Moirai-1.0-R-Base

Moirai-1.0-R-Base is the reference dense checkpoint in Salesforce's original Moirai family, sitting between Moirai-1.0-R-Small and Moirai-1.0-R-Large. At 91M parameters it is the natural default for the first-generation Moirai design: enough capacity to improve general forecasting quality on heterogeneous multivariate settings without the cost of the large variant.

It keeps the same masked-encoder transformer used across the dense 1.0-R line, with multi-patch projections, any-variate attention, and a mixture-distribution output head. The any-variate attention lets a single model handle arbitrary numbers of target variables and dynamic covariates, while the mixture output head returns probabilistic forecasts with calibrated quantiles rather than a single trajectory. Like its siblings it is pretrained on the LOTSA corpus, giving it broad zero-shot coverage across domains.

On TSFM.ai pick it as the balanced dense Moirai option when you want stronger accuracy than Moirai-1.0-R-Small but do not need to jump to Moirai-1.0-R-Large. Move down to the small checkpoint when serving cost or throughput dominates, up to the large checkpoint when a workload rewards the extra capacity, or across to the 1.1-R family if your series skew toward low-frequency yearly and quarterly cadences.