India’s own GPU could arrive in 3-5 years, 18,000 AI servers to go live soon says Ashwini Vaishnaw

India is gearing up to make a significant breakthrough in high-end computing by developing its own Graphics Processing Unit (GPU) within the next three to five years, while also working on an indigenous foundational Artificial Intelligence (AI) platform expected to be ready in just 10 months. Union Minister for Electronics and Information Technology Ashwini Vaishnaw made these announcements during the Budget Roundtable 2025, organized by India Today and Business Today.
In a major step towards AI development, the government will roll out 18,000 high-end GPU-based computing facilities in the coming days, making advanced computing power accessible to researchers, startups, and academic institutions. This move is crucial for reducing India's reliance on foreign chip manufacturers, particularly Nvidia, which currently dominates over 80% of the global GPU market.
With AI becoming a critical driver of global innovation, India’s efforts to develop self-sufficient semiconductor and AI ecosystems mark a pivotal shift. This article explores India’s GPU development strategy, AI advancements, computing infrastructure expansion, and the broader impact of these initiatives on the country’s technological future.

Developing an advanced, high-performance GPU requires cutting-edge research, skilled engineering, and robust semiconductor manufacturing capabilities. According to Vaishnaw, India is considering multiple approaches to achieve this goal, including leveraging open-source GPU architectures, acquiring licensed chip designs, and innovating its own GPU technology from the ground up.
Instead of designing a GPU entirely from scratch, India plans to build upon existing architectures—an approach widely followed worldwide. This strategic pathway enables faster development while reducing the technical and financial barriers that come with semiconductor manufacturing. If executed successfully, India could significantly reduce its dependency on foreign semiconductor companies, strengthening its position in the global high-performance computing industry.

GPUs were initially designed for graphics rendering and multimedia processing but have now become indispensable for AI and machine learning applications. Unlike traditional Central Processing Units (CPUs), which handle sequential processing tasks, GPUs excel in parallel processing, making them ideal for training AI models, deep learning algorithms, and big data analytics.
With AI-driven industries growing at an unprecedented pace, having a domestic GPU manufacturing ecosystem will give India a competitive edge in areas such as autonomous systems, scientific simulations, cybersecurity, and advanced analytics. By investing in indigenous GPU technology, India is preparing itself for the next era of digital innovation.

In addition to hardware advancements, India is also working on its first AI foundational model, which is expected to be ready within 10 months. This initiative aims to enhance India’s AI capabilities across various sectors, including healthcare, education, governance, and defense. Unlike proprietary AI models developed by global tech giants like OpenAI (ChatGPT) and Google (Gemini), India’s AI platform will be tailored to local needs, linguistic diversity, and regional data privacy requirements.
Vaishnaw noted that India has already witnessed success in small-scale AI deployments. For instance, Indian Railways improved its ticket confirmation rate by 27% using AI-driven predictive models. By expanding such AI applications, the government aims to foster innovation, increase efficiency, and create new opportunities for economic growth.
Indian startups, researchers, and universities are actively studying international AI research papers to refine their models. Vaishnaw highlighted that Chinese AI company DeepSeek optimized AI training by leveraging mathematical research from as early as 2003 and 2005. Similarly, Indian researchers are analyzing open-source AI frameworks to build a cost-effective and efficient AI model that aligns with India's technological and economic priorities.

Recognizing the high computational demands of AI research, the Indian government is rolling out 18,000 high-end GPUs for AI development. These GPUs will be accessible to startups, academic institutions, and enterprises, allowing them to conduct AI model training and large-scale data analysis.
Vaishnaw confirmed that 10,000 GPUs are already available, with the remaining 8,000 set to be deployed within days. This initiative is crucial for ensuring that Indian developers and researchers have the necessary computational power to compete with global tech leaders. By providing affordable access to AI infrastructure, the government aims to create a level playing field for innovation.

The government’s Make in India program has played a key role in boosting domestic electronics manufacturing, particularly in smartphone production. Over the past few years, India has transformed into a global hub for mobile phone assembly and component production, reducing import dependency.
According to Vaishnaw, the mobile manufacturing industry has created 12 lakh (1.2 million) jobs, with India now producing essential smartphone components, including:


Despite progress in electronics manufacturing, semiconductor production remains a major challenge. Vaishnaw acknowledged that India lost four decades (1950–1990) due to the License Raj, which restricted manufacturing growth. However, recent initiatives like the Semiconductor Mission, global partnerships with chip manufacturers (such as TSMC and Intel), and government incentives for fabless semiconductor startups are laying the foundation for India’s long-term semiconductor ambitions.
By focusing on indigenous chip design, manufacturing capabilities, and R&D investment, India aims to reduce dependence on imported semiconductor technology and become a key player in the global semiconductor supply chain.
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