Top 4 E2E Networks Alternatives for GPU and AI/ML Workloads in India (2026)

If you’re evaluating cloud platforms for GPU-based AI/ML training or inference, self-service scaling, and INR pricing without hyperscaler complexity, this comparison is for you. E2E Networks is one well-known option in this space in India, alongside a few others worth knowing about.
In this blog we have compared 4 E2E Networks alternatives you should explore before deciding on which cloud platform you want to go with.

What should a GPU cloud platform in India offer?

A GPU cloud platform in India should at least offer INR pricing, INR pricing, an India datacentre, a real choice of GPU models, and self-service scaling you can start without a sales call.

• INR pricing. Removes exchange-rate exposure on what’s often a large, recurring compute bill.
• India datacentre. Lower latency for India-based users, and relevant for DPDP data residency requirements.
• GPU model variety. Training, fine-tuning, and inference workloads need different GPU classes, from entry-level cards to H100/H200-class hardware.
• Self-service scaling. The ability to spin up or down without a procurement cycle, especially useful for experimentation-heavy AI teams.

Quick comparison table

Below we have a quick comparison between 5 entry-tier GPU pricing below uses each provider’s own lowest-published GPU model, which differs by card across providers, so treat this as a starting-point comparison, not an identical spec match.

*Hourly rates converted to a monthly estimate at ~720 hours and current exchange rates, for comparison only. Confirm live pricing before purchasing, GPU rates move with availability.
**Cyfuture’s specific entry-tier GPU rate isn’t published, and needs a direct quote from Cyfuture.

Let’s take a look at each of these cloud platforms, individually for better clarity. Starting with E2E Networks.

E2E Networks

E2E Networks is one of India’s most established GPU cloud providers, and it’s the right call for teams doing serious deep learning or GenAI work.

• India data centres: Delhi NCR, Mumbai, and Bengaluru.
• GPU catalogue: H200, H100, A100, L40S, L4, and A30, among the widest ranges available from an India-native provider.
• Pricing: Publicly listed rates include H100 from $1.80/hr, H200 from $2.20/hr, and B200 from $4.90/hr, with lower-tier cards like L4 available from roughly ₹50–70/hour.
• Billing: INR, with UPI, NEFT, credit cards, and direct debit all supported, plus GST-compliant invoicing.
• Extras: TIR, E2E’s own Jupyter-based managed ML platform, is a genuine convenience for data science teams who want a managed notebook environment without extra setup. E2E is also NSE-listed, which is a meaningful trust signal for enterprise procurement.
• Best for: Teams running deep learning training, fine-tuning, or GenAI inference at meaningful scale, and teams that specifically want a managed ML workflow layer on top of raw GPU access.

CloudPe

CloudPe is an Indian cloud platform built on OpenStack, built by Leapswitch Networks and winner of CIO Choice’s Best Public Cloud award for 2026. CloudPe is particularly for teams that want general-purpose cloud and GPU access on the same platform, rather than a GPU-only specialist.

• India data centres: Mumbai, Pune, Delhi, and Bengaluru.
• Pricing: GPU instances start at ₹14,500/month (NVIDIA RTX A5000), scaling up to NVIDIA H200 for larger workloads. General-purpose VMs start separately at ₹930/month.
• Performance: Independently benchmarked at 33% faster than AWS and 45% faster than Azure on comparable CPU instances.
• Billing: INR native, no underlying USD conversion.
• Where it’s a lighter fit: CloudPe’s GPU catalogue is narrower than dedicated GPU specialists like E2E Networks or NeevCloud, who carry a wider spread from entry-level cards through H200 and beyond. If your workload needs a specific high-end GPU model CloudPe doesn’t carry, check availability first.

AceCloud

AceCloud is a GPU cloud provider recognized as a Gartner Trusted Cloud Partner, known for a wide GPU catalogue and flat monthly pricing rather than hourly billing. AceCloud is especially for teams that prefer flat monthly pricing over hourly billing.

• India data centres: Noida and Mumbai.
• GPU catalogue: A100, H100, H200, L40S, L4, A30, A2, RTX Pro 6000, RTX A6000, and RTX 8000, a genuinely wide spread.
• Pricing: A100 (24GB) instances list at roughly ₹35,000/month, with a Gartner-recognized 99.99% uptime SLA.
• Billing: INR with full GST invoicing.
• Best for: Teams that want predictable flat monthly GPU costs rather than usage-based hourly billing, and teams already comparing multiple GPU models side by side before committing.

Cyfuture Cloud

Cyfuture Cloud is a Tier IV certified, MeitY-empanelled Indian cloud provider that offers GPU compute as part of a broader managed-services stack, not as a standalone product. It is particularly for enterprises that want GPU compute alongside a broader managed-services stack in the same platform.

• India data centres: Jaipur, Noida, and Bangalore, each with full data processing agreements for DPDP compliance.
• Platform depth: Fine-tuning, AI inferencing, serverless inference, GPU clusters, S3-compatible object storage, and vector databases are all available within the same environment, co-located to avoid inter-service data transfer costs.
• Certifications: Tier IV certified, MeitY-empanelled, which matters for government and regulated-sector procurement.
• Pricing: Specific GPU rates weren’t published in the sources checked for this piece. Get a direct quote before including firm numbers.
• Best for: Indian enterprises, BFSI, healthcare, and government AI projects where India data residency is a hard requirement and a single integrated platform (not just raw GPU rental) is the priority.

NeevCloud

NeevCloud positions itself as “India’s first AI Supercloud,” backed by one of the broadest GPU model ranges covered here, priced on a pay-as-you-go hourly basis. It is particularly for budget-conscious teams that want the widest possible GPU selection.

• India data centres: Indore and Mumbai.
• GPU catalogue: One of the broadest available, spanning RTX 3090 through A100, H100, H200, and B200/B300.
• Pricing: Entry-level cards like the RTX 3090 start around $0.54/hour, with H200 available from roughly $1.99–2.39/hour depending on offer. Note that pricing is quoted in USD per hour rather than INR, with 18% GST applied separately, worth checking against providers with native INR billing if currency predictability matters to you.
• Storage: S3-compatible object storage through a Zata.ai partnership, with no egress fees within region.
• Best for: Teams that want the broadest GPU model selection and are comfortable with USD-denominated hourly pricing.

How do you choose between these cloud platforms?

To make the right decision the simplest way is to avoid looking at the brand name and match the platform to your workload type first, then to your billing preference.

• Training large models or running GenAI at scale?
  E2E Networks or NeevCloud’s wider high-end GPU catalogues are built for this.
• Need GPU and general-purpose compute in one place?
  CloudPe combines both under a single platform.
• Want flat, predictable monthly billing instead of hourly rates?
  AceCloud and CloudPe both price this way; E2E and NeevCloud are primarily hourly.
• Working in a regulated industry needing a fuller managed-services stack?
  Cyfuture Cloud’s integrated platform is built with that in mind.
• Does currency predictability matter to you?
  CloudPe, E2E Networks, and AceCloud all bill natively in INR. NeevCloud’s GPU rates are USD-denominated.