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  5. Contrastive Language Model
Model Architecturesaka CLM

Contrastive Language Model

A Contrastive Language Model (CLM) is a System One model that trains a state encoder and an action encoder with a contrastive loss, then picks the candidate action whose embedding best matches the current state.

Ask Melo about this← all terms

CLM-8B, released September 2026 under Apache 2.0, is trained on 60M Q&A pairs, 30M synthetic hard negatives and 1M agentic trajectories. Because state and action embeddings are cached independently, it runs up to 9x faster than Jev on some zero-shot tasks, and a fine-tuned version acts as a fast verifier for best-of-N coding agents.

Related terms

System One ModelJevContrastive LearningEmbeddingRLCD (Reinforcement Learning for Calibrated Decisions)Encoder-Only Model