# Datarus-R1-14B-preview

[![Model](https://img.shields.io/badge/Model-Datarus--R1--14B-blue)](https://huggingface.co/DatarusAI/Datarus-R1-14B-preview) [![License](https://img.shields.io/badge/License-Apache%202.0-green)](LICENSE) [![Website](https://img.shields.io/badge/Website-datarus.ai-orange)](https://datarus.ai) [![Demo](https://img.shields.io/badge/Demo-Try%20Now-purple)](https://chat.datarus.ai) [![Paper](https://img.shields.io/badge/Paper-arXiv-red)](https://arxiv.org/abs/2508.13382)

## 🚀 Overview **Datarus-R1-14B-Preview** is a 14B-parameter open-weights language model fine-tuned from Qwen2.5-14B-Instruct, designed to act as a virtual data analyst and graduate-level problem solver. Unlike traditional models trained on isolated Q&A pairs, Datarus learns from complete analytical trajectories—including reasoning steps, code execution, error traces, self-corrections, and final conclusions—all captured in a ReAct-style notebook format. ### Key Highlights - **🎯 State-of-the-art efficiency**: Surpasses similar-sized models and competes with 32B+ models while using 18-49% fewer tokens - **🔄 Dual reasoning interfaces**: Supports both Agentic (ReAct) mode for interactive analysis and Reflection (CoT) mode for concise documentation - **📊 Superior performance**: Achieves up to 30% higher accuracy on AIME 2024/2025 and LiveCodeBench - **💡 "AHA-moment" pattern**: Exhibits efficient hypothesis refinement in 1-2 iterations, avoiding circular reasoning loops ## 🔗 Quick Links - 🌐 **Website**: [https://datarus.ai](https://datarus.ai) - 💬 **Try the Demo**: [https://chat.datarus.ai](https://chat.datarus.ai) - 🛠️ **Jupyter Agent**: [GitHub Repository](https://github.com/DatarusAI/Datarus-JupyterAgent) - 📄 **Paper**: [Datarus-R1: An Adaptive Multi-Step Reasoning LLM](https://arxiv.org/abs/2508.13382) ## 📊 Performance ### Benchmark Results | Benchmark | Datarus-R1-14B-Preview | QwQ-32B | Phi-4-reasoning | DeepSeek-R1-Distill-14B | |-----------|----------------|---------|-----------------|-------------------------| | **LiveCodeBench v6** | 57.7 | 56.6 | 52.6 | 48.6 | | **AIME 2024** | 70.1 | 76.2 | 74.6* | - | | **AIME 2025** | 66.2 | 66.2 | 63.1* | - | | **GPQA Diamond** | 62.1 | 60.1 | 55.0 | 58.6 | *Reported values from official papers ### Token Efficiency and Performance

## 🎯 Model Card ### Model Details - **Model Type**: Language Model for Reasoning and Data Analysis - **Parameters**: 14.8B - **Training Data**: 144,000 synthetic analytical trajectories across finance, medicine, numerical analysis, and other quantitative domains + A curated collection of reasoning datasets. - **Language**: English - **License**: Apache 2.0 ### Intended Use #### Primary Use Cases - **Data Analysis**: Automated data exploration, statistical analysis, and visualization - **Mathematical Problem Solving**: Graduate-level mathematics including AIME-level problems - **Code Generation**: Creating analytical scripts and solving programming challenges - **Scientific Reasoning**: Complex problem-solving in physics, chemistry, and other sciences - **Interactive Notebooks**: Building complete analysis notebooks with iterative refinement ### Dual Mode Usage #### Agentic Mode (for interactive analysis) - Use ``, ``, ``, ``, `` tags - Enables iterative code execution and refinement - Best for data analysis, simulations, and exploratory tasks #### Reflection Mode (for documentation) - Use `` and `` tags - Produces compact, self-contained reasoning chains - Best for mathematical proofs, explanations, and reports ## 📚 Citation ```bibtex @article{benchaliah2025datarus, title={Datarus-R1: An Adaptive Multi-Step Reasoning LLM for Automated Data Analysis}, author={Ben Chaliah, Ayoub and Dellagi, Hela}, journal={arXiv preprint arXiv:2508.13382}, year={2025} } ``` ## 🤝 Contributing We welcome contributions! Please see our [GitHub repository](https://github.com/DatarusAI/Datarus-JupyterAgent) for: - Bug reports and feature requests - Pull requests - Discussion forums ## 📄 License This model is released under the Apache 2.0 License. ## 🙏 Acknowledgments We thank the Qwen team for the excellent base model and the open-source community for their valuable contributions. ## 📧 Contact - **Email**: ayoub1benchaliah@gmail.com, hela.dellagi@outlook.com - **Website**: [https://datarus.ai](https://datarus.ai) - **Demo**: [https://chat.datarus.ai](https://chat.datarus.ai) ---

Experience the future of AI-powered data analysis with Datarus-R1 [Try Demo](https://chat.datarus.ai) | [View Code](https://github.com/DatarusAI/Datarus-JupyterAgent) | [Read Paper](https://arxiv.org/abs/2508.13382)

## ⭐ Support If you find this model and Agent pipeline useful, please consider __Like/Star__! Your support helps us continue improving the project. Found a bug or have a feature request? Please open an issue on GitHub. ---

Made with ❤️ by the Datarus Team from Paris