Consilium: When Multiple LLMs Collaborate

Consilium introduces a framework for coordinating multiple large language models (LLMs) to enhance collaborative decision-making processes. The architecture enables dynamic task allocation among LLMs, optimizing performance based on their individual strengths and weaknesses. This approach has shown significant improvements in task completion time and accuracy on benchmark datasets, making it a valuable tool for practitioners seeking to leverage the complementary capabilities of multiple models in complex AI applications.