Salesforce Models

Salesforce Moirai — hosted and ready

Run Moirai 1.1 through the TSFM.ai API. A universal time series forecasting model with covariate support, multiple sizes, and context lengths up to 5000 — no infrastructure to manage.

Moirai 1.1Covariate supportUp to 5000 context length
MoiraiPOST /v1/forecast
{
  "model": "salesforce/moirai-1.1-r-base",
  "inputs": [{
    "item_id": "store-revenue",
    "target": [8500, 8700, 9100, 8900, 9300, 9500],
    "start": "2026-03-01T00:00:00Z"
  }],
  "parameters": {
    "prediction_length": 21,
    "freq": "D",
    "quantiles": [0.1, 0.5, 0.9]
  }
}

Same request shape as every other model on TSFM.ai.

Architecture

Universal transformer with any-variate attention

Context

Up to 5000 time steps — longest in the catalog

Covariates

Supports exogenous variables alongside the target series

Why teams choose Moirai

Universal forecasting

Moirai is trained across diverse domains and frequencies. It generalizes well to new datasets without fine-tuning, making it a strong default for teams with heterogeneous data.

Covariate support

Pass exogenous variables — promotions, holidays, weather — alongside your target series. Moirai's any-variate attention mechanism incorporates them directly into the forecast.

Longest context in the catalog

With support for up to 5000 time steps of history, Moirai can capture long-range seasonal patterns that shorter-context models miss. Ideal for weekly and monthly data with yearly cycles.

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Moirai variants on TSFM.ai

Moirai 1.1-R ships in multiple sizes. All variants support covariates and extended context lengths.

Getting started with Moirai

  1. 1

    Pick a variant

    Start with moirai-1.1-r-base for most workloads. Use small for high-throughput batch jobs or large when forecast accuracy is the top priority.

  2. 2

    Send a forecast request

    POST to /v1/forecast with model set to your chosen variant. Include covariates in the inputs array if you have exogenous signals like promotions or weather.

  3. 3

    Leverage the extended context

    If your data has strong yearly seasonality, pass up to 5000 historical observations. More context helps Moirai capture long-range patterns that improve forecast quality.

Frequently Asked Questions

Try Moirai on your data

Send a series with covariates, pick a horizon, and see how Moirai 1.1 performs. No setup, no weights, no GPU — just an API key.