Contrastive-LM · Agent Decision Model

CLM-v0.1-8B

Adds two small projection heads, a state head and an action head, on top of a frozen Qwen3-8B encoder, trained with a bidirectional InfoNCE contrastive loss rather than as a generative model, built for scoring, ranking and agent tool or action selection. Trained in three phases: pretraining on roughly 60M Nemotron Q&A pairs, mid-training on 30M synthetic hard negatives, and post-training on 1M agentic trajectories, at a 2,048-token maximum sequence length. Reports state-of-the-art on DeepSWE at 81.6% and Terminal-Bench 2.1 at 87.6%, and claims 4-9x lower latency than Jev (week 38) at comparable zero-shot performance on computer-use and tool-calling. Apache 2.0, weights on Hugging Face, pip installable.