Based in the Emirati capital, Abu Dhabi, the Institute of Foundation Models (IFM) introduced K2 Horizon last week. This group of six AI foundation models, ranging from 0.9 billion to 375 billion parameters, is claimed to be the “largest fully open-source fleet of AI models” yet made available.

IFM uses “fully open” to mean more than mere downloadable model weights. Across K2 Horizon, it has committed to publishing training and evaluation code, training data where redistribution is possible or detailed construction recipes where it is not, plus configurations, logs and intermediate checkpoints spanning pretraining through agentic post-training.

The aim is to let developers inspect how the models were built, reproduce their development and adapt them for their own work. But that commitment should not be confused with complete availability at launch: All six models had downloadable weights, while the model cards for the 0.9B, 32B and flagship 375B said some training data, code or checkpoints would arrive later. The 32B release was also only a Stage 1 checkpoint, with the final model still to come.

“Open source is much more than open weights. Science works when others can see the data, follow the method, reproduce the result, and improve on it,” said Eric Xing , IFM founder and university professor at the Mohamed bin Zayed University of Artificial Intelligence. “K2 Horizon delivers on that need. Every model in the fleet ships with its training data, recipe, and evaluations.

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