BigQuery is introducing TimesFM 3.0, a new foundation model for multivariate time-series forecasting directly within SQL. Previously, AI.FORECAST supported only univariate forecasting. TimesFM 3.0, developed by Google Research, excels at multivariate forecasting, ranking highly on public leaderboards like GIFT-Eval. It can forecast multiple correlated target columns simultaneously. The model also supports covariate forecasting, using both past and future known values. This enables more accurate predictions by incorporating external drivers like weather or promotions. Existing univariate forecasting and anomaly detection workflows can benefit from TimesFM 3.0 by simply updating the model specification. Multivariate forecasting in BigQuery requires a specific input table format with historical and future horizon rows. Users can also leverage natural language prompts in BigQuery Conversational Analytics for multivariate forecasting. This new capability eliminates the need for complex data pipelines and model infrastructure for enterprise-grade forecasting.