IBM Releases SOTA Granite Time Series PatchTST-FM-r2 with Commercial License

IBM Research has published the Granite Time Series PatchTST-FM-r2 model on Hugging Face, claiming state-of-the-art performance on time series forecasting tasks under a commercial-friendly license. The model builds on the PatchTST architecture, using patching and channel-independent transformers to handle diverse temporal data at scale. Developers working in finance, operations, IoT, or any domain requiring forecasting can now deploy a top-tier time series model without the licensing friction typically associated with commercial use. The Hugging Face release makes integration into existing ML pipelines straightforward via the standard transformers ecosystem. This is a meaningful contribution to the open model landscape for a task class that has historically lagged behind NLP and vision in terms of freely available foundation models.