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 (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.
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, G42, and Cerebras Systems have launched K2 Think V2, a 70-billion parameter reasoning system built on the K2-V2 base model. K2 Think V2 is fully open-source, from pre-training data to post-training alignment, ensuring transparency and reproducibility. It achieves leading results on complex reasoning benchmarks like AIME2025 and GPQA-Diamond. Why it matters: This release marks a significant advancement in the UAE's AI capabilities, demonstrating leadership in building globally accessible and fully sovereign AI systems focused on reasoning.
MBZUAI, Petuum, and LLM360 have launched K2-65B, an open-source 65B parameter LLM, trained on 1.4T tokens using 480 A100 GPUs. K2-65B outperforms Llama 2 70B while using 35% fewer resources, emphasizing sustainable AI development. The model and its chat variant, K2-Chat, excel in math, coding, medicine, and human-like response generation, with the model available under the Apache 2.0 license. Why it matters: This launch highlights the UAE's increasing capabilities in developing efficient and high-performing LLMs, promoting open-source collaboration and setting new standards for sustainable AI practices in the region.
MBZUAI and G42 have launched K2 Think, an open-source AI system for advanced reasoning with 32 billion parameters. It outperforms reasoning models 20 times larger, employing techniques like long chain-of-thought fine-tuning and reinforcement learning. K2 Think will be available on Cerebras' platform, achieving 2,000 tokens per second, and ranks highly in math performance. Why it matters: This launch positions the UAE as a leader in AI innovation through public-private partnerships and open-source contributions, demonstrating that efficient AI design can rival larger models.
KAUST researchers collaborated with the Paris Observatory and the National Astronomical Observatory of Japan (NAOJ) to develop advanced Extreme-AO algorithms for habitable exoplanet imaging. The new algorithms, powered by KAUST's linear algebra code running on NVIDIA GPUs, optimize and anticipate atmospheric disturbances. The implemented Singular Value Decomposition (SVD) algorithm won an award at the PASC Conference 2018 and is used at the Subaru Telescope in Hawaii. Why it matters: This advancement enhances the ability to image exoplanets, potentially leading to breakthroughs in the search for habitable planets using ground-based telescopes.
MBZUAI is hosting the K2 Think Hackathon, challenging participants to develop applications using the K2 Think reasoning model developed with G42. The hackathon involves a global idea call followed by a 48-hour build challenge in Abu Dhabi for the top 10 teams. The winning feature will be integrated into the K2 Think application. Why it matters: This hackathon provides a valuable opportunity to test and shape a cutting-edge AI model, potentially leading to innovative applications in various sectors like finance and education within the UAE and beyond.