India's indigenous GPUs ready for demonstration by 2025
July 10, 2025
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Home Bharat

India’s Technological Leap: Indigenous GPUs ready for demonstration by 2025, production by 2029

India is set to showcase its first homegrown GPUs by the end of 2025 as part of the ₹10,372 crore IndiaAI Mission, with large-scale production planned to begin by 2029. The initiative aims to boost AI capabilities, reduce import dependence, and strengthen India's position in the global tech ecosystem

by WEB DESK
May 17, 2025, 09:00 pm IST
in Bharat, Technology
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Representative image

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India is preparing to unveil its first Made-in-India Graphics Processing Units (GPUs) by the end of 2025, marking a significant step toward technological self-reliance in the era of artificial intelligence (AI) and high-performance computing. Government sources recently confirmed that these indigenously developed GPUs will be ready for technology demonstrations within the next year, showcasing their capabilities in advanced computational tasks far beyond traditional graphics rendering. The Centre for Development of Advanced Computing (C-DAC), an autonomous institution under the Ministry of Electronics and Information Technology, has been assigned the responsibility of developing the indigenous GPU.

According to current plans, technology demonstration of these GPUs will begin by late 2025, giving researchers and developers a chance to test their potential in real-world use cases. However, full-scale production and deployment of these Indian-designed chips is expected to happen by 2029. These tasks include artificial intelligence (AI), machine learning (ML), scientific simulations, and complex mathematical operations. This initiative forms a key component of India’s larger strategy to establish itself as a leading center for advanced digital infrastructure through the IndiaAI Mission, which is backed by a budget of Rs 10,372 crore (around US$ 1.21 billion).

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The mission is being led by the Ministry of Electronics and Information Technology (MeitY) with strong backing from the Union Minister for Electronics and IT, Mr. Ashwini Vaishnaw, who confirmed that indigenous chipsets are expected to be fully developed and production-ready within the next three to four years.

This timeline aligns with India’s long-term vision of becoming self-reliant in semiconductor technologies, an ambition further reinforced by global supply chain disruptions during the COVID-19 pandemic and the rising demand for compute-intensive technologies like AI, ML, and data analytics. The Indian government is not taking this journey alone. It plans to engage with global chip makers later in 2025 to accelerate development and gain access to the latest design tools and fabrication technologies. Strategic collaborations with international semiconductor firms will help India leapfrog some of the technological barriers and ensure that its indigenous GPUs remain globally competitive.

As part of its AI infrastructure roadmap, the government initiated a competitive bidding process to acquire high-performance GPUs from established players. In the first round of bidding, 10 companies were empanelled to supply 18,693 GPUs, including top-of-the-line models such as Nvidia H100 and H200, as well as AMD’s MI325 and MI300X. Leading Indian technology companies such as Jio Platforms, Tata Communications, and Yotta Data Services played a significant role as major participants, highlighting the private sector’s keen involvement in expanding India’s AI computing capabilities.

A cost analysis showed encouraging figures for Indian organizations and startups, with the average hourly rate for GPU compute units estimated at around Rs 115.85 (approximately US$ 1.36) for entry-level GPUs and Rs 150 (about US$ 1.76) for high-performance models. This is significantly lower than the global benchmark of Rs 213.44 to Rs 256.12 (US $ 2.5 to 3) per hour, positioning India as one of the most cost-effective destinations for AI computing resources.

To foster innovation and ensure accessibility, the government has proposed a 40% discount on GPU usage rates for startups, academic institutions, and students. Further concessions will be provided to users who commit to long-term engagements, defined as six months or more. This initiative is aimed at encouraging consistent usage and strengthening AI research capabilities across the country, particularly in Tier-2 and

The interest generated by the first round of bidding has led to global players expressing willingness to supply an additional 15,000-18,000 GPUs in the upcoming second phase. Recognizing the growing demand, the government has now shifted to a quarterly empanelment process to allow more firms to participate and keep up with the dynamic requirements of India’s AI ecosystem.

One of the challenges facing India is a 50,000 GPU limit imposed by the United States government, which regulates the export of advanced computing equipment. As India edges closer to this threshold, bilateral trade negotiations with the US are underway to ease or revise this cap.

Given India’s strategic importance as a growing digital economy and its alignment with Western tech standards, these talks are expected to yield positive outcomes. The resolution of this issue will be crucial in sustaining India’s AI infrastructure growth without bottlenecks.

Developing homegrown GPUs is not just a technological achievement, it is a geopolitical and economic milestone. As countries like China, the United States, and members of the European Union continue to advance rapidly in this field, India’s entry into indigenous GPU production is both timely and essential. It brings multiple strategic benefits, including reduced dependency on foreign hardware, enhanced data sovereignty, and improved national security. The initiative is also expected to boost domestic semiconductor talent and research and development, while strengthening India’s position in the global AI supply chain. Moreover, this move aligns with the Atmanirbhar Bharat (Self-Reliant India) vision and opens up opportunities for India to become a future exporter of AI computing power.

Topics: Atmanirbhar BharatGraphics Processing UnitsGPU
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