Time series / Model

TimesFM 3.0

Organisation
Google Research
Family
TimesFM · version 3.0
Released
2026-08-31 (Google Research blog post 'TimesFM-3: A zero-shot foundation model for multivariate forecasting' dated August 31, 2026 (https://research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/); HF repo google/timesfm-3.0-pytorch created 2026-08-24)
Checkpoints
google/timesfm-3.0-pytorch
Weights
Open · timesfm-non-commercial-license-v1.0
Links

Training data disclosure: Partial list

Level determined for 4% of benchmark cells.

“timesfm-3.0 is pretrained using”
huggingface.co · model card · Data · retrieved 2026-10-15
“Synthetic and augmented data.”
huggingface.co · model card · Data · retrieved 2026-10-15
“TimesFM-3 has 330 million parameters and is pre-trained on a real-world and synthetic time-series corpus comprising more than 1 trillion time points.”
research.google · website · retrieved 2026-10-15

Training corpora

Other declared training data

Benchmark cells

GIFT-Eval

Unknown Jena Weather (GIFT-Eval) · training data not disclosed in enough detail

Unknown BizITObs - Application · training data not disclosed in enough detail

Unknown BizITObs - Service · training data not disclosed in enough detail

Unknown BizITObs - L2C · training data not disclosed in enough detail

Unknown Bitbrains - Fast Storage · training data not disclosed in enough detail

Unknown Bitbrains - rnd · training data not disclosed in enough detail

Unknown Restaurant (Recruit Restaurant Visitor Forecasting) · training data not disclosed in enough detail

Unknown ETT1 (GIFT-Eval) · training data not disclosed in enough detail

Unknown ETT2 (GIFT-Eval) · training data not disclosed in enough detail

Unknown Loop Seattle (LibCity) · training data not disclosed in enough detail

Unknown SZ-Taxi (LibCity) · training data not disclosed in enough detail

Unknown M_DENSE (LibCity) · training data not disclosed in enough detail

Unknown Solar (LSTNet, 137 Alabama PV plants) · training data not disclosed in enough detail

Unknown Hierarchical Sales (Mancuso et al., 2020) · training data not disclosed in enough detail

Unknown M4 Yearly · training data not disclosed in enough detail

Unknown M4 Quarterly · training data not disclosed in enough detail

Unknown M4 Monthly · training data not disclosed in enough detail

Unknown M4 Weekly · training data not disclosed in enough detail

Unknown M4 Daily · training data not disclosed in enough detail

Unknown M4 Hourly · training data not disclosed in enough detail

Unknown Hospital · training data not disclosed in enough detail

Unknown COVID Deaths · training data not disclosed in enough detail

Unknown US Births · training data not disclosed in enough detail

Unknown Saugeen River Flow · training data not disclosed in enough detail

Unknown Temperature Rain · training data not disclosed in enough detail

Unknown KDD Cup 2018 · training data not disclosed in enough detail

Unknown Car Parts · training data not disclosed in enough detail

Unknown ElectricityLoadDiagrams20112014 (UCI) · training data not disclosed in enough detail

Long-horizon forecasting (ETT, Electricity, Traffic, Weather, Exchange, ILI)

Unknown ETTh1 · training data not disclosed in enough detail

Unknown ETTh2 · training data not disclosed in enough detail

Unknown ETTm1 · training data not disclosed in enough detail

Unknown ETTm2 · training data not disclosed in enough detail

Unknown Electricity (ECL, 321 clients) · training data not disclosed in enough detail

Seen, split unclear Traffic (PeMS San Francisco Bay, 862 sensors) · the dataset was used; the source does not say which part (via GIFT-Eval Pretrain (GiftEvalPretrain))

Evidence (2)
“GiftEvalPretrain excluding the datasets that overlap with fev-bench”
huggingface.co · model card · Data · retrieved 2026-10-15
“Traffic Hourly”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15

Unknown Weather (Jena, 2020; Autoformer) · training data not disclosed in enough detail

Unknown Exchange-Rate · training data not disclosed in enough detail

Related data seen ILI (CDC influenza-like illness, national) · related dataset CDC FluView ILINet (LOTSA) was used (via GIFT-Eval Pretrain (GiftEvalPretrain))

Evidence (5)
“GiftEvalPretrain excluding the datasets that overlap with fev-bench”
huggingface.co · model card · Data · retrieved 2026-10-15
“CDC Fluview ILINet”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15
“includes the weekly recorded influenza-like illness (ILI) patients data from Centers for Disease Control and Prevention of the United States between 2002 and 2021”
arxiv.org · paper · Section 4 (Datasets) · retrieved 2026-10-15
“https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html”
arxiv.org · paper · Section 4, footnote 4 · retrieved 2026-10-15
“CDC Fluview ILINet CDC Fluview WHO NREVSS”
arxiv.org · paper · Table 14 (dataset column) · retrieved 2026-10-15

Time-series anomaly detection

Unknown TSB-AD-U (TSB-AD univariate) · training data not disclosed in enough detail

Unknown TSB-AD-M (TSB-AD multivariate) · training data not disclosed in enough detail

Unknown UCR Time Series Anomaly Archive (Hexagon ML/UCR, KDD Cup 2021) · training data not disclosed in enough detail

Unknown Server Machine Dataset (SMD) · training data not disclosed in enough detail

Unknown Mars Science Laboratory (MSL) telemetry anomaly dataset · training data not disclosed in enough detail

Unknown Soil Moisture Active Passive (SMAP) telemetry anomaly dataset · training data not disclosed in enough detail

Unknown Pooled Server Metrics (PSM) · training data not disclosed in enough detail

Unknown Secure Water Treatment (SWaT) · training data not disclosed in enough detail

Unknown Yahoo S5 Labeled Anomaly Detection Dataset (Yahoo Webscope S5) · training data not disclosed in enough detail

Unknown Numenta Anomaly Benchmark (NAB) · training data not disclosed in enough detail

Time-series classification

Unknown UCR Time Series Classification Archive (2018) · training data not disclosed in enough detail

Unknown UEA Multivariate Time Series Classification Archive (2018) · training data not disclosed in enough detail

Notes

Multivariate, 330M params (blog), no paper found. Weights on HF under a non-commercial licence (code and weights up to 2.5 stay Apache-2.0, per README). GIFT-Eval's results config for TimesFM-3 sets "testdata_leakage": "No". The card's citation is still the 1.0 paper. Other stated exclusions, not tracked here: GiftEvalPretrain datasets that overlap with fev-bench (all).

Sources