README

TimesFM

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation
model developed by Google Research for time-series forecasting.

   Paper:
    A decoder-only foundation model for time-series forecasting,
    ICML 2024.
   🆕 TimesFM 3.0 Checkpoint:
    google/timesfm-3.0-pytorch. Checkpoints up to 2.5:
    TimesFM Hugging Face Collection.
   Google Reseach blog posts:
     TimesFM-3: A zero-shot foundation model for multivariate forecasting
     A decoder-only foundation model for time-series forecasting   
   TimesFM in Google 1P Products:
       BigQuery ML:
        Enterprise level SQL queries for scalability and reliability.
       Google Sheets:
        For your daily spreadsheet.
       Vertex Model Garden:
        Dockerized endpoint for agentic calling.

This open version is not an officially supported Google product.

Latest Model Version: TimesFM 3.0 ✨

Archived Model Versions:

-   2.5: relevant code under src/timesfm.
-   1.0 and 2.0: relevant code archived in the subdirectory v1. You can pip
    install timesfm==1.3.0 to install an older version of this package to load
    them.

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 Update — September 2026

TimesFM 3.0 finishes rollout in Google Cloud BigQuery ML, supporting commercial and production uses (see clarified license notice).

 Update — August 2026

TimesFM 3.0 is out!

TimesFM 3.0 introduces native multivariate time-series forecasting, flexible
covariate support (both past-only and past-and-future covariates), superior
zero-shot generalist capabilities, and top performance across all three major
time-series foundation model benchmarks.

 Key Highlights:

-   Native Multivariate & Univariate Forecasting with Covariates: Seamlessly
    forecast multi-channel multivariate series as well as individual univariate
    series, with native support for past-only and past-and-future dynamic
    covariates without per-task tuning.
-   Top Benchmark Performance:
    -   🥇 fev-bench: Rank 1 overall across 100 diverse real-world
        forecasting tasks.
    -   🥇 TIME Benchmark: Rank 1 overall across 50 domain datasets and
        98 evaluation tasks.
    -   🥇 GIFT-Eval: Rank 1 among all foundation models.

 License notice for pretrained weights

 Important: The TimesFM source code in this repository is licensed under Apache-2.0, and model weights up to version 2.5 remain Apache-2.0. However, TimesFM 3.0 pretrained weights are distributed under the separate timesfm-non-commercial-license-v1.0 license and are restricted to non-commercial, non-production use. Commercial or production use of downloaded / self-hosted weights is not permitted.

 Commercial & Production Use: Commercial and production use of TimesFM 3.0 is fully permitted through authorized Google Cloud services, including BigQuery ML, which are governed by the Google Cloud Terms of Service.

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Latest release

New model weights and associated code: TimesFM-3.0