A compact, no-frills language model that prioritizes transparency over performance. Trained on deduplicated data, it produces cleaner outputs than its non-deduped sibling, but its small size means it struggles with complex reasoning and longer context coherence. Researchers value it more as a controlled experimental subject than a production workhorse.