Introducing K2 Horizon: Frontier Performance, Radically Open

Today IFM is releasing K2 Horizon, a connected fleet of six models: 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B. Across reasoning, mathematics, coding, agentic tasks, and general capabilities, K2 Horizon delivers top-tier performance in every size class—with the 0.9B, 3.7B, and 7B models setting new state of the art at their respective scales. K2 Horizon is also our most comprehensive open release to date. For every model, we are opening the training lifecycle from pretraining through reasoning and agentic post-training. We are releasing intermediate checkpoints, training data or detailed data-construction recipes, open architecture, mixture compositions, training code, configurations, fine-grained logs, evaluation results, and final weights. The models and code are released under the Apache 2.0 license. Datasets are released under their applicable licenses, such as ODC-BY; We disclose how the data was constructed and mixed when redistribution is not possible. Together, K2 Horizon represents the most comprehensive open model release to date: A new performance frontier across scales. The 0.9B, 3.7B, and 7B models achieve world-leading performance in their size classes across widely used evaluations. The 36B-A4B model, equipped with our new Mixture-of-Value-Attention (MoVA) mechanism, delivers exceptional capability per active parameter, outperforming some much larger models. The 32B and 375B-A23B models rank among the top models in their respective classes. Together, the six models provide competitive performance across deployment environments ranging from edge devices to the enterprise. The first fully open model fleet for agents. K2 Horizon is the first open model family to expose the complete development process through agentic post-training. By releasing checkpoints, data (or data recipe), code, configurations, and training logs across every stage, K2 Horizon makes it possible to study how reasoning, tool use, planning, and agentic capabilities emerge; reproduce the methods that create them; and adapt those methods to new tools, environments, and domains. Six models spanning edge to enterprise. The 0.9B model is designed for highly constrained environments such as watches and glasses, while the 3.7B and 7B models bring advanced capabilities to phones and other on-device applications. The dense 32B model and sparse 36B-A4B model provide powerful options for local workstations and efficient serving. The 375B-A23B model brings the fleet’s strongest capabilities to demanding enterprise deployments. All six models include quantization support. One connected fleet. The six models share core architecture, vocabulary, training methodology, interfaces, evaluation infrastructure, and deployment tooling, with a smaller vocabulary for the 0.9B model. This consistency also makes it easier to move between sizes, route work dynamically, and study capability and efficiency across scale.

World-leading performance across the scales The 0.9B, 3.7B, and 7B models achieve state-of-the-art results in their respective classes across mathematics, reasoning, general capability, coding, and agentic tasks. The 36B-A4B model performs beyond the level normally expected from its active parameter count, demonstrating the efficiency of our unique Mixture-of-Expert design when computing attention values. The 32B and 375B-A23B models place among the top models in their respective comparison classes. The small models are especially notable. K2 Horizon 0.9B achieves an AIME 2026 score above 48, along with strong reasoning, tool-use, and agentic capabilities.

A Deep Dive into The K2 Horizon Fleet K2 Horizon 375B-A23B: the enterprise powerhouse K2 Horizon 375B-A23B is the fleet’s largest and most capable model.