Institute of Foundation Models

K2 Horizon Uno

Institute of Foundation Models

K2 Horizon Uno augments the Horizon autoregressive language backbone with a conditional LoRA diffusion pathway for parallel token proposals. The released 7B and 0.9B adapters require separately downloaded base model weights; the adapter repository is not a complete 7B language checkpoint. Uno’s sampler verifies proposed tokens against the frozen autoregressive pathway, preserving its output distribution under the method’s assumptions. This is a substantive decoding specialization rather than an independently enlarged language backbone. Apache-licensed adapters, code, training recipes, and a technical report support evaluation; throughput gains depend on workload and inference configuration.

K2 Horizon

Institute of Foundation Models

K2 Horizon is the Institute of Foundation Models’ open language-model fleet spanning 0.9B, 3.7B, 7B, 32B, 36B-A4B, and 375B-A23B tiers. The release combines dense and sparse models, including the 36B tier’s Mixture-of-Value-Attention design, for reasoning, mathematics, coding, and agents. Apache-licensed models and code are accompanied by intermediate checkpoints, training data or construction recipes, configurations, logs, and evaluations. Context differs by training stage: the documented 7B and 32B final views support 512K, while earlier base and midtraining checkpoints have smaller limits. Tier names describe core model sizes and may differ from all-parameter repository totals.