Core Insights - MiroMind ODR (Open Deep Research) is introduced as a powerful open-source deep research model, achieving a GAIA score of 82.4, surpassing other models like OpenAI's Deep Research and Manus [1][4][32] - The project is fully open-source, including its core model, data, training processes, AI infrastructure, and DR agent framework, allowing for reproducibility [3][4][15] - The team plans to maintain a monthly update schedule for open-source contributions, indicating a commitment to continuous improvement and community engagement [4][21] Performance Metrics - MiroMind ODR achieved a GAIA score of 82.4, while OpenAI's Deep Research scored 67.4 and Manus scored 73.3, highlighting MiroMind's superior performance [4][19] - The model MiroThinker, part of the ODR project, has shown state-of-the-art performance with a score of 60.2% on GAIA-Text-103 [19][21] Project Components - MiroMind ODR consists of four sub-projects: MiroFlow (Agent framework), MiroThinker (model), MiroVerse (data), and MiroTrain (training infrastructure), each contributing to the overall functionality and performance of the deep research model [15][21] - MiroFlow supports multiple mainstream tool calls and extends large language models for tool-assisted deep research reasoning [18][21] - MiroVerse provides 147,000 open-source training datasets, focusing on community feedback and continuous updates [21][32] Leadership and Vision - Dai Jifeng, a prominent figure in the project, has a strong academic background and extensive experience in computer vision and deep learning, having published over 80 papers with significant citations [26][30] - The mission of MiroMind is to develop self-aware digital entities that evolve with the community, aiming for safe and beneficial AGI [30][32]

Core Viewpoint - MiroMind ODR (Open Deep Research) is introduced as a powerful open-source deep research model, achieving a GAIA test score of 82.4, surpassing other models like OpenAI's Deep Research and Manus [2][5]. Group 1: Model Performance and Features - MiroMind ODR has the highest performance score of 82.4 in GAIA validation, outperforming models such as OpenAI Deep Research (67.4) and Manus (73.3) [2][5]. - The model is fully open-source and reproducible, with all core components, data, training processes, and frameworks available for public access [4][5]. - The project team plans to maintain a monthly update schedule for open-source contributions, indicating ongoing development and improvement [5]. Group 2: Sub-Projects Overview - MiroMind ODR consists of four sub-projects: MiroFlow (Agent Framework), MiroThinker (Model), MiroVerse (Data), and MiroTrain (Training Infrastructure) [20]. - MiroFlow supports multiple mainstream tool calls and extends large language models, achieving stable reproducibility with a performance score of 82.4 on GAIA [22]. - MiroThinker is a large language model that natively supports tool-assisted reasoning, demonstrating top performance in GAIA [23]. - MiroVerse provides 147,000 open-source training datasets, focusing on community feedback and continuous updates [26]. - MiroTrain supports stable and efficient training for deep research models, covering the entire training process [27]. Group 3: Development Team and Leadership - Dai Jifeng, a prominent figure in the project, has a strong academic background and extensive experience in computer vision and deep learning, with over 80 published papers and more than 60,000 citations [32][36]. - His previous roles include positions at Microsoft Research Asia and SenseTime, and he has returned to academia as an associate professor at Tsinghua University [40][41]. - The project aims to contribute to AGI (Artificial General Intelligence) research, with a mission to create self-aware digital entities that evolve with the community [45][47].