# Google Research — TimesFM-3: A zero-shot foundation model for multivariate forecasting

- Company: Google Research (research.google)
- Announced: 2026-08-31T17:19:40+00:00
- Subject: Research
- Source: https://research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/
- Record: https://forck.live/items/7136-timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting

Ayush Jain and Rajat Sen, Research Scientists, Google Research We introduce TimesFM-3, a state-of-the-art time series foundation model that enables highly accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks. Quick links Since the debut of TimesFM in 2024, we’ve seen the adoption of time-series foundation models for real-world time-series forecasting tasks across multiple domains, such as retail, finance, observability, manufacturing, healthcare and natural sciences . Up until TimesFM-2.5 (released in September 2025), our models were strictly limited to univariate forecasting: forecasting using only the history of a single time series. Yet, most real-world forecasting problems are inherently multivariate: where multiple time series and auxiliary external features jointly impact the future forecast of a time series. Consider forecasting ice cream sales for a retail chain. Past sales alone rarely tell the full story. …

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Record: https://forck.live/items/7136-timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting
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