Abu Dhabi IFM opens source six K2 Horizon models, ranging from 0.9B to 375B parameters.

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Abu Dhabi IFM has open-sourced six K2 Horizon models with parameter sizes ranging from 0.9B to 375B. The 0.9B and 3.7B models are optimized for edge and mobile devices, while the 375B-A23B employs a MoE architecture. Open interest in large models remains strong, with AI-driven projects among the altcoins to watch. The 0.9B, 3.7B, and 7B models have set new benchmarks. IFM will release training code, data recipes, and checkpoints under the Apache 2.0 license. The 375B-A23B achieved a score of 47 on the Intelligence Index, nearing that of MiniMax-M3.
ME AI News, Dongcha Beating AI Bulletin: MBZUAI’s Institute for Foundation Models (IFM) in the UAE has released K2 Horizon, open-sourcing six models at once: 0.9B, 3.7B, 7B, 32B, 36B-A4B, and 375B-A23B. The 0.9B model is designed for edge devices such as watches and glasses, while the 7B model can run on smartphones. The largest model, 375B-A23B, employs MoE, activating approximately 23B parameters per generated token. The official team states that the 0.9B, 3.7B, and 7B models set new benchmarks across multiple evaluations within their respective size categories. In addition to the final weights, the training code, data or data construction recipes, intermediate checkpoints, training logs, and evaluation records will also be made public. Some data is subject to licensing restrictions and cannot be redistributed directly, but the sources, construction methods, and ratios will be disclosed. The models and code are licensed under Apache 2.0. Artificial Analysis assigned the 375B-A23B an Intelligence Index score of 47, nearing MiniMax-M3’s score of 45. It performs stronger on agent tasks but is relatively weaker in knowledge and complex reasoning. (Source: BlockBeats)
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