IndiaAI Mission Unveils Indigenous Foundation Models EKA-1, Dhīr 2B, and Dhīr 5B with Multilingual and Offline Capabilities Under the Ministry of Electronics and Information Technology's IndiaAI Mission, three homegrown AI foundation models have been launched to support on-device processing and multiple Indian languages. Marking a notable step forward in building domestic technological capabilities, the IndiaAI Mission operating under the Ministry of Electronics and Information Technology (MeitY) officially introduced three homegrown artificial intelligence foundation models on Tuesday. The newly launched models include EKA-1, Dhīr 2B, and Dhīr 5B. The initiative aligns with the national priority of cultivating localized artificial intelligence capacity and reducing reliance on foreign technological frameworks. IT Secretary S Krishnan attended the official launch event alongside senior ministry officials, representatives from IndiaAI, and executive leadership from the developer firms. IndiaAI Mission and Public Compute Infrastructure The creation of these systems was facilitated through the IndiaAI Innovation Centre Foundation Models pillar, a strategic programme dedicated to developing indigenous artificial intelligence and large language models. Officials highlighted that the deployment of subsidized national AI compute resources combined with targeted research support played an instrumental role in bringing the models to completion. The government emphasized that shared public AI infrastructure serves as an essential catalyst for accelerating domestic technological innovation. IT Secretary S Krishnan stated during the proceedings that such indigenous models reinforce India's technological and strategic autonomy in the artificial intelligence sector. He noted that the availability of domestic models creates significant opportunities to enhance productivity and operating efficiency across government administration, industrial sectors, academic research, and formal education. Krishnan also highlighted that platforms like AIKosh are positioned to widen ecosystem access, enabling researchers, university students, technical innovators, and the public to test these models and build specialized applications upon them. Soket Labs Develops EKA-1 for Indian Enterprise Demands Selected under the foundation models pillar, Soket Labs Technology and Research engineered the EKA-1 model specifically tailored to address Indian operational environments. The architecture features 26.3 billion parameters and underwent pre-training utilizing approximately 7.5 trillion tokens. In terms of linguistic range, EKA-1 provides full support for English and all 22 scheduled Indian languages recognized by the Constitution. Soket categorizes the system as an open, sparse hybrid language model optimized for mathematical processing, coding tasks, complex reasoning, and autonomous agentic workflows. A key operational advantage of EKA-1 is its capability to execute inferencing directly on local edge hardware, enabling specific functions to run reliably in the total absence of mobile cellular data or Wi-Fi connections. Soket Chief Executive Officer Abhishek Upperwal stated that the model directly addresses the rigorous functional demands of India's banking, financial services, and cybersecurity industries. Abhishek Upperwal explained that the model aligns with targeted sector needs and mirrors the requirements of India's evolving digital landscape. ZenteiQ Releases Dhīr 2B and 5B for Secure On-Premise Use In parallel, ZenteiQ AiTech Innovations launched Dhīr 2B and Dhīr 5B as open-source foundation models designed to support English alongside 10 Indian languages. Developed as secure, on-premise multilingual digital assistants, both variants focus on document-grounded tasks and offline workflow automation. Their core utility centers on organizational knowledge retrieval, administrative document processing, and facilitating enterprise or citizen service delivery mechanisms. According to official project details, the primary design focus was ensuring dependable performance in low-bandwidth, disconnected, or security-sensitive operational settings, with practical deployments planned across defense agencies, public administrative bodies, industrial enterprises, and academic institutions. ZenteiQ Chief Executive Officer Prof. Sashikumar noted that the models operate effectively on both GPUs and TPUs. Prof. Sashikumar pointed out that their lightweight architecture permits direct installation on smartphones, eliminating the necessity for continuous cloud server connectivity. Local Data Privacy and Broadened Accessibility Government officials noted that running computational workloads directly on local hardware ensures data remains strictly confined to the host device, providing robust guarantees for personal privacy and institutional security. Furthermore, localized offline execution bridges the digital divide for institutions operating in remote geographies with weak telecommunications infrastructure. Linking these releases to wider public digital initiatives, officials reaffirmed that distribution via AIKosh will expand developer adoption across the country. What this means for you This launch equips Indian institutions and ordinary users with privacy-centric, localized AI tools capable of running without constant internet connectivity. • Across India: Sensitive sectors such as defense, public governance, and banking can now deploy advanced intelligence systems on local servers without transmitting data abroad. This significantly elevates institutional data sovereignty and curtails subscription expenses. • For Remote Areas: Users living in regions with unstable or non-existent mobile networks can operate lightweight multilingual models directly on smartphones. This makes essential administrative and educational tools accessible in localized languages regardless of network status. • For Researchers and Students: Access through the AIKosh platform allows domestic innovators to build specialized applications on fully indigenous foundation models. This eliminates reliance on expensive proprietary global APIs for local development. • Multilingual Accessibility: Broad support across scheduled languages allows civic and corporate workflows to handle native documentation seamlessly. Citizen-facing services will become more accessible without requiring English fluency. Why this happened The Indian government sponsored the development of these systems to safeguard technological sovereignty and secure critical institutional data within national borders. • Need for Strategic Autonomy: Global artificial intelligence infrastructure is heavily concentrated among a handful of foreign technology corporations, creating vulnerabilities around digital sovereignty. Developing indigenous foundation models ensures that critical operations remain insulated from overseas disruptions. • Localization and Multilingual Realities: Mainstream global language models primarily optimize for Western datasets and struggle with nuanced Indian languages and administrative workflows. These new architectures are trained directly on Indian tokens to deliver accurate domain reasoning across scheduled languages. • Connectivity Limits and Data Privacy: High-security sectors such as defense and financial services cannot routinely export internal records to foreign cloud servers without risking data breaches. Developing lightweight models capable of running entirely offline on edge hardware directly addresses these security and connectivity bottlenecks. Questions & Answers 1. Which three indigenous foundation models were released by the IndiaAI Mission? The mission unveiled three homegrown models named EKA-1, Dhīr 2B, and Dhīr 5B. 2. Who developed EKA-1 and what are its specifications? EKA-1 was engineered by Soket Labs Technology and Research, featuring 26.3 billion parameters trained on about 7.5 trillion tokens. 3. What makes Dhīr 2B and Dhīr 5B suitable for low-connectivity environments? Developed by ZenteiQ, they are lightweight open-source models that run directly on smartphones without requiring cloud access. 4. How does the AIKosh platform support the broader research ecosystem? AIKosh provides an open distribution channel where students, innovators, and researchers can evaluate and build applications on top of the models. https://trendkia.com/en/money/bharata-ke-gharelu-ai-modala-eka-1-dh-r-2b-aura-dh-r-5b-loncha-22-bharatiya-bhashaon-aura-phalaina-kama-karane-ki-kshamata-55955 TrendKia — Har trend, sabse pehle.