India backs 20 homegrown AI models, approves ₹1.64 lakh crore semiconductor projects to boost tech self-reliance

India is accelerating efforts to build sovereign capabilities across artificial intelligence (AI) and semiconductors, with the Centre supporting 20 indigenous foundation models, approving 237 AI projects with subsidised compute access, and clearing 12 semiconductor manufacturing projects involving a committed investment of ₹1.64 lakh crore, according to the Ministry of Electronics and Information Technology (MeitY).

In a written reply in the Lok Sabha, Minister of State for Electronics and IT Jitin Prasada said the government's AI strategy is guided by Prime Minister Narendra Modi's vision of democratising technology while addressing India-specific challenges and creating economic and employment opportunities. He said the Centre has adopted a calibrated approach under the IndiaAI Mission and the India Semiconductor Mission to reduce dependence on overseas capabilities in semiconductor manufacturing, computing infrastructure, foundational AI models and advanced research.

IndiaAI Mission gathers pace

Approved in March 2024 with a total outlay of ₹10,371.92 crore over five years, the IndiaAI Mission is aimed at building a robust and inclusive AI ecosystem.

Under the programme, the government received 506 proposals for indigenous foundation models, of which 20 proposals—including 12 Large Multimodal Models and eight Small Language Models—have been selected for support, with intellectual property remaining with the applicants.

Among the models already launched are Sarvam AI's 30-billion and 105-billion parameter models and Indus, Gnani.AI's speech-to-speech model, BharatGen's multilingual foundation models (Param2-17B, Patram-7B and Shrutam-2), and Avataar AI's video-generation model.

The government has also empanelled 15 compute service providers across four rounds and approved 237 projects, sanctioning 93.18 lakh GPU hours under subsidised compute support. In addition, a purchase order has been issued for a 1.1 EFLOPS High-Performance AI Compute System at the NIC Data Centre in Shastri Park, Delhi.

To accelerate AI adoption, the Centre has launched 11 national hackathons and innovation challenges, developed 62 AI prototypes, and deployed 20 AI solutions across public-sector institutions. It has also approved 58 AI Centres of Excellence, with 22 centres already operational across 13 states and Union Territories, while 13 projects focused on safe and trusted AI—including bias mitigation, privacy-preserving AI and algorithm auditing—have been selected for support.

Semiconductor push gathers momentum

The government said semiconductors remain critical to sectors ranging from consumer electronics and telecom to defence, industrial manufacturing and automobiles.

Since the launch of the Semicon India Programme in January 2022, the Centre has approved 12 manufacturing projects involving ₹1.64 lakh crore in investments, with three projects already commencing commercial production.

Building on this, the Union Cabinet approved Semicon 2.0 in July 2026 with an outlay of ₹1.27 lakh crore to accelerate chip design, expand fabrication and advanced packaging capacity, and strengthen the broader semiconductor supply chain, including materials, gases and equipment.

Separately, under the National Mission on Interdisciplinary Cyber-Physical Systems, backed by an outlay of ₹3,660 crore, 25 Technology Innovation Hubs have been established to support research, deep-tech innovation, skill development and startup incubation across AI, robotics, quantum technologies, cybersecurity, IoT and fintech.

Prasada also noted that India joined the Pax Silica coalition at the India AI Impact Summit 2026 alongside the US and other partner countries to strengthen global semiconductor supply chains.

Citing the Stanford Global AI Vibrancy Report 2025, the minister said India ranks third globally in AI competitiveness and ecosystem vibrancy and is the second-largest contributor to GitHub AI projects, underscoring the country's growing position in the global AI ecosystem.