Blackwell-class compute for foundation-model training, high-throughput inference, and HPC — with 192GB HBM3e per GPU, INR billing, and no hyperscaler lock-in. Provision in minutes, not procurement cycles.
From early-stage AI startups to Fortune 500 R&D labs.
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MODEL SPECIFICATIONS
The NVIDIA B200 is the flagship GPU of NVIDIA's Blackwell generation — a dual-die accelerator with 208 billion transistors, 192GB of HBM3e memory, and native FP4 support. It delivers roughly 4× the AI training throughput of the H100 and up to 15× faster real-time LLM inference, making it purpose-built for trillion-parameter models, production inference, and large-scale scientific computing.
* Accelerates HPC, simulation, and scientific research * Powers generative AI, rendering, and visualization pipelines * Runs the full CUDA and NVIDIA AI Enterprise software stack * Scales across multi-GPU clusters over NVLink 5 (1.8 TB/s) * Serves high-throughput, low-latency inference with native FP4 * Provides infrastructure for enterprise AI deployments.
Train foundation AI models.
Deploy AI applications at scale.
Accelerate simulation workloads.
Support visual computing tasks.
DEPLOYMENT
Deploy enterprise GPU infrastructure through a structured provisioning and onboarding process.
Align NVIDIA B200 infrastructure with your AI, HPC, and production workload requirements.
| Feature | AI Training ₹160 / hr | AI Inference ₹78,000 / month | HPC & Research Custom — contact sales |
|---|---|---|---|
| Typical Users | ML Engineers | AI Product Teams | Research Teams |
| Common Workloads | Foundation Models | AI Applications | Simulations |
| Processing Pattern | Long-Running Jobs | Request Processing | Batch Computing |
| Resource Focus | Model Training | Response Generation | Compute Tasks |
| Data Usage | Training Datasets | Production Data | Research Data |
| Environment Type | Development Platforms | Production Systems | Research Clusters |
| Deployment Type | — | — | — |
Every B200 workload runs inside Indian Tier III data centres, data residency for BFSI, healthcare & gov.
INR-denominated pricing versus AWS, Azure, and GCP. No forex risk, no egress traps.
PyTorch, TensorFlow, CUDA, and Jupyter ready on launch. No setup overhead.
On-demand cloud for burst workloads or dedicated bare-metal for sustained training - same portal.
Backed by 100G networking and a named SRE, not a generic helpdesk queue.
DPDP Act 2023 aligned, CERT-In auditor on file, RBI-ready audit trails.
AI INFRASTRUCTURE RESOURCES
Discover complementary infrastructure and services for AI, HPC, and accelerated computing environments.
GPU INFRASTRUCTURE
GPU compute for training and inference workloads.
STORAGE
Fast data access for AI pipelines and large datasets.
NETWORKING
Dedicated internal connectivity between GPU, storage, and apps.
SECURITY
Network policies protecting GPU workloads and cloud resources.
AI OPERATIONS
Model development, deployment, and lifecycle management.
ARCHITECTURE
Design scalable distributed training and inference clusters.
Production feedback from teams running NVIDIA B200 capacity in Indian data centres.
200+
Indian operators
99.99%
Monthly uptime
24/7
Named SRE
Frequently asked
Learn how private networks enable secure communication between cloud resources and infrastructure.
The NVIDIA B200 is a Blackwell-generation data center GPU with 192GB of HBM3e memory, up to 8 TB/s bandwidth, and native FP4 support. It's built for large-scale AI training, high-throughput inference, and HPC.
For most AI workloads, yes. NVIDIA reports roughly 4× faster training and up to 15× faster real-time LLM inference versus H100, driven by native FP4 and the 2nd-gen Transformer Engine.
Yes. Organizations use NVIDIA B200 infrastructure to build, train, deploy, and operate production AI applications.
Yes. NVIDIA B200 is designed for modern AI workloads, including large language models and generative AI applications.
Yes. NVIDIA B200 supports deployment within larger GPU infrastructure environments for distributed computing workloads.
Technology companies, research institutions, enterprises, healthcare organizations, financial services firms, and engineering teams commonly deploy advanced GPU infrastructure.
We reply within 2 hrs · IST business hours
Tell us what you're rendering, simulating or serving, and we'll come back with a GPU count, an instance shape and a price — not a brochure. If a different GPU is the better fit, we'll tell you that instead.