Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives

arXiv:2610.11734 · cs.LG, cs.AI · Submitted 2026-10-08 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-10-08

Updated: 2026-10-08

Code: https://github.com/google-research/timesfm

Terminology

• Foundation Model — 1× in this paper · explained in 3 episodes

Sources

• GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
• Chronos: Learning the Language of Time Series
• Chronos-2: From Univariate to Universal Forecasting
• TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
• A decoder-only foundation model for time-series forecasting
• ForecastPFN: Synthetically-Trained Zero-Shot Forecasting
• TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
• Toto 2.0: Time Series Forecasting Enters the Scaling Era
• Compositional Visual Generation with Composable Diffusion Models
• Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
• Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
• Sundial: A Family of Highly Capable Time Series Foundation Models
• Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling
• TabDPT: Scaling Tabular Foundation Models on Real Data
• TiRex-2: Generalizing TiRex to Multivariate Data and Streaming
• It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
• TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
• fev-bench: A Realistic Benchmark for Time Series Forecasting
• Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models
• Unified Training of Universal Time Series Forecasting Transformers

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