Moirai-MoE-1.0-R-Base
Model directorySalesforce/moirai-moe-1.0-R-base~0.94B stored params params | Upstream checkpoint
Moirai-MoE-1.0-R-Base is Salesforce's sparse-expert extension of the Moirai line, the larger counterpart to Moirai-MoE-1.0-R-Small. Instead of relying on a single dense network for all behaviors, the Moirai-MoE design routes tokens through specialized experts to improve parameter efficiency and specialization across heterogeneous series.
Architecturally it is a sparse mixture-of-experts decoder-only transformer with probabilistic output heads, holding around 0.94B stored parameters. Because routing activates only a subset of experts per token, inference stays cheaper than an equally sized dense alternative while still supporting multivariate zero-shot forecasting with calibrated quantiles. The checkpoint card is sparse; Salesforce's official Moirai-MoE materials describe large heterogeneous time-series pretraining for the setup rather than a separate narrow corpus for this exact checkpoint.
Where to run this model
Compute availability, hardware requirements, and pricing depend on the execution provider.
Get model weights, deployment instructions, and current provider listings.
Hugging Face provider mappings checked 2026-10-06. No Inference Provider mapping was listed for this checkpoint.
Model Classification
Family
Moirai-MoE-1.0-R
Type
time series foundation model
Pretrained time-series model for zero-shot or few-shot forecasting workloads.
Resources
Training Data
Official checkpoint card is sparse; Salesforce's official Moirai-MoE materials describe large heterogeneous time-series pretraining in the Moirai-MoE setup rather than a separate narrow corpus for this exact checkpoint.
Recommended For
- • Multivariate forecasting across heterogeneous domains
- • Workloads that benefit from probabilistic outputs and arbitrary variate counts
Strengths
- • Strong multivariate coverage across the Moirai family
- • Well-suited to covariates and correlated series
Limitations
- • Model cards for some newer Moirai variants are still sparse on exact checkpoint details
- • Heavier family choices can be more expensive than tiny single-purpose baselines
Capabilities
Tags
Specifications
- Parameters
- ~0.94B stored params
- Architecture
- sparse MoE decoder-only transformer with probabilistic output heads
- Context length
- n/a
- Max context
- n/a
- Minimum history
- n/a
- Recommended history
- n/a
- Input step
- n/a
- Required target series
- 1
- Temperature
- Ignored
- Top P
- Ignored
- Max output
- n/a
- License
- n/a