Google’s TimesFM-3 forecasts several related series at once, with no fine-tuning

Google Research released TimesFM-3 on 31 August 2026, a 330-million-parameter decoder-only foundation model for time-series forecasting pre-trained on more than a trillion time points. Unlike its predecessors it handles multiple targets, past covariates and past-future covariates together in zero shot, emits nine quantiles per step, and produces the whole forecast horizon in one forward pass. Google reports it top-ranked among pre-trained foundation models on GIFT-Eval, fev-bench and TIME for both point and probabilistic metrics. The repository code is Apache-2.0; the weights carry a non-commercial, non-production licence.

What it means Check the licence before you plan on it: the code is Apache-2.0 but the weights are non-commercial and non-production, which rules out most business forecasting.