AceCloud
E2E Networks
You want a managed Indian cloud for VMs, GPUs, Kubernetes, databases and storage with human support, predictable INR billing, unmetered bandwidth and no egress charges.
You need a self-serve AI-first GPU cloud with MeitY empanelment, B200/H200/H100 availability, INR GPU pricing and India data residency for AI/ML workloads.
Quick Overview
Feature Comparison
| Feature | ACE AceCloud | E2E E2E Networks |
|---|---|---|
| Provider positioning | 🇮🇳 Indian managed cloud VMs, GPUs, Kubernetes, storage, databases, networking | 🇮🇳 AI-first hyperscaler GPU cloud, TIR AI/ML platform, storage, AI services |
| Public listing / MeitY | ~ Private brand Brand of RTDS group; not publicly listed | ✓ NSE-listed + MeitY empanelled Useful for public sector and regulated procurement |
| General compute pricing | from ₹1,015/mo Standard Instances; hourly and monthly plans | ~ Calculator/account based Public pricing page currently emphasizes GPU and storage pricing |
| GPU cloud range | ✓ H100, A100, L40S, L4, A30, A2 H100 HGX 1× monthly from ₹180,000; hourly H100 listed at ₹315.07* | ✓ B200, H200, H100, A100, L40S, A30, L4 L4 from ₹49/hr; H100 from ₹249/hr; H200 from ₹300/hr |
| Data centre / residency coverage | ✓ 3 data centers India-first cloud with Noida, Mumbai and Atlanta references on pricing pages | ✓ India data residency Delhi NCR for GPU page; MeitY page references Mumbai and Delhi-NCR regions |
| Billing currency | ₹ INR UPI, credit cards and debit cards for India customers | ₹ INR / $ USD pages GPU page shows INR; pricing page also exposes USD view |
| Bandwidth / egress | ✓ No egress cost Unmetered bandwidth and no data transfer charge mentioned publicly | ~ Check plan details Storage, IP and network add-ons should be reviewed in calculator/account |
| Support style | ✓ 24×7 human support Public cloud page highlights <15 min human support | ✓ 24/7 IST support GPU page mentions local support in IST timezone |
| Uptime SLA | 99.99%* | 99.95% |
| AI platform depth | ✓ GPU + infra stack Good for AI teams that want managed infrastructure support | ✓ GPU + TIR + model services Good for self-serve AI platform workflows |
| Migration / onboarding | ✓ Guided migration AceCloud mentions migration planning and dedicated engineer support | ~ More self-serve Strong dashboard and calculator-led buying flow |
| Best-fit buyer | Enterprises, SMBs and AI teams wanting managed infra help, cost predictability and low-egress architecture | AI startups, research teams and public-sector-aligned buyers needing fast GPU access, MeitY alignment and self-serve GPU workflows |
✓ Winner in this category · ~ Partial · Highlighted rows = clear edge · *Always verify plan, taxes, region, commitment and eligibility before purchase.
Pricing Comparison
General Compute / Cloud Servers
| Standard Instances | from ₹1,015/mo |
| Billing cycle | Hourly / Monthly |
| Data transfer | No egress charge |
| Compute VMs | via calculator/account |
| Public pricing emphasis | GPU + storage |
| Storage pricing | Object $0.03/GB-mo |
GPU Cloud
| NVIDIA H100 HGX (80 GB) | ₹180,000/mo |
| NVIDIA H100 hourly* | ₹315.07/hr |
| NVIDIA A100 | ₹184.93/hr |
| NVIDIA L40S | ₹123.29/hr |
| NVIDIA L4 | ₹41.92/hr |
| NVIDIA B200 (192 GB) | ₹430/hr |
| NVIDIA H200 (141 GB) | ₹300/hr |
| NVIDIA H100 (80 GB) | ₹249/hr |
| NVIDIA A100 80GB | ₹189/hr |
| NVIDIA L40S | ₹102/hr |
| NVIDIA L4 | ₹49/hr |
Our Verdict
AceCloud wins for managed cloud, support and cost predictability
Pick AceCloud when your team wants a broader managed infrastructure partner, not only raw GPU capacity. It is stronger for buyers who value guided onboarding, migration support, human response, unmetered bandwidth and no egress-cost positioning across compute, GPU, Kubernetes, database, storage and network services.
E2E Networks wins for self-serve GPU breadth and MeitY-aligned buying
Pick E2E Networks when you need quick access to a wider public GPU catalogue including B200, H200, H100, A100, L40S and L4, and when MeitY empanelment or NSE-listed-company transparency matters for procurement. It is especially relevant for AI teams comfortable with self-serve infrastructure workflows.
| Use case | AceCloud | E2E Networks |
|---|---|---|
| Managed cloud migration and onboarding | ★★★ | ★★ |
| GPU breadth and newest listed accelerators | ★★ | ★★★ |
| No egress / bandwidth predictability | ★★★ | ★★ |
| Government / PSU procurement alignment | ★★ | ★★★ |
| Enterprise AI infrastructure support | ★★★ | ★★★ |
| Self-serve GPU experimentation | ★★ | ★★★ |
| SMB / startup cloud stack beyond GPUs | ★★★ | ★★ |
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