As India accelerates its national artificial intelligence ambitions under the IndiaAI Mission, Nvidia is positioning itself at the center of the country’s sovereign AI infrastructure strategy. Once primarily known as a graphics processing unit (GPU) manufacturer, Nvidia has evolved into a full-stack AI computing powerhouse, powering everything from hyperscale data centers and large language models (LLMs) to enterprise AI deployments. India is now emerging as a critical growth market in that global expansion.
With New Delhi prioritizing data sovereignty, domestic AI compute capacity, and homegrown generative AI models, Nvidia is embedding its technology across the entire AI stack in India — spanning GPU infrastructure, AI software platforms, foundational models, and enterprise-grade AI applications. The company’s Blackwell architecture GPUs, AI Enterprise software suite, and Nemotron open models are becoming integral components of India’s sovereign AI ecosystem.
Building Sovereign AI Compute Infrastructure in India
A central pillar of India’s AI policy is reducing reliance on foreign hyperscalers for critical AI workloads. To support this objective, Nvidia is collaborating with domestic cloud and infrastructure providers including Yotta, Larsen & Toubro (L&T), and E2E Networks to establish large-scale sovereign GPU compute capacity within India.
Yotta’s Shakti Cloud is being significantly expanded with over 20,000 Nvidia Blackwell Ultra GPUs, positioning it among the largest AI compute platforms in the country. Meanwhile, E2E Networks is developing a Blackwell-based GPU cluster hosted at L&T’s Vyoma Data Center in Chennai. This deployment will incorporate Nvidia HGX B200 systems, Nvidia AI Enterprise software, and access to Nemotron open-source models, enabling advanced AI training and inference workloads to run entirely within Indian borders.
These initiatives are strategically important for sectors handling sensitive data, including government, defense, financial services, healthcare, and critical infrastructure, where data localization and national security considerations are paramount.
Powering India’s Homegrown Large Language Models (LLMs)
Beyond hardware, Nvidia’s competitive edge increasingly lies in its vertically integrated AI ecosystem. Its stack includes GPUs, AI frameworks such as NeMo and Megatron-LM, curated datasets, reinforcement learning tools, and optimized inference pipelines. This full-stack approach allows developers to scale from foundational infrastructure to production-grade AI applications within a unified platform.
Indian startups and government-backed AI initiatives are actively leveraging Nvidia’s NeMo framework and Nemotron models to build multilingual and domain-specific LLMs tailored to India’s linguistic and enterprise requirements. Sarvam.ai is using NeMo Curator to develop high-quality multilingual datasets while integrating Nemotron resources into its generative AI platform. According to Nvidia, Nemotron models have been pre-trained from scratch across parameter sizes ranging from 3 billion to 100 billion parameters and post-trained using NeMo RL on H100 GPUs through domestic cloud partners.
The government-supported BharatGen consortium has developed a 17-billion-parameter mixture-of-experts model using Nvidia’s pre-training and post-training frameworks. Similarly, AI systems company Chariot is building an 8-billion-parameter real-time text-to-speech model optimized for India’s diverse languages and dialects. Nvidia has also announced the release of Nemotron-3 Nano, with larger Super and Ultra variants expected to follow, further expanding options for scalable and efficient AI model deployment.
Indian IT Services Firms Take Nvidia-Powered AI Global
India’s global IT services leaders are also integrating Nvidia’s AI platforms to deliver enterprise AI transformation solutions worldwide. Companies such as Infosys, Tech Mahindra, Persistent Systems, and Wipro are leveraging Nvidia AI Enterprise to deploy AI agents, automation frameworks, and generative AI solutions across sectors including banking, telecom, pharmaceuticals, healthcare, and manufacturing.
Infosys, for example, has built a 2.5-billion-parameter coding model using the NeMo framework and integrated it into its Topaz AI platform. The model supports advanced code generation, agent-driven workflows, software refactoring, and end-to-end engineering automation, trained on curated code repositories, synthetic datasets, and mathematical reasoning inputs. This underscores India’s growing influence in building and exporting enterprise AI systems at global scale.
Nvidia’s Expanding Role in India’s AI Economy
Nvidia’s deepening engagement across GPU clusters, sovereign cloud infrastructure, generative AI model development, and enterprise AI deployment signals that it is no longer merely a chip supplier in the Indian market. Instead, the company is becoming a foundational technology partner in India’s AI transformation journey. As India pushes to become a global AI hub with strong data sovereignty, domestic compute capacity, and indigenous large language models, Nvidia’s Blackwell GPUs, AI software ecosystem, and enterprise partnerships are positioning it squarely at the heart of the country’s sovereign AI revolution.
