplace partners) |
| Min commitment | None | None | None (on-demand) |
| Support | 24x7, email, ticket | Direct, Telegram, email | Paid support tiers; Business Support+ starts at $29/month minimum, Enterprise Support is materially higher |
Important: GPU pricing is not always apples-to-apples. Providers differ in bundled vCPU, RAM, storage, public IP, network limits, support, monthly commitment discounts, and availability. Use the tables below as directional comparisons, not procurement quotes.
AWS pricing note: AWS India does not map cleanly to a single-GPU A100 80GB plan like India-native providers. AWS GPU instances are typically large multi-GPU instance families (P4d with A100 40GB, P4de with A100 80GB, P5 with H100). Availability, quota, and regional pricing should be verified in the AWS pricing calculator before procurement.
Pricing comparison: A100 80GB
The A100 80GB is the most common GPU for training and fine-tuning. Here's what a single GPU costs from India-native providers:
| Provider | On-demand /hr | 730-hour estimate | What's bundled |
|---|---|---|---|
| TensorCloud A100-Dev | $1.35 | $986 | 8 vCPUs, 32GB RAM, 200GB NVMe, public IP |
| TensorCloud A100-1 | $1.82 | $1,329 | 16 vCPUs, 64GB RAM, 500GB NVMe, public IP |
| E2E Networks | ~$2.10 | ~$1,533 | GPU + compute (E2E also offers lower monthly/annual committed rates) |
Note: E2E's public pricing page shows different hourly, monthly, and annual pricing tiers. The 730-hour estimate above uses the on-demand hourly rate and is not their actual monthly committed price. Commitment pricing is not directly comparable to on-demand.
TensorCloud's bundled plans include storage, a public IP, and compute — resources that are additional line items on other platforms when building a complete AI workload.
Pricing comparison: H100
| Provider | On-demand /hr | 730-hour estimate |
|---|---|---|
| E2E Networks | ~$2.90 | ~$2,117 |
| TensorCloud H100-1 | $3.22 | $2,351 |
| AWS (India region) | Varies by purchase model | Verify in pricing calculator |
E2E offers a lower H100 hourly rate. TensorCloud's H100-1 plan bundles 24 vCPUs, 192GB RAM, and 1TB storage — which closes the gap when you factor in additional compute and storage costs.
Platform depth comparison
All three providers offer GPU compute. The difference is in what else you get and how it's packaged.
| Service | E2E Networks | TensorCloud | AWS India |
|---|---|---|---|
| GPU compute | A100/H100/H200/B200, large fleet | A100/H100, bundled plans | P4/P5 instance families |
| Managed database | Available (DBaaS) | Available (4 PostgreSQL plans) | RDS, Aurora, DynamoDB |
| Object storage | Available | S3-compatible, 5GB free tier | S3 |
| Block storage | Available | Included in bundled plans | EBS |
| DNS management | Available | Available (PowerDNS-backed) | Route 53 |
| Load balancers | Available | Available ($0.01/hr) | ALB/NLB |
| AI model deployment | Available (TIR/model endpoints) | One-click deploy, 254+ pre-downloaded models | SageMaker, Bedrock |
| Transactional email | Not a core offering | Included (DKIM-signed, 10K free) | SES |
| Notebooks | Available | Available (GPU Jupyter) | SageMaker Notebooks |
| Overall orientation | Cloud/infrastructure-oriented | Startup/full-stack oriented | Enterprise ecosystem-oriented |
Where TensorCloud differentiates
The comparison table shows all three providers offer managed databases, DNS, model deployment, and storage. The difference is in bundling, workflow integration, and startup experience:
- Bundled plans — TensorCloud's GPU plans bundle compute, storage, public IP, and fair-use egress into a single hourly rate. Fewer separate infrastructure line items for common startup workloads.
- One-click LLM deployment — 254+ open-source models pre-downloaded and ready to deploy with an OpenAI-compatible API. No container setup, no model download wait.
- Integrated platform — GPU instances, managed databases, object storage, DNS, email, and load balancers on one dashboard with one invoice. No vendor-stacking.
- Direct support — Telegram, email, direct access to the engineering team. No tiered support plans.
- INR billing with GST — proper tax invoices for Indian companies, no FX risk.
Where E2E differentiates
- GPU fleet depth — E2E has a large GPU fleet including A100, H100, H200, and B200. TensorCloud's fleet is smaller but scaling.
- Enterprise maturity — NSE-listed, Rs 246 Cr FY26 revenue, established procurement and audit trail.
- Broader GPU selection — multiple GPU types and configurations for different workload sizes.
- 24x7 support — dedicated support infrastructure.
Where AWS differentiates
- Ecosystem depth — SageMaker, Bedrock, Lambda, S3, RDS, CloudFormation, IAM — the deepest managed service catalogue.
- Global multi-region — deploy across 30+ regions. India-native providers are India-only.
- Enterprise governance — Organizations, SCPs, CloudTrail, compliance certifications.
- Existing contracts — many enterprises already have AWS committed spend.
Total cost of ownership: a real example
Workload: One A100 80GB instance + 500GB storage + public IP + managed PostgreSQL (small) + 200GB egress/month.
| Cost component | E2E Networks | TensorCloud | AWS India |
|---|---|---|---|
| GPU compute (730 hrs on-demand) | ~$1,533 | $1,329 (A100-1 plan) | Verify in calculator |
| Block storage (500GB) | Additional | Included in plan | ~$40 (EBS gp3) |
| Public IP | Available | Included in plan | $3.65 |
| Managed PostgreSQL | Available (check pricing) | $44 (PG-S plan) | ~$50 (RDS db.t3.micro) |
| Data egress (200GB) | Check pricing | Included in plan (subject to fair use) | $18 |
| Monthly estimate | ~$1,533 + add-ons | $1,373 (bundled) | Significantly higher |
The key difference is not just raw GPU price — it is packaging. E2E may offer attractive committed GPU pricing, especially for teams that can assemble and operate the surrounding stack themselves. TensorCloud is designed to reduce the number of moving parts by bundling GPU compute, storage, public IP, fair-use egress, managed services, deployment workflow, and direct support into one startup-friendly platform. AWS provides the deepest ecosystem, but the final bill depends heavily on instance family, region, storage, data transfer, support plan, and managed service usage.
Data residency and compliance
| E2E Networks | TensorCloud | AWS India | |
|---|---|---|---|
| Data stays in India | Yes | Yes | Yes (ap-south-1) |
| INR billing + GST invoices | Yes | Yes | USD (INR via partners) |
| Indian entity | Yes (NSE-listed) | Yes (private) | No (US entity) |
| DPDP-ready deployment support | Possible with controls | Possible with controls | Possible with configuration |
| Sectoral compliance readiness | Possible with controls | Possible with controls | Possible with configuration and controls |
For Indian startups in regulated industries (BFSI, healthcare, government), working with an Indian entity that bills in INR with proper GST invoices simplifies procurement, tax credit, and audit. Data residency helps, but DPDP compliance still depends on contracts, access controls, logging, retention, deletion workflows, consent flows, and processor/sub-processor obligations.
Making the decision
For Indian AI startups, the right GPU cloud is not simply the cheapest GPU per hour. It is the platform that gets your model into production with the least friction, predictable billing, and the right level of operational control.
Choose E2E Networks if you want mature India-native GPU capacity and are comfortable assembling the broader stack. E2E may offer attractive committed GPU pricing, and their broadening AI platform gives you options as your needs grow.
Choose TensorCloud if you want a bundled AI cloud platform built around startup speed: GPU, storage, databases, DNS, email, LLM deployment, and direct support in one place. Best for teams that want to focus on building AI products, not managing infrastructure.
Choose AWS India if your team is already invested in AWS contracts, governance, SageMaker, Bedrock, or global multi-region architecture.
Get started with TensorCloud
Not sure which GPU you need? Tell us your model name, expected traffic, context length, and monthly budget. We'll recommend the right configuration and estimate your cost.
- Sign up at tensordata.com — no credit card required
- Choose a plan — A100-Dev at $1.35/hr is ideal for getting started
- Launch an instance — SSH-ready in under 5 minutes
- Deploy a model — one-click from our 254+ model registry
Or compare GPU pricing across all providers for the full breakdown.
Pricing sources and methodology
| Provider | Source |
|---|---|
| TensorCloud | Internal published pricing |
| E2E Networks | Public pricing page, documentation |
| AWS | EC2 instance types, on-demand pricing, support plans |
| GCP | GCP pricing calculator |
Pricing changes frequently and may vary by region, availability, commitment term, quota, taxes, exchange rate, and negotiated enterprise discounts. Always verify final pricing with the provider before procurement.
Pricing data last verified: June 2026. All prices are on-demand rates in USD unless otherwise noted. This post will be updated quarterly. Subscribe to our RSS feed for updates.
E2E Networks, AWS, Amazon Web Services, Google Cloud Platform, SageMaker, Bedrock, and NVIDIA are trademarks of their respective owners. TensorCloud is not affiliated with or endorsed by any of these companies.
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