MiroMind

Overview

MiroMind is at the forefront of developing open, honest, and patient Agentic AI, fostering a collaborative environment where developers are partners in creation, not just users. They are building the future of AI together, emphasizing transparency and continuous evolution.

What is MiroMind?

MiroMind is a research and development initiative focused on advancing Agentic AI through open-source contributions. Their mission is to empower developers by providing state-of-the-art models, robust training infrastructure, and flexible agent frameworks. They believe in building AI "with" developers, not "above" them, marking day one of a new era in AI development.

Key Benefits

• Open Collaboration: Engage with a community of developers to build and evolve AI together.
• State-of-the-Art Models: Access and utilize advanced open-source models like MiroThinker that push the boundaries of AI performance.
• Powerful Infrastructure: Leverage MiroTrain and MiroRL for efficient training of long-context SFT/RL models.
• Flexible Agent Framework: Utilize MiroFlow to power sophisticated agent tasks with high reproducibility.
• Rich Datasets: Benefit from MiroVerse, a curated collection of solution traces for agent task development.

Main Features

MiroMind offers a suite of integrated tools and resources:

• MiroThinker: A series of open-source, state-of-the-art Deep Research models that excel on challenging benchmarks like GAIA.
• MiroTrain & MiroRL: Comprehensive training infrastructure designed for developing long-context SFT/RL models with up to 64K context.
• MiroFlow: A cutting-edge agent framework that supports both proprietary models and MiroThinker, achieving high scores in tool-use agent tasks.
• MiroVerse: A valuable dataset comprising high-quality, verified solution traces for a wide array of agent tasks.

Who Should Use It

MiroMind is ideal for:

• AI Researchers: Seeking to leverage and contribute to cutting-edge open-source AI models.
• Software Developers: Looking to integrate advanced AI capabilities into their applications.
• Machine Learning Engineers: Needing robust tools for training and deploying complex AI agents.
• Data Scientists: Working on agent-based tasks and requiring high-performance frameworks and datasets.
• Open Source Enthusiasts: Passionate about collaborative AI development and transparent AI systems.