AI has already slipped into the bloodstream of everyday business.
It’s tagging tumours in radiology labs, crunching fraud patterns for banks, powering crop forecasts, and fine-tuning marketing campaigns in Tier 2 cities. But none of this moves without the cloud underneath. The question is — which one’s actually built for the job?
And this is where things get exciting.
India has seen an explosion of AI cloud providers in the past year. Not generic cloud platforms trying to moonlight as AI-ready, but platforms built with AI in their DNA. We’ve compared them all. From hyperlocal heroes to global heavyweights. Pricing, GPUs, flexibility, and what truly sets them apart.
Beyond a chat on options available, it’s also about knowing where your AI ambitions will actually run.
Neysa
Let’s start with the one that’s been built for AI from the ground up. Neysa has become India’s first fully AI-focused cloud platform — launched in 2023 and already powering training, fine-tuning, and deployment for teams that can’t afford to lose time to DevOps chaos.
Why Neysa?
- Built for AI from the ground up — not retrofitted like legacy clouds
- Fractional GPUs to reduce costs on low-to-mid training runs
- Pre-configured MLOps stacks — saves days of setup
- Indian data centres for better compliance and latency
- DevOps-free workflows for faster iteration
- Pricing structured for startups and scaleups — no enterprise lock-in
Sample Pricing
Ideal for early-stage AI startups building LLMs, computer vision apps, or recommender systems. Neysa’s fractional GPU pricing and ready-to-go MLOps environments save devs time and infra cost from day one.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Entry AI | 6 | 42 GB | H100 (10 GB) | ₹40/hr |
| Mid-Tier AI | 16 | 96 GB | L4 (24 GB) | ₹74.8/hr |
| Enterprise AI | 32 | 180 GB | L40S (48 GB) | ₹100/hr |
| Ultimate AI | 48 | 288 GB | H100 SXM (80 GB) | ₹275/hr |
| Next Gen AI | 48 | 288 GB | H200 (141 GB) | ₹200/hr |
Akash Networks
Akash Networks hasn’t followed the crowd. It has disrupted cloud with decentralisation, giving users a peer-to-peer platform that slashes middlemen and costs.
What Stands Out
- Blockchain-based infra
- Fully transparent pricing
- Ideal for Web3 + AI hybrid applications
Plans Snapshot
Works best for decentralised applications like blockchain-based AI, federated learning, or when transparency and no single point of control are must-haves.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Starter | 8 | 64 GB | 1 x A100 | ₹120 |
| Pro | 16 | 128 GB | 2 x H100 | ₹480 |
| Ultra | 32 | 256 GB | 4 x H100 | ₹960 |
Jarvis Labs
Indian-built and AI-focused, Jarvis Labs has become a favourite for those who want granular control — and refuse to waste a second or a rupee more than needed.
What Makes Jarvis Click
- Per-second billing
- Jupyter Notebooks baked in
- Great for solo devs and scaled workloads
Plans
Suits solo researchers or startups with tight budgets running small-to-mid-scale training or inference cycles — especially with frequent spin-up/spin-down compute needs.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Nano | 4 | 32 GB | 1 x A100 | ₹100 |
| Micro | 8 | 64 GB | 1 x H100 | ₹270 |
| Macro | 16 | 128 GB | 2 x H100 | ₹550 |
MilesWeb
MilesWeb started in web hosting but has now pushed into AI cloud, with surprisingly strong offerings.
Why They’ve Made the List
- Dedicated GPU instances
- Fully managed setup
- NVLink support
Pricing
Designed for teams transitioning from traditional hosting to AI — useful for mid-sized enterprises or agencies experimenting with AI model deployment without overhauling their stack.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Nano | 4 | 32 GB | 1 x A100 | ₹100 |
| Micro | 8 | 64 GB | 1 x H100 | ₹270 |
| Macro | 16 | 128 GB | 2 x H100 | ₹550 |
NeevCloud
NeevCloud has quietly positioned itself as the go-to choice for mid to large-scale businesses that want performance without the AWS tax.
The Standouts
- Spot instances + reserved pricing
- Excellent for scientific compute
- NCCL-based multi-GPU scaling
Plans
Great for research labs and engineering teams running scientific simulations, medical imaging models, or high-throughput AI pipelines — especially with multi-GPU training.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Nano | 4 | 32 GB | 1 x A100 | ₹100 |
| Micro | 8 | 64 GB | 1 x H100 | ₹270 |
| Macro | 16 | 128 GB | 2 x H100 | ₹550 |
Ace Cloud
Ace Cloud has steadily grown into a reliable AI cloud choice.
Why Teams Have Chosen It
- Reserved and on-demand pricing
- Pre-installed AI environments
- 24/7 Indian support
Plans Overview
Works for Indian companies needing predictable, locally supported infrastructure for long-term AI deployment — ideal for SaaS tools using embedded AI features.
| Plan | vCPUs | RAM | GPU | Price (₹/hr) |
| Start | 8 | 64 GB | 1 x A100 | ₹130 |
| Grow | 16 | 128 GB | 1 x H100 | ₹300 |
| Scale | 32 | 256 GB | 2 x H100 | ₹620 |
AWS AI
Amazon Web Services has offered the entire AI ecosystem with: Sagemaker, AMIs, EC2, and global reach.
Why It Still Stands Strong
Instance Options
Best for global teams already running workloads on AWS. Works for massive-scale training or deployment in regulated industries that demand enterprise-grade reliability.
| Instance | vCPUs | RAM | GPUs | Price (₹/hr) |
| p4d.24xlarge | 96 | 1.1 TB | 8 x A100 | ₹2,500 |
| p5.48xlarge | 192 | 2.3 TB | 8 x H100 | ₹3,800 |
Google Cloud for AI
Google has combined AI-native tools like Vertex AI and TPUs with scalable cloud infrastructure.
What Works Best
- TPUs for faster training
- Vertex AI for end-to-end MLOps
- Spot pricing savings up to 90%
Plans
Ideal for TensorFlow-first teams, data science platforms, or ML Ops teams using Vertex AI. TPUs suit training transformer-based models fast.
| Instance | vCPUs | RAM | GPU | Price (₹/hr) |
| A2 Mega | 96 | 1.4 TB | 8 x A100 | ₹2,600 |
| A3 Ultra | 192 | 2.5 TB | 8 x H100 | ₹3,900 |
Microsoft Azure AI
Azure has focused squarely on the enterprise market.
Why It Works for Big Teams
- GPT integration via Azure OpenAI
- Azure AI Studio for no-code workflows
- Power BI and Microsoft 365 ecosystem
Instance Specs
Fits large enterprises using Microsoft stack — e.g. building AI into Excel, Power BI, or internal workflows via Azure AI Studio.
| Instance | vCPUs | RAM | GPUs | Price (₹/hr) |
| ND | 96 | 1.5 TB | 8 x A100 | ₹2,700 |
| NH | 192 | 3.0 TB | 8 x H100 | ₹4,000 |
Oracle
Oracle has quietly built a cloud that’s become GPU-competitive.
What’s Surprised Everyone
- Pre-configured AI apps
- Flexible instance configs
- DB and Kubernetes integrations
Plans
Great for teams already using Oracle DB or apps — useful for AI+data warehousing combos and Kubernetes-based AI deployment.
| Plan | vCPUs | RAM | GPUs | Price (₹/hr) |
| GPU Base | 96 | 1.2 TB | 8 x A100 | ₹2,400 |
| GPU Ultra | 192 | 2.4 TB | 8 x H100 | ₹3,700 |
