NVIDIA A30 Price in India AI and Data Center GPU Cost Analysis

Are you looking for a reliable GPU solution to handle AI, ML, and data center workloads? The NVIDIA A30 GPU stands out as a cost-effective powerhouse designed specifically for enterprises, research institutions, and cloud computing providers. Built on NVIDIA’s Ampere architecture, it delivers high efficiency, superior AI inference capabilities, and multi-instance GPU technology all at a relatively affordable price point compared to the A100 and H100 models.

In this article, we’ll explore the NVIDIA A30 price in India, its features, performance metrics, and how it fits into modern AI and data center infrastructures. Whether you’re setting up a private cloud, upgrading enterprise systems, or running advanced neural network models, this guide will help you make an informed investment.

Overview of the NVIDIA A30 GPU

The NVIDIA A30 is a data center GPU built for enterprise-level performance. It’s designed to balance efficiency, performance, and scalability across multiple workloads, including AI inference, deep learning, HPC (High-Performance Computing), and data analytics.

Unlike gaming-oriented GPUs, the A30 is optimized for sustained performance in multi-tenant and virtualized environments. It also supports NVIDIA Multi-Instance GPU (MIG) technology, which allows a single GPU to be divided into multiple instances, maximizing utilization across virtual machines.

NVIDIA A30 Price in India (2025 Update)

As of 2025, the NVIDIA A30 GPU price in India ranges between ₹3,50,000 and ₹5,00,000, depending on the configuration, supplier, and warranty coverage.

While the A30 may seem expensive upfront, its ability to handle multiple workloads simultaneously makes it highly cost-efficient in the long run.

Key Specifications of NVIDIA A30

GPU Architecture: NVIDIA Ampere

Memory: 24GB HBM2

Memory Bandwidth: 933 GB/s

CUDA Cores: 10752

Tensor Cores: 336 (3rd Gen)

NVLink Support: Yes (600 GB/s bi-directional)

TDP: 165W

Form Factor: PCIe 4.0

Virtualization Support: NVIDIA vGPU & MIG

ECC Memory: Supported

These specifications make the A30 an efficient and balanced performer for AI inference, machine learning, and HPC clusters.

Performance Overview

The NVIDIA A30 delivers outstanding computational performance across diverse workloads. It offers high throughput for mixed-precision AI tasks and exceptional energy efficiency, making it a practical choice for large-scale data centers.

AI and ML Performance Benchmarks (approximate):

INT8 Inference: Up to 330 TOPS

FP16 Training: Up to 20 TFLOPS

FP64 Performance: 4 TFLOPS

Energy Efficiency: ~25% more efficient than A100 under sustained load

The A30 is particularly popular for AI inference, data processing, and virtual desktop infrastructure (VDI) deployments.

NVIDIA A30 vs A100: Price and Performance Comparison

While the A100 dominates in raw compute power, the A30 offers superior efficiency per watt, making it ideal for inference workloads and scalable enterprise applications.

Use Cases of the NVIDIA A30 GPU

1. AI Inference at Scale

The A30 accelerates inference workloads for models like NLP, vision recognition, and real-time recommendation systems.

2. Cloud Computing

With its MIG support, cloud hosting providers can host multiple virtual GPUs on a single A30, maximizing performance per node.

3. Data Analytics and Big Data

The A30 handles parallel data processing efficiently, making it a great fit for analytics pipelines and AI-driven insights.

4. Virtual Desktop Infrastructure (VDI)

The A30 enables seamless virtual workstation experiences for designers, developers, and engineers using 3D or GPU-intensive tools.

5. Enterprise AI and HPC

From autonomous systems to deep learning training, the A30 powers a wide range of enterprise-level workloads.

Why NVIDIA A30 Is a Smart Investment

The A30’s combination of price, power efficiency, and scalability makes it one of the most attractive GPUs for Indian enterprises transitioning to AI-powered operations.

Its low power consumption (165W) significantly reduces operational costs while maintaining high processing power — a key factor for data centers that aim to optimize energy efficiency.

Cloud GPU Alternative – Cyfuture Cloud

If purchasing a GPU like the A30 feels expensive, cloud GPU hosting is a practical alternative. Providers like Cyfuture Cloud offer A30, A100 GPU, and H100 GPU instances on flexible rental or subscription models.

Benefits of choosing Cyfuture Cloud:

- Pay-per-use pricing with no hardware investment

- Access to high-performance NVIDIA GPUs

- Local Indian data centers for low-latency AI training

- Transparent pricing and flexible billing options

- Round-the-clock expert support for configuration and optimization

This model is ideal for startups, researchers, and businesses that need GPU power without owning the infrastructure.

Conclusion

The NVIDIA A30 GPU bridges the gap between affordability and high-performance computing, making it one of the best choices for enterprises seeking AI, ML, and data center efficiency in 2025.

With a price range of ₹3.5–₹5 lakh, it offers immense value through scalability, MIG technology, and outstanding inference capabilities. Whether you’re running large-scale analytics, machine learning models, or virtualization environments, the A30 stands out as a dependable and energy-efficient solution.

For businesses that prefer flexibility and lower capital expenditure, Cyfuture Cloud provides cost-effective A30 GPU hosting solutions in India with transparent pricing and robust infrastructure support. It’s the perfect way to harness enterprise-grade GPU power — on your terms.