Google Research · Multivariate Forecasting

TimesFM-3

A 330M decoder-only transformer for time-series forecasting pretrained on over a trillion time points, and the first in the line that is natively multivariate - where TimesFM and 2.5 were strictly univariate, this handles multiple targets, past covariates and past-future dynamic covariates in one forward pass. Uses 32-step patches, alternating causal temporal and full variate attention, and non-autoregressive contiguous patch masking to emit nine quantiles per target in a single pass. Tops Gift-Eval, FEV-Bench and TIME against Chronos-2, Toto 2.0 and TimesFM-2.5 on both point and probabilistic metrics; code and weights released, BigQuery integration promised.