E2E Networks

E2E Networks GPU pricing overview

E2E Networks is a specialist GPU cloud provider headquartered in New Delhi, India. 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. Billing is On-demand with a minimum commitment of None. Available regions include IN. GPU instances can be provisioned on-demand, making E2E Networks suitable for both short-duration experiments and sustained production workloads.

E2E Networks vs other GPU providers

E2E Networks competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: India data residency — data stays in India; H200 and H100 availability; NSE-listed — established Indian cloud provider. Use the side-by-side comparison tool above to see E2E Networks pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 5 E2E Networks listings alongside 91+ providers in a single sortable view.

Best use cases for E2E Networks

E2E Networks is best suited for: Indian AI teams with data residency requirements, South Asian enterprises needing local data storage, Cost-sensitive Indian ML workloads, Teams needing low-latency GPU access within India. Support tiers range from Standard → Enterprise, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 5 active GPU listings on E2E Networks, covering H200 141GB, H100 80GB, A100 80GB, A100 40GB and more. H100 SXM5 instances with NVLink interconnect are commonly used for large-scale training workloads. A100 40GB and RTX 4090 instances are frequently used for fine-tuning and inference of smaller models.

E2E Networks billing model and cost structure

E2E Networks uses On-demand pricing. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing may be available for predictable long-running workloads — check the provider's pricing page for current committed-use rates. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.

Choosing the right GPU on E2E Networks

GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — high HBM3 bandwidth and FP16 throughput make them well-suited for large transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB is a common choice on many providers. RTX 4090 instances are widely used for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.

How E2E Networks pricing data is collected

Prices shown are sourced from E2E Networks's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in USD per hour. Daily snapshots are kept in our history archive and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.

Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and many other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.