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E2E Networks vs Gcore: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for E2E Networks and Gcore. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Provider type
Specialist
Specialist
Founded
2009
2014
Headquarters
New Delhi, India
Luxembourg
Billing model
On-demand
On-demand, Reserved
Min commitment
None
None
Support tier
Standard → Enterprise
Standard → Enterprise
Regions
1 regions
5 regions

Strengths & Best For

E2E Networks

E2E Networks is an Indian GPU cloud provider offering H200, H100, A100 80GB, A100 40GB, and L40S instances with India data residency and competitive pricing for the South Asian market. On-demand billing and India-based data centers make it a practical choice for Indian AI teams with data residency requirements or latency-sensitive inference workloads. Listed on NSE (National Stock Exchange of India). A strong domestic option for Indian organizations that want GPU compute without routing data through international cloud providers.

Strengths
  • India data residency — data stays in India
  • H200 and H100 availability
  • NSE-listed — established Indian cloud provider
  • Competitive pricing for South Asian market
  • On-demand billing with no minimum commitment
Weaknesses
  • Primarily India-focused — limited global regions
  • Smaller GPU catalog than hyperscalers
  • Less mature ML ecosystem vs global providers
Best For
Indian AI teams with data residency requirementsSouth Asian enterprises needing local data storageCost-sensitive Indian ML workloadsTeams needing low-latency GPU access within India
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Gcore

Gcore is a global GPU cloud and CDN provider offering H100, A100, L40S, and L4 instances across 40+ points of presence worldwide, with ultra-low latency networking and built-in DDoS protection for edge AI inference workloads. On-demand and reserved billing options are available, making it a versatile GPU cloud for teams that need both compute and network performance at a global scale. A top choice for latency-sensitive AI inference applications that need to serve users across multiple continents.

Strengths
  • 40+ global PoPs with ultra-low latency networking
  • Built-in DDoS protection
  • H100, A100, L40S, L4 availability
  • CDN + GPU compute in one provider
Weaknesses
  • Smaller provider — limited scale vs hyperscalers
  • Less mature ML tooling vs specialist AI clouds
  • Support quality varies by region
Best For
Global inference deployment needing low latencyLatency-sensitive AI applications serving multiple continentsTeams needing edge compute with DDoS protection
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Key differences

E2E Networks

Indian GPU cloud — H200, H100, A100 with India data residency

Gcore

Global GPU cloud and CDN — H100, A100, L40S across 40+ PoPs worldwide

AttributeE2E NetworksGcore
Provider typespecialistspecialist
Billing modelOn-demandOn-demand, Reserved
Min commitmentNoneNone
Regions1 (IN)5 (EU, US, APAC, +2)
Support tierStandard → EnterpriseStandard → Enterprise
Best forIndian AI teams with data residency requirements, South Asian enterprises needing local data storageGlobal inference deployment needing low latency, Latency-sensitive AI applications serving multiple continents
Founded / HQ2009 · New Delhi, India2014 · Luxembourg