The EU and India are forging a strategic partnership on artificial intelligence that sidesteps the US-China race for cutting-edge frontier models, instead focusing on practical, affordable AI systems that most countries actually need. This emerging collaboration represents a fundamentally different approach to AI development, one centered on applied systems like multilingual tools, industrial AI, and AI safety rather than building the largest language models (LLMs, or AI systems trained on vast amounts of text data).

Why Is the EU-India AI Partnership Different from the US-China Competition?

The EU-India AI cooperation is not a belated attempt to compete in the frontier-model race dominated by the United States and China. Instead, both regions are focused on developing trusted, affordable, multilingual, and sector-specific AI systems for practical deployment across public services, healthcare, industry, energy, agriculture, and disaster management. This distinction matters because only a handful of countries will ever develop frontier models, while most nations need to implement AI across their economies and institutions.

In June 2026, more than 100 European and Indian technology companies gathered in New Delhi for the first EU-India Tech Business Forum, signaling growing momentum on both sides. The meeting covered artificial intelligence, semiconductors, cybersecurity, data governance, and digital public infrastructure. This forum was preceded by the second EU-India Trade and Technology Council meeting in February 2025, where both parties agreed to enhance cooperation between the European AI Office and the IndiaAI Mission across large language models, AI for human development, responsible AI, semiconductors, and high-performance computing.

What Computing Infrastructure Is India Building for AI Development?

India's AI strategy follows a dual-track approach. On one side, Indian firms and public institutions adopt leading global AI models, including American and open-source Chinese systems wherever appropriate. Simultaneously, New Delhi is developing domestic capabilities through the IndiaAI Mission, which integrates public-private computing resources and develops indigenous large, multimodal, and domain-specific models.

Computing infrastructure is central to India's AI ambitions. The IndiaAI initiative was initially structured around a public AI compute infrastructure comprising 10,000 or more graphics processing units (GPUs, the specialized chips used to train AI models). Subsequent official updates indicate that India has now onboarded over 38,000 GPUs, most likely a combination of various Nvidia, AMD, Intel, AWS, and Google chips. While this does not position India as a frontier-compute superpower, it does establish a domestic experimentation environment where Indian companies can train, fine-tune, and deploy systems tailored to local requirements.

For context, OpenAI's single Stargate facility in Abilene, Texas, is planned to contain 450,000 Nvidia B200 chips, illustrating the vast gap between India's infrastructure and the largest US AI clusters. However, India's 38,000 GPUs are sufficient for developing practical, locally-focused AI applications.

Which Indian AI Models Are Already in Use?

Multiple companies are already providing locally developed large language models marketed as supporting India's linguistic diversity. These include:

• Sarvam AI: Released 30-billion and 105-billion parameter open-source models trained entirely in India using IndiaAI compute, with tools for speech, translation, and document understanding supporting all 22 official languages of India.
• BharatGen: A government-supported initiative led by an academic consortium that introduced a multilingual 17-billion parameter Param2 model intended for public-sector applications.
• Krutrim: Developed a multilingual model and cloud platform for Indian developers and businesses, including Krutrim-2, a 12-billion-parameter model supporting English and Indian languages.

While these models are smaller than globally dominant LLMs, whose parameter counts are usually undisclosed but estimated in the hundreds of billions or more, the Indian models are more locally specialized, with emphasis on Indian languages, domestic use cases, and deployment within India's AI infrastructure.

What Are the Key Areas for EU-India Collaboration?

The biggest opportunities for EU-India cooperation lie in applied AI rather than frontier-model development. These include multilingual systems, climate and disaster modeling, healthcare, industrial AI, controlled testing environments, and AI safety evaluations. Individual European member states are also pursuing bilateral AI partnerships with India, reflecting broader European interest in collaboration.

France and India have signed an AI declaration encompassing industrial partnerships, research on large language models, and AI norms and standards. Germany and India have established an AI pact focused on industrial AI collaboration, responsible AI development, and exchange of experience on the EU AI Act. Italy, Sweden, Finland, and Czechia have all identified AI as a priority area for cooperation with India.

How Can the EU and India Strengthen Their AI Partnership?

Despite India's progress, significant gaps remain that international collaboration can address. India ranks third globally for AI research output but only eighth for patents and fifteenth for citation impact. Only 16 percent of Indian AI papers have a foreign co-author, the lowest share among the top ten research nations. The country spends only about 0.6 percent of gross domestic product on research and development, compared with 3 to 4 percent in leading innovation economies, and lacks substantial private investment in AI.

• Research Collaboration: Increase joint research projects between European and Indian institutions to boost citation impact and patent development, addressing India's current gaps in these metrics.
• Data and Annotation: Develop annotated Indian-language datasets, which are currently thin and limit the effectiveness of locally-trained models for linguistic diversity.
• Advanced Computing Access: Provide access to additional computing resources and expertise, enabling India to scale its AI infrastructure beyond the current 38,000 GPUs.
• Talent Exchange: Facilitate researcher and developer exchanges between EU and Indian institutions, addressing India's scarcity of top-tier AI researchers while leveraging India's growing GitHub developer base.

Europe's value to India extends beyond regulatory frameworks. While the EU AI Act provides Europe with a strong legal framework for AI rights, safety, and compliance, it also offers industrial environments for AI deployment, research networks, standards expertise, and public funding. This combination of regulatory clarity and practical infrastructure makes the EU an attractive partner for India's AI ambitions.

The EU-India partnership also reflects a broader global trend: most countries recognize that frontier-model development is not their path forward. Instead, they are investing in applied AI systems that solve real problems in their economies and societies. By collaborating on multilingual tools, industrial applications, and AI safety, the EU and India are building a model of AI cooperation that could be replicated across other regions seeking to develop trusted, affordable AI capabilities without competing in an expensive and winner-take-all frontier-model race.