Toto
Decoder-only multivariate transformer optimised for observability metrics. Pre-trained on a mix of Datadog telemetry, open datasets, and synthetic data — 4–10× larger than the pretraining corpora of competing TSFMs. Ships with the BOOM observability benchmark.
Toto is Datadog's time-series foundation model, specifically aimed at the observability domain — high-frequency, multivariate signals from metrics infrastructure rather than the macroeconomic or energy-load series that dominate most TSFM benchmarks.
The model is a 151M-parameter decoder-only transformer with several architectural tweaks for multivariate observability data. Pretraining mixes Datadog's own telemetry with open and synthetic series and is reported to be 4–10× larger than the pretraining corpora of leading competitors. The release ships with BOOM, a 350M-point benchmark of real-world Datadog observability signals.
Versions on TS-Arena
Each version below corresponds to one registered model id in the leaderboard. Click through to its detail page for per-model rankings, forecasts, and history.
- Toto Open Base 1.0toto151M params…
151M-parameter decoder-only transformer; the openly released base size.