ChatTS is a specialized large language model designed for time series analysis that provides conversational QA capabilities for exploring structure, changes, and relationships across multiple time series of varying lengths. The model natively handles multivariate time series and retains raw numerical values for precise quantitative answers. It integrates with standard LLM pipelines through Transformers and vLLM support, includes complete training and evaluation datasets, and was presented at VLDB 2025.