Inception, Cerebras, and MBZUAI Launch Arabic Open-weight LLM Jais 2
The model has proven to be proficient across diverse content, covering Arabic poetry, culture, and social media tone of voice, resulting in its ability to capture Arabic as a language used in daily life.
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[Image source: Chetan Jha/MITSMR Middle East]
Inception, Cerebras Systems, and the Institute of Foundation Models at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) on Tuesday announced the launch of Jais 2, an open-weight Arabic large language model (LLM).
Jais 2 is built with 70 billion parameters and trained on the richest Arabic-first dataset to exist.
“The use of Arabic within AI has historically been constrained by limited datasets and fragmented representation. Jais 2 addresses these limitations by bringing unprecedented depth, nuance, and contextual intelligence to the language. From dialect to tone, the model understands Arabic as it is spoken, written, and lived,” said Ashish Koshy, CEO, Inception, a G42 company.
JAIS 2 is designed to offer more powerful reasoning, improved fluency across modern standard Arabic and regional dialects, and strong English performance. It aims to better handle real-world language patterns, such as code-switching and informal speech, while delivering advanced technical and creative capabilities.
“Jais underscores the UAE’s growing leadership in building advanced, open-weight AI systems. The momentum in the UAE is remarkable, and we remain committed to empowering this ecosystem with efficient compute and deep collaboration to accelerate innovation and broaden access to high-performance AI,” said Natalia Vassilieva, VP and Field CTO, Cerebras Systems.
Notably, it has proven to be proficient across diverse content, covering Arabic poetry, culture, and social media tone of voice, resulting in the model capturing Arabic as a language used in daily life.
“Arabic has long been underserved in AI development due to limited high-quality data for training large language models. Today, with Jais, we mark a defining advancement in Arabic AI, as we share a model built not only with scale, but with cultural and linguistic fidelity at its core,” said Professor Preslav Nakov, Department Chair and Professor of Natural Language Processing, MBZUAI.
“By dramatically expanding the quality and diversity of Arabic data, we have created a foundation that reflects the richness of the Arabic language. This model stands as an example of how AI can evolve through cultural alignment, safety-centered design, and open innovation,” he added.
