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 GCP if BigQuery, GKE, Vertex AI, analytics and Google-native ML workflows are central to the architecture.
| Feature | NEY Neysa | GCP GCP |
|---|---|---|
| Provider focus | ~ India-built AI cloud platform focused on managed GPU VMs, bare-metal GPUs, managed Kubernetes clusters and AI workload optimization. | ~ Global cloud platform known for BigQuery, Google Kubernetes Engine, Vertex AI, data analytics, AI/ML services and global infrastructure. |
| Starting compute reference | ~ AI cloud focused · Public pricing is GPU and AI-cloud led rather than commodity VPS-led. | ~ ₹1,971/mo · VM Small · E2 custom · 1 vCPU · 1 GB RAM example converted to INR. |
| GPU availability | ~ NVIDIA L4 24 GB on-demand AI Cloud reference converted to INR. | ~ 1× L4 24 GB GPU example converted to INR. |
| H100 pricing visibility | ~ ₹422/hr · NVIDIA H100 SXM 80 GB on-demand AI Cloud reference converted to INR. | ~ ₹1,365/hr · 1× H100 80 GB a3-highgpu-1g example converted to INR. |
| Billing model | ~ Pro-rated billing with on-demand and reserved pricing options; visible dollar prices converted to INR only. | ~ Service and usage-dependent pricing with sustained-use discounts; values converted from GetDeploying examples. |
| Egress / transfer | ✓ Public pricing page states no additional charges for data ingress, egress or inference transactions. | – Free allowance depends on service; 1 TB beyond allowance converted to INR. |
| Data-centre / sovereignty | ~ India-built AI cloud positioning with public, private and hybrid deployment options. | ~ 40+ data centres globally, with India region availability depending on selected service. |
| Support | ~ AI workload, managed infrastructure and Kubernetes-oriented support positioning. | ~ Strong documentation and paid support tiers with deep data/ML ecosystem support. |
| Best fit | ~ AI startups, ML teams and enterprises that need GPU cloud, bare-metal options, managed Kubernetes and AI infrastructure economics. | ~ Data-heavy teams using BigQuery, GKE, Vertex AI, analytics and cloud-native ML services at hyperscaler scale. |
| Data/ML platform | – AI cloud with managed GPUs and Kubernetes for AI workloads | ✓ BigQuery, GKE and Vertex AI are major platform strengths |
| H100 pricing reference | ✓ Lower visible H100 on-demand reference after INR conversion | – H100 example is materially higher in GetDeploying reference |
| Pricing simplicity | ✓ No additional ingress, egress or inference transaction charges in public pricing copy | – Usage-specific hyperscaler pricing with service-dependent discounts |
| Managed Kubernetes | – Managed Kubernetes clusters for AI workloads | ✓ GKE is a mature hyperscaler Kubernetes platform |
✓ 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 | ₹1,971/mo | 1 vCPU · 1 GB RAM · E2 custom |
| VM Medium | ₹8,672/mo | 4 vCPU · 16 GB RAM · E2 custom |
| VM Large | ₹17,303/mo | 8 vCPU · 16 GB RAM · E2 custom |
| NVIDIA H100 | ₹1,365/hr | 1× H100 80 GB |
| NVIDIA A100 | ₹353/hr | 1× A100 40 GB |
| NVIDIA L4 | ₹68/hr | 1× L4 24 GB |
| NVIDIA T4 | ₹75/hr | 1× T4 16 GB |
| Extra egress | ₹11,544/TB | Premium network reference |
Neysa is stronger for AI teams that want GPU-focused infrastructure, lower visible H100 economics and simpler data-movement cost positioning.
GCP wins when BigQuery, GKE, Vertex AI, analytics and Google-native cloud services are non-negotiable requirements.
| Use case | Neysa | GCP |
|---|---|---|
| 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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