Moirai-1.0-R-Base
onlineSalesforce/moirai-1.0-R-base91M params | 512 context | $0.00025 per forecast
Moirai-1.0-R-Base is the reference dense checkpoint in the original Moirai family. It keeps the any-variate masked-encoder design while scaling model capacity enough to improve general forecasting quality on heterogeneous multivariate settings. It is a good default dense Moirai checkpoint when you want stronger accuracy than the small model without jumping to the much larger large variant.
Model Classification
Family
Moirai
Type
time series foundation model
Pretrained time-series model exposed on TSFM.ai for zero-shot or few-shot forecasting workloads.
Resources
Training Data
LOTSA, the Large-scale Open Time Series Archive, with roughly 27B observations across nine domains including energy, transport, finance, healthcare, sales, climate, web, and social data.
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
- 91M
- Architecture
- masked encoder transformer with multi-patch projections, any-variate attention, and mixture-distribution output
- Context length
- 512
- Max context
- 8,192
- Minimum history
- n/a
- Recommended history
- n/a
- Input step
- n/a
- Required target series
- 1
- Temperature
- Ignored
- Top P
- Ignored
- Max output
- 1,024
- Avg latency
- n/a
- Uptime
- n/a
- Plan limits
- 1,000 rpm free · 1,000,000 rpm with billing
- Accelerator
- T4
- Regions
- Virginia, US
- License
- n/a
Pricing
- Per forecast
- $0.00025
Performance
- Average latency
- n/a
- Availability
- n/a
- Plan limits
- 1,000 rpm free · 1,000,000 rpm with billing