This Time Is Different: An Observability Perspective on Time Series Foundation Models
Abstract
We introduce Toto, a time series forecasting foundation model with 151 million parameters. Toto uses a modern decoder-only architecture coupled with architectural innovations designed to account for specific challenges found in multivariate observability time series data. Toto's pre-training corpus is a mixture of observability data, open datasets, and synthetic data, and is 4-10$\times$ larger than those of leading time series foundation models. Additionally, we introduce BOOM, a large-scale benchmark consisting of 350 million observations across 2,807 real-world time series. For both Toto and BOOM, we source observability data exclusively from our own telemetry and internal observability metrics. Extensive evaluations demonstrate that Toto achieves state-of-the-art performance on both BOOM and on established general purpose time series forecasting benchmarks. Toto's model weights, inference code, and evaluation scripts, as well as BOOM's data and evaluation code, are all available as open source under the Apache 2.0 License.
Cite
Text
Cohen et al. "This Time Is Different: An Observability Perspective on Time Series Foundation Models." Advances in Neural Information Processing Systems, 2025.Markdown
[Cohen et al. "This Time Is Different: An Observability Perspective on Time Series Foundation Models." Advances in Neural Information Processing Systems, 2025.](https://mlanthology.org/neurips/2025/cohen2025neurips-time/)BibTeX
@inproceedings{cohen2025neurips-time,
title = {{This Time Is Different: An Observability Perspective on Time Series Foundation Models}},
author = {Cohen, Ben and Khwaja, Emaad and Doubli, Youssef and Lemaachi, Salahidine and Lettieri, Chris and Masson, Charles and Miccinilli, Hugo and Ramé, Elise and Ren, Qiqi and Rostamizadeh, Afshin and du Terrail, Jean Ogier and Toon, Anna-Monica and Wang, Kan and Xie, Stephan and Xu, Zongzhe and Zhukova, Viktoriya and Asker, David and Talwalkar, Ameet and Abou-Amal, Othmane},
booktitle = {Advances in Neural Information Processing Systems},
year = {2025},
url = {https://mlanthology.org/neurips/2025/cohen2025neurips-time/}
}