Choose Neysa if your workload is AI-first and you need GPU VMs, bare-metal GPU options, managed Kubernetes clusters and predictable AI cloud economics.
Choose AWS if service breadth, global regions, managed AI/data services and enterprise ecosystem depth outweigh AI-cloud simplicity and predictable unit economics.
| Feature | NEY Neysa | AWS AWS |
|---|---|---|
| Provider focus | ~ India-built AI cloud platform focused on managed GPU VMs, bare-metal GPUs, managed Kubernetes clusters and AI workload optimization. | ~ Global hyperscaler with EC2, EKS, S3, RDS, SageMaker, Bedrock, analytics, security and one of the broadest managed-service portfolios. |
| Starting compute reference | ~ AI cloud focused · Public pricing is GPU and AI-cloud led rather than commodity VPS-led. | ~ ₹721/mo · VM Small · t3.micro · 2 vCPU · 1 GiB RAM example converted to INR. |
| GPU availability | ~ NVIDIA L4 24 GB on-demand AI Cloud reference converted to INR. | ~ Radeon Pro V520 GPU example converted to INR; NVIDIA options also listed. |
| H100 pricing visibility | ~ ₹422/hr · NVIDIA H100 SXM 80 GB on-demand AI Cloud reference converted to INR. | ~ ₹662/hr · 1× H100 80 GB p5.4xlarge example converted to INR. |
| Billing model | ~ Pro-rated billing with on-demand and reserved pricing options; visible dollar prices converted to INR only. | ~ Complex on-demand, reserved, savings plan and multi-service billing; values converted from GetDeploying examples. |
| Egress / transfer | ✓ Public pricing page states no additional charges for data ingress, egress or inference transactions. | – 100 GB free egress allowance; 1 TB beyond allowance converted to INR. |
| Data-centre / sovereignty | ~ India-built AI cloud positioning with public, private and hybrid deployment options. | ~ 30+ data-centre locations with India regions listed in Mumbai and Hyderabad on GetDeploying. |
| Support | ~ AI workload, managed infrastructure and Kubernetes-oriented support positioning. | ~ Extensive docs and enterprise support tiers; advanced support is typically paid. |
| Best fit | ~ AI startups, ML teams and enterprises that need GPU cloud, bare-metal options, managed Kubernetes and AI infrastructure economics. | ~ Enterprises that need service breadth, global regions, managed AI/data services, mature enterprise controls and hyperscaler procurement patterns. |
| Service breadth | – Focused AI cloud stack for GPU and Kubernetes workloads | ✓ Extensive hyperscaler catalogue across compute, storage, AI, analytics and security |
| GPU economics | ✓ Lower visible H100 on-demand reference than AWS after INR conversion | – H100 reference is significantly higher in GetDeploying example |
| Pricing simplicity | ✓ AI cloud pricing with no extra ingress, egress or inference transaction charges | – Broad but complex pricing across services, regions and commitments |
| Enterprise ecosystem | – AI cloud and managed GPU platform | ✓ Mature enterprise controls, regions, marketplace and procurement ecosystem |
✓ Winner in this category · ~ Partial / context-dependent · highlighted rows = clearer advantage
| NVIDIA L4 | ₹113/hr | 24 GB GPU · on-demand AI Cloud |
| NVIDIA L40S | ₹188/hr | 48 GB GPU · on-demand AI Cloud |
| NVIDIA H100 SXM | ₹422/hr | 80 GB GPU · on-demand AI Cloud |
| NVIDIA H100 NVL | ₹422/hr | 94 GB GPU · on-demand AI Cloud |
| NVIDIA H200 SXM | ₹455/hr | 141 GB GPU · on-demand AI Cloud |
| L4 reserved monthly | ₹41,209/mo | 36-month reserved reference |
| H100 reserved monthly | ₹171,232/mo | 36-month reserved reference |
| VKE Master Node | ₹10,903/mo | Non-HA monthly reference |
| VM Small | ₹721/mo | 2 vCPU · 1 GiB RAM · t3.micro |
| VM Medium | ₹11,525/mo | 4 vCPU · 16 GiB RAM · t3.xlarge |
| VM Large | ₹23,877/mo | 8 vCPU · 16 GiB RAM · c5.2xlarge |
| NVIDIA H100 | ₹662/hr | 1× H100 80 GB |
| NVIDIA L40S | ₹179/hr | 1× L40S 48 GB |
| NVIDIA L4 | ₹221/hr | 1× L4 24 GB |
| NVIDIA T4 | ₹51/hr | 1× T4 16 GB |
| Extra egress | ₹8,658/TB | Beyond free allowance |
Neysa is stronger when AI teams want focused GPU infrastructure, simpler AI-cloud economics and fewer add-on charges for data movement or inference transactions.
AWS wins when the buyer needs the deepest managed-service catalogue, global architecture options, enterprise governance and hyperscaler procurement maturity.
| Use case | Neysa | AWS |
|---|---|---|
| Focused AI GPU economics | ★★★ | ★★☆ |
| Enterprise managed-service breadth | ★★☆ | ★★★ |
| Global region footprint | ★★☆ | ★★★ |
| Pricing simplicity for AI workloads | ★★★ | ★☆☆ |
| Data/egress predictability | ★★★ | ★☆☆ |
| Hyperscaler ecosystem depth | ★☆☆ | ★★★ |
| India-built AI cloud positioning | ★★★ | ★☆☆ |
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