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Introducing IndQA

For developers building AI workflows for Indian users, IndQA offers a much-needed tool to test and improve models' cultural and linguistic competence, directly impacting user trust and product adoption in one of the world's fastest-growing tech markets.

OpenAI Blog·November 3, 2025·1 min readresearch

researchIntroducing IndQA

openai.com

What happened

OpenAI has released IndQA, a new benchmark designed to evaluate how well AI systems understand and reason in Indian languages. Developed in collaboration with domain experts, IndQA covers 12 languages—including Hindi, Bengali, and Tamil—and spans 10 knowledge areas such as history, science, and local customs. Unlike earlier benchmarks, it specifically tests cultural context and reasoning, not just translation accuracy. For builders creating AI workflows for Indian users, this benchmark offers a standardized way to measure and improve model performance on region-specific tasks. It also highlights the growing need for multilingual and culturally aware AI systems, particularly in underserved language markets. Developers can use IndQA to validate their models' readiness for deployment in India, a rapidly expanding digital economy.

Key takeaways

OpenAI launched IndQA, a benchmark for AI systems in 12 Indian languages across 10 knowledge areas.
The benchmark emphasizes cultural understanding and reasoning, not just language translation.
IndQA was built with domain experts to ensure relevance and accuracy.
It provides a standardized evaluation method for developers targeting Indian-language applications.
The benchmark addresses a gap in evaluating AI models for underserved language markets.