India’s First Indigenous AI Model: Sarvam’s LLM and the IndiaAI Mission
The Government of India has selected Bengaluru-based Sarvam AI to develop the country’s first indigenous Large Language Model (LLM) under the ₹10,370 crore IndiaAI Mission. This strategic move aims to reduce dependence on foreign AI tools (like OpenAI) and respond to China’s affordable DeepSeek model.
Key Developments
Sarvam is the first startup to be approved under the IndiaAI Mission’s compute access initiative.
Will receive 4,000 Nvidia H100 GPUs for 6 months for model training.
Model variants:
Sarvam-Large: For advanced reasoning and text generation.
Sarvam-Small: For real-time voice interaction.
Sarvam-Edge: For on-device tasks in rural areas.
Sarvam’s Indigenous LLM: Features and Capabilities
Technical Features
Training Data: Curated from Bhashini and Project Vaani for Indian languages.
Accuracy: Outperforms Llama-4 Scout in Hindi JEE Advanced questions.
Deployment: Built on local infrastructure, optimized for population-scale use.
Strategic Advantages
Voice-First Design: Supports 22 Indian languages with WhatsApp/telephone integration.
Security: Closed-source model ensures data sovereignty.
Cost Efficiency: Model training at 5% of Silicon Valley’s cost.
IndiaAI Mission: 7-Pillar Framework
| Pillar | Key Initiative | Budget Allocation |
|---|---|---|
| AI Compute Access | 14,000 GPUs deployed, 10,000 more planned | ₹4,563 crore (44%) |
| AI Kosha | National dataset platform for Indian languages | ₹1,200 crore |
| Startup Financing | Risk capital for 400+ AI startups | ₹2,000 crore |
Objectives:
Democratize GPU access for researchers
Develop AI tools for health/agriculture
Train 1 million AI professionals by 2030
What is an LLM: Relevance for UPSC
What is a Large Language Model?
Definition: An AI system trained on massive text data to understand and generate human language.
UPSC Focus Areas:
Ethics: Reducing bias in models for the Indian context.
Applications: Healthcare, crop prediction.
Security: The need for data localization.
Previous Questions in UPSC
2020 Prelims: Applications of AI in energy/disease diagnosis.
2023 Mains: Role of AI in clinical diagnosis and privacy.
Strategic Importance for India
Competing with Global Models
China’s DeepSeek: Model training at $6 million (1/20th the cost of Western models).
Sarvam’s Edge: Hybrid models for India’s voice-first internet users.
Societal Impact
Education: AI tutors in regional languages.
Governance: Multilingual voice assistants for schemes like MNREGA.
Why This Matters for Your Exam Preparation
UPSC Prelims Focus
Science & Technology: LLM architecture, importance of GPUs.
Polity: Data sovereignty under the DPDP Act.
Mains Answer Writing
GS III: Role of AI in inclusive growth.
Essay: "Ethical AI for India’s Development".
Key Terms to Remember
Parameter Count: 70B in Sarvam-Large, 1.7T in ChatGPT-4.
RLVR Training: Reinforcement Learning with Verifiable Rewards.
FP8 Quantization: Post-training optimization for Indian languages.
Internal Links:
AI in Governance: Previous Analysis
External References:
This initiative positions India as a leader in AI innovation for the Global South and highlights UPSC’s increasing focus on strategic technologies. Aspirants should keep track of AI ethics debates and indigenous R&D milestones for an edge in essay/data-based questions.
