> For the complete documentation index, see [llms.txt](https://docs.jua.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.jua.ai/models-and-products/jua-models.md). # Jua Models Jua's proprietary deep-learning models delivering high-resolution global weather forecasts: * **EPT-1.5 and EPT-1.5 Early** - Our core product offerings * **EPT-2 and EPT-2 Early** - Our flagship state-of-the-art models Both model families provide global coverage with four daily runs and a 20-day prediction horizon. **Out now**: Our newest additions to the EPT-2 family * **EPT-2e** is our ensemble model for probabilistic forecasting, ideal for long-term risk hedging strategies * **EPT-2 Reasoning** is our advanced reasoning model based on active learning from live data * **EPT-2 RR** is our rapid refresh forecast model, with our fastest dissemination times and 24 updates per day * **EPT-2 HRRR** is out high-resolution rapid refresh forecast model, with unprecedented detail over Europe ## EPT-2: Our Latest Flagship EPT-2 is our state-of-the-art weather model that outperforms leading public AI weather models including Microsoft Aurora, DeepMind's GraphCast, ECMWF's AIFS, and our previous EPT-1.5 model. Released in April 2024, EPT-2 represents our most advanced forecasting technology yet. * **Full hindcast dataset** available for performance analysis and evaluation * **Enhanced accuracy** across all weather parameters * **Improved resolution** for more precise forecasting --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.jua.ai/models-and-products/jua-models.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.