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.
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.
Intriguing. Should be interesting to compare this to Qwen3.8 (27B). I've been plenty impressed with Qwen's ability, but boy does it like to overthink things, even after getting it off the default xhigh reasoning, it'll take 20 minutes to plan something, thinking so much it'll have to compress its context multiple times to reach a single answer. The quality of the answer is great, but there has to be a middle ground.