Open-source AI models and tools released by GCC institutions — notably Falcon LLM (TII), Jais (MBZUAI/Inception), AraBERT, and other publicly available models.
The UAE President has endorsed the launch of K2 Think, which is described as the world’s most advanced open-source reasoning model. This launch recognizes Sheikh Khalifa’s contributions to advancing science and technology within the UAE. The announcement signifies a major national initiative in the field of artificial intelligence development. Why it matters: This positions the UAE at the forefront of open-source AI innovation and advanced reasoning capabilities, potentially setting new benchmarks for global AI development.
This paper introduces AraLLaMA, a new Arabic large language model (LLM) trained using a progressive vocabulary expansion method inspired by second language acquisition. The model utilizes a modified byte-pair encoding (BPE) algorithm to dynamically extend the Arabic subwords in its vocabulary during training, balancing the out-of-vocabulary (OOV) ratio. Experiments show AraLLaMA achieves performance comparable to existing Arabic LLMs on various benchmarks, and all models, data, and code will be open-sourced. Why it matters: This work addresses the need for more accessible and performant Arabic LLMs, contributing to democratization of AI in the Arab world.
MBZUAI's Institute of Foundation Models (IFM) has released K2 Think V2, a 70 billion parameter open-source general reasoning model built on K2 V2 Instruct. The model excels in complex reasoning benchmarks like AIME2025 and GPQA-Diamond, and features a low hallucination rate with long context reasoning capabilities. K2 Think V2 is fully sovereign and open, from pre-training through post-training, using IFM-curated data and a Guru dataset. Why it matters: This release contributes to closing the gap between community-owned reproducible AI and proprietary models, particularly in reasoning and long-context understanding for Arabic NLP tasks.
IFM has released K2-V2, a 70B-class LLM that takes a "360-open" approach by making its weights, data, training details, checkpoints, and fine-tuning recipes publicly available. K2-V2 matches leading open-weight model performance while offering full transparency, contrasting with proprietary and semi-open Chinese models. Independent evaluations show K2 as a high-performance, fully open-source alternative in the AI landscape. Why it matters: K2-V2 provides developers with a transparent and reproducible foundation model, fostering trust and enabling customization without sacrificing performance, which is crucial for sensitive applications in the region.
MBZUAI's Institute of Foundation Models has released K2, a 70-billion-parameter, reasoning-centric foundation model. K2 is designed to be fully inspectable, with open weights, training code, data composition, mid-training checkpoints, and evaluation harnesses. K2 outperforms Qwen2.5-72B and approaches the performance of Qwen3-235B. Why it matters: This release promotes transparency and reproducibility in AI development, providing researchers with the resources needed to study, adapt, and build upon a strong foundation model.
MBZUAI increased faculty diversity and worked with global partners on application projects in 2023, including developing Jais (with Core42 and Cerebras) and Vicuna (with UC San Diego, UC Berkeley, CMU, and Stanford). They also launched Jais Climate, a bilingual LLM for climate intelligence, and LLM360, a framework for transparent LLM research. Why it matters: MBZUAI's involvement in open-source GenAI initiatives and partnerships positions the UAE as a key player in responsible AI development and talent creation.
The Technology Innovation Institute (TII) in Abu Dhabi inaugurated the Open-Source AI Summit, gathering over 300 international AI experts, including representatives from Meta and Google DeepMind. Discussions centered on ethical considerations in AI ownership, sustainable AI computing innovations, and compute power challenges. TII leadership emphasized the importance of open-source models like Falcon AI for fostering collaborative innovation and global access. Why it matters: The summit highlights the UAE's commitment to shaping the global AI agenda by promoting open-source AI development and addressing critical governance and ethical issues.
KAUST Assistant Professor Paula Moraga has authored a new textbook, "Spatial Statistics for Data Science: Theory and Practice with R," based on her lectures. The book is available for free on her website and in hard copy through the publisher. Dr. Moraga's research focuses on developing statistical methods and computational tools for geospatial data analysis and health surveillance, with applications in reducing disease burden and identifying high-risk populations. Why it matters: The publication strengthens KAUST's research profile in spatial data science and offers valuable open-source resources for addressing critical challenges in public health and resource management within Saudi Arabia and the broader region.
MBZUAI is hosting a short course on developing open-source machine learning packages. The course will be led by Chih-Jen Lin, an affiliated professor at MBZUAI and distinguished professor at National Taiwan University, who has developed widely used ML packages like LIBSVM and LibMultiLabel. The course will cover topics such as starting a project, choosing functionalities, and identifying research problems from user feedback. Why it matters: This course can help improve the quality and usability of open-source machine learning tools coming from the region's research institutions.