Inception, Cerebras, And MBZUAI Release Jais 2, The Next Generation Of Their Open-Weight Arabic Large Language Model

The Abu Dhabi-based artificial intelligence (AI) firm Inception, in partnership with the California-based AI computing company Cerebras Systems and the Abu Dhabi-based Institute of Foundation Models at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), has released Jais 2, the next generation of their open-weight Arabic large language model (LLM).

Built with 70 billion parameters and trained on the richest Arabic-first dataset to date, Jais 2 makes use of a redesigned architecture and a cleaner dataset that together improve the model’s reasoning and fluency across Modern Standard Arabic and regional dialects, besides showing strong performance in English. It has been trained to handle real-world linguistic patterns such as code-switching and informal tone, while maintaining advanced technical and creative capabilities. It also incorporates a safety-focused framework that relies on instruction-tuning, evaluation, and continuous user feedback. 

In a statement, Ashish Koshy, CEO of Inception, said, “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. We are incredibly proud to help deliver a system that will accelerate innovation for millions across the region and beyond.” 

Natalia Vassilieva, VP and Field CTO, Cerebras Systems, added, “Jais underscores the UAE’s growing leadership in building advanced, open-weight AI systems. At Cerebras, we’re proud that Jais 2 was both trained and is now served on Cerebras systems, in close partnership with our UAE collaborators. By combining their expertise with machine learning techniques, uniquely enabled by Cerebras hardware, we achieved state-of-the-art quality using only a fraction of the compute used to train similar-sized models in the past. 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.” 

Professor Preslav Nakov, Department Chair and Professor of Natural Language Processing at MBZUAI, said, “Arabic has long been underserved in AI development due to limited high-quality data for training LLMs. Today, with Jais, we mark a defining advancement for Arabic AI, as we share a model that is built not only with scale, but with cultural and linguistic fidelity at its core. 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.”