Moirai-MoE-1.0-R-Base
onlineSalesforce/moirai-moe-1.0-R-base~0.94B stored params params | 512 context | $0.5000 input | $1.50 output
Moirai-MoE-1.0-R-Base is Salesforce's sparse expert extension of the Moirai line. Instead of relying on a single dense model for all behaviors, it routes tokens through specialized experts to improve parameter efficiency and specialization across heterogeneous series. Salesforce's official Moirai-MoE materials position the Base variant as a top zero-shot performer in the family while keeping inference cheaper than an equally sized dense alternative.
Model Classification
Family
Moirai-MoE-1.0-R
Type
time series foundation model
Pretrained time-series model exposed on TSFM.ai 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
- 512
- Max output
- 1,024
- Avg latency
- n/a
- Uptime
- n/a
- Rate limit
- n/a
- Accelerator
- NVIDIA GPU
- Regions
- Virginia, US
- License
- n/a
Pricing
- Input / 1M tokens
- $0.5000
- Output / 1M tokens
- $1.50
Performance
- Average latency
- n/a
- Availability
- n/a
- Rate limit
- n/a