SAIL Model Team

The SAIL team introduces SAIL, an open scientific agent model with 35B total and 3B active parameters, developed through a science-aware improvement loop in which frontier-model agents diagnose its task failures and build training tasks from papers and code repositories, then trained via supervised fine-tuning, specialist training, multi-teacher on-policy distillation, and agentic reinforcement learning; it improves over its base model on all 13 evaluations and achieves the highest SciCode and ArxivDIGESTables scores in the comparison.

The SAIL team introduces SAIL, an open scientific agent model with 35B total and 3B active parameters, developed through a science-aware improvement loop in which frontier-model agents diagnose its task failures and build training tasks from papers and code repositories, then trained via supervised fine-tuning, specialist training, multi-teacher on-policy distillation, and agentic reinforcement learning; it improves over its base model on all 13 evaluations and achieves the highest SciCode and ArxivDIGESTables scores in the comparison.