Google AI has unveiled TimesFM-3, a 330 million parameter foundation model designed for multivariate time series forecasting. Unlike its predecessors, which were limited to univariate predictions, TimesFM-3 can jointly forecast multiple related time series and incorporate past and future external factors without task-specific fine-tuning. The model achieves state-of-the-art performance across several benchmarks, including GIFT-Eval and the TIME leaderboard, by utilizing a novel architecture with alternating causal temporal and full variate attention mechanisms. While the code is available under an Apache-2.0 license, the model weights are restricted to non-commercial, non-production use. AI
IMPACT Enhances multivariate time series forecasting capabilities, potentially improving accuracy in domains like retail, finance, and healthcare.
RANK_REASON Research paper and model release from a major AI lab.
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- Ayush Jain
- Google AI
- Google Research
- Rajat Sen
- TimesFM
- TimesFM-2.5
- TimesFM-3
- fev-bench
- GIFT-Eval
- TIME leaderboard
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