Editorial illustration for G42 Launches NANDA 87B: Open-Source Hindi-English AI Model from MBZUAI
G42 Unveils NANDA 87B: Open-Source Hindi-English AI Model
The Hindi-speaking world has waited for an AI that doesn’t just translate, it thinks in the same tongue. Today, from Abu Dhabi, G42 and its partners deliver exactly that: NANDA 87B, an open-source Hindi-English model built atop Llama-3.1 70B by MBZUAI. This isn’t another incremental update.
Trained on over 65 billion Hindi tokens with a purpose-built tokeniser, the model cuts through the inefficiency that plagues most bilingual systems. “India deserves world-class technology that speaks its language,” said Manu Jain, G42 India’s CEO. He’s right.
The implications stretch far beyond code, education, entertainment, enterprise. A model that breathes Hindi natively is a model that finally listens to a billion people.
The model has been developed by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in collaboration with Inception, a G42 company, and chipmaker Cerebras. Built on Llama-3.1 70B, NANDA 87B has been trained on more than 65 billion Hindi tokens using a Hindi-centric tokeniser to improve efficiency in training and inference. "India deserves world-class technology that speaks its language. NANDA 87B is a major step in that direction," said Manu Jain, chief executive of G42 India, adding that the model is intended to support innovation across education, entertainment and enterprise use cases in India's AI ecosystem.
NANDA 87B does not merely translate words; it reimagines the architecture of access. By releasing this model into the open fold, G42 and its partners have done something far more consequential than unveiling a benchmark figure. They have handed India’s educators, creators, and entrepreneurs a tool that speaks their native tongue with computational fluency, a tool that will not sit behind a paywall or a proprietary gate.
The 65 billion Hindi tokens are not just data; they are a linguistic inheritance, now programmable. This is the kind of infrastructure that turns “world-class” from an aspiration into a daily utility. In a landscape often cluttered with closed silos and exorbitant API costs, an open bilingual heavyweight like this is a declaration: technology does not have to be alien to be advanced.
The next chapter of India’s AI story will be written not in English alone, but in the voices of a billion people, and NANDA 87B has just sharpened the pencil.
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Common Questions Answered
How many tokens were used to train the NANDA 87B AI model?
The NANDA 87B model was trained on more than 65 billion Hindi tokens using a specialized Hindi-centric tokenizer. This approach aims to improve the model's efficiency in both training and inference processes for Hindi and English language processing.
What foundational model was used in developing NANDA 87B?
NANDA 87B is built on the Llama-3.1 70B foundational model, developed through a collaborative effort between Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Inception, and Cerebras. This strategic partnership highlights the model's technical ambition in creating a multilingual AI solution.
What is the primary goal of the NANDA 87B AI model?
The primary goal of NANDA 87B is to provide world-class technology that authentically represents Indian linguistic complexity, specifically targeting Hindi and English speakers. As stated by Manu Jain, the model aims to deliver a technological solution that truly speaks the language of India.
Further Reading
- Abu Dhabi's G42 group upgrades Llama-3-Nanda LLM with Hindi-English dataset — Business Standard
- MBZUAI, Inception launch enhanced Nanda Hindi LLM — Middle East AI News
- Papers with Code - Latest NLP Research — Papers with Code
- Hugging Face Daily Papers — Hugging Face
- ArXiv CS.CL (Computation and Language) — ArXiv
