Show HN: LLMRouter – Stop using GPT-4/o1 for everything (16 routing strategies) (github.com)

LLMRouter has been released as a versatile intelligent routing system that enhances LLM (large language model) inference by intelligently selecting the most appropriate model based on query characteristics. This innovative tool supports over 16 distinct routing strategies organized into four categories, including single-round and multi-round routers, allowing for optimized performance based on task complexity and cost efficiency. Furthermore, it features a unified command-line interface and an automated data generation pipeline that can harness data from 11 benchmark datasets, significantly streamlining the overall LLM operation process. This development is significant for the AI/ML community as it presents a sophisticated approach to optimize LLM deployment, reducing resource consumption while potentially improving response accuracy and relevance. With the ability to plug in custom routers and a rich set of tools for both training and inference, LLMRouter provides researchers and developers with flexibility and ease of use. The integration of diverse routing techniques—from K-Nearest Neighbors to hybrid probabilistic methods—positions LLMRouter as a powerful asset for enhancing various AI applications and advancing research in intelligent model deployment systems.