TimesFM Forecasting

Overview

TimesFM (Time Series Foundation Model) is a pretrained decoder-only foundation model developed by Google Research for time-series forecasting. It works zero-shot — feed it a time series and it returns point forecasts with quantile prediction intervals, no training required. The timesfm package (current 3.0.2) ships two model APIs:

• TimesFM 2.5 (200M, Apache-2.0 weights) — timesfm.TimesFM_2p5_200M_torch with ForecastConfig; univariate, optional covariates via XReg. The default in this skill and the only choice for commercial or production use.
• TimesFM 3.0 (~330M, released Aug 2026) — timesfm3.TimesFM3Forecaster; univariate and multivariate forecasting with native past-only and past-and-future covariates. Its weights are under timesfm-non-commercial-license-v1.0, so use it only for non-commercial research and tell the user about the restriction.