Launch NVIDIA GPU instances in minutes — pre-loaded with PyTorch, TensorFlow and CUDA — and pay only for the hours you run. No procurement cycle, no capex, no waiting on hardware.
From early-stage AI startups to Fortune 500 R&D labs.
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TECHNICAL SPECIFICATIONS
GPU compute provisioned on Nutanix HCI, with the AI stack already configured. Pick a card, pick a region, and your team is training inside the hour.
Accelerated Cloud Infrastructure
Run training, inference, rendering and simulation on GPU infrastructure that scales with the workload instead of the procurement calendar.
Provision dedicated GPU instances within minutes and scale resources as workload requirements evolve without investing in physical hardware.
| Feature | Development & Testing Starter GPU Ideal for AI experiments and development workloads. Get Pricing |
|---|
GPU-POWERED WORKLOADS
Deploy scalable GPU infrastructure for AI, machine learning, rendering, scientific computing, and data-intensive applications.
Every GPU workload runs inside Indian data centres. Full data residency, no cross-border transfer, DPDP Act 2023 aligned
The same class of GPU compute, priced in INR. No forex exposure, no egress bill you didn't model for. One portal, one bill, one support team.
Host360 is an authorised Nutanix Cloud Partner. The same HCI platform that runs core banking and state data centre workloads across India
PyTorch, TensorFlow, CUDA, Jupyter and LLM frameworks ship pre-installed. Most teams lose their first week to environment setup. Here you skip it.
DEPLOYMENT
Provision, configure, and scale GPU resources through a streamlined deployment process.
Six months in, the questions change from "can it handle this?" to "why did we wait?"
Dedicated
GPU Resources
24×7
Technical Support
Elastic
Scaling Options
FREQUENTLY ASKED QUESTIONS
Find answers to common questions about Host360 GPU Cloud Instances, deployment, performance, scalability, and supported workloads.
GPU cloud instances are virtual machines with NVIDIA GPUs attached, rented by the hour for AI training, inference, rendering and scientific computing. You get accelerated compute without buying, racking or maintaining hardware. Host360 provisions them on Nutanix HCI inside Indian data centres.
Host360 offers NVIDIA H100, H200, B200 and Blackwell series GPUs, plus RTX Pro 6000 for rendering and visualisation workloads. Configurations run from a single shared GPU up to 8 GPUs per server with 128 CPU cores and 2 TB RAM.
Minutes. Instances launch pre-configured with PyTorch, TensorFlow, CUDA and Jupyter, so there's no framework installation step. Dedicated bare-metal GPU servers take longer — typically provisioned within hours rather than the weeks a hardware purchase would require.
Host360 GPU compute typically costs 30–40% less than equivalent hyperscaler instances. Pricing is in INR, so there's no forex exposure, and there are no surprise data egress charges. Billing is hourly on-demand, with reserved pricing for sustained workloads.
All GPU workloads and data remain within Indian data centres, with no cross-border transfer. The platform is aligned with DPDP Act 2023 requirements and includes RBAC, encryption at rest and in transit, VPC isolation and full audit logging — which is why it's used for BFSI, healthcare and government workloads.
Yes. GPU instances support Docker and Kubernetes, including managed NKE clusters with auto-scaling node pools. Container-based GPU deployment is standard for teams running inference services in production.
We reply within 2 hrs · IST business hours
Tell us what you're building and we'll size the GPU configuration, share INR pricing, and have you deployed the same week. No procurement cycle required.
Accelerate AI training with dedicated GPUs
Run LLM inference with low latency
Flexible GPU container deployment
Accelerate animation and media rendering
| Maximum Performance Enterprise GPU Designed for mission-critical AI and HPC workloads. Get Pricing |
|---|
| GPU Allocation | Shared GPU | Dedicated GPU | Multi GPU |
| Vcpu Resources | Standard Compute | Dedicated vCPUs | High Core Compute |
| GPU Memory | Standard VRAM | High VRAM | Maximum VRAM |
| Storage |
GENERATIVE AI
Power image, video, and text generation workloads at scale.
On-demand cloud GPU for experimentation, dedicated bare-metal GPU for long training runs, up to 8 GPUs per server with 128 cores and 2 TB RAM.
Cloud engineers who understand AI workloads, backed by a 99.99% uptime SLA. Not a generic helpdesk queue.
| SSD Storage |
| Enterprise NVMe |
| Network | Standard Network | High Speed Network | Premium Networking |
| Scalability | Basic Scaling | Elastic Scaling | Unlimited Scaling |
| Best Use Case | AI Development | AI Production | Enterprise AI & HPC |
“Our compliance team's first question is always where the data sits. Everything staying inside Indian data centres ended that conversation before it started. That alone saved us a quarter of review cycles.”
Aditya Kulkarni
“he stack was already there — CUDA, PyTorch, Jupyter, all configured. My team didn't lose a week to environment setup, which is genuinely what usually happens.”
Sneha Iyer
“We run bursty workloads. Some weeks it's four GPUs, some weeks it's zero. Paying for what we actually used cut our compute spend by roughly a third against what we were paying before.”
Faisal Qureshi
“Support actually understands AI workloads. When a distributed training job was stalling, the engineer on the ticket knew what NCCL was. That's not a given.”