E2E Networks vs TensorDock: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for E2E Networks and TensorDock. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
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.
- 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
- Primarily India-focused — limited global regions
- Smaller GPU catalog than hyperscalers
- Less mature ML ecosystem vs global providers
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TensorDock is a GPU cloud marketplace connecting users with independent hosts across 100+ global locations. 45+ GPU models from consumer RTX cards to HGX H100 SXM5, including H100 SXM5, A100 SXM4, and RTX 4090. Pay-per-second billing with no minimum commitments, no waitlists, and no quotas. Hosts compete on price, keeping rates among the lowest available. KVM virtualization with root access and dedicated GPUs. Windows 10 support. Voltage Park (merged with Lightning AI) is a TensorDock partner. Customers include Florida State University, airgpu, ELBO, and Creavite.
- H100 SXM — competitive H100 pricing
- A100 SXM and RTX 4090 at competitive marketplace rates
- Pay-per-second billing with no minimum commitment
- 45+ GPU models from consumer to H100
- 100+ global locations across 20+ countries
- No waitlists or quotas — low minimum deposit to start
- Marketplace model — hardware quality varies by host
- No enterprise SLAs or uptime guarantees
- Limited support for complex distributed training
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Key differences
E2E Networks
Indian GPU cloud — H200, H100, A100 with India data residency
TensorDock
H100 SXM, A100 SXM, RTX 4090 — 45 GPU types, 100+ locations