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MiroMind Research Agent: Fully Open-Source Deep Research Agent with Reproducible State-of-the-Art Performance on FutureX, GAIA, HLE, BrowserComp and xBench.

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MiroFlow

DOCS DEMO MODELS DATA

BLOG GITHUB DISCORD WeChat RedNote

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This repo is the official implementation of the MiroMind Research Agent Project. It is a leading-performance, fully open-source system designed to perform multi-step internet research for addressing complex challenges such as future event prediction. The project currently comprises four key components:

  • πŸ€– MiroFlow: an open-source research agent framework that offers reproducible state-of-the-art performance on representative benchmarks (e.g., FutureX, GAIA, HLE, xBench-DeepSearch, and BrowserComp benchmarks), included in this repo. See [Get Started in Under 5 Minutes] for a quick start.
  • πŸ€” MiroThinker: an open-source agent foundation model that natively supports tool-assisted reasoning. See MiroThinker.
  • πŸ“Š MiroVerse: 147k premium open-source training data supporting research agent training. See MiroVerse.
  • 🚧 MiroTrain / MiroRL: The training infra that supports stable and efficient training for the research agent models. See MiroTrain / MiroRL

πŸ“‹ Table of Contents


πŸ“° News & Updates

  • [2025-09-15]: πŸŽ‰πŸŽ‰ MiroFlow v0.3: Enhanced codebase architecture and significantly improved benchmark performance, boosting GPT-5's prediction accuracy for future events by 11%. MiroFlow now ranks #1 in the future prediction benchmark. See FutureX.
  • [2025-08-27]: MiroFlow v0.2: Achieves state-of-the-art performance across multiple agentic benchmarks, including HLE (27.2%), HLE-Text-Only (29.5%), BrowserComp-EN (33.2%), BrowserComp-ZH (47.1%), and xBench-DeepSearch (72.0%).
  • [2025-08-26]: Released GAIA Validation Trace (73.94% pass@1) and Gradio Demo for local deployment.
  • [2025-08-08]: MiroFlow v0.1: Complete open-source release of the research agent framework.

πŸš€ Get Started in Under 5 Minutes

πŸ“‹ Prerequisites

  • Python: 3.12 or higher
  • Package Manager: uv
  • Operating System: Linux, macOS

⚑ Quick Setup

Example: Intelligent document analysis with file processing capabilities.

# 1. Clone and setup
git clone https://github.com/MiroMindAI/MiroFlow && cd MiroFlow
uv sync

# 2. Configure API key
cp .env.template .env
# Edit .env and add your OPENROUTER_API_KEY

# 3. Run your first agent
uv run main.py trace --config_file_name=agent_quickstart_1 --task="What is the first country listed in the XLSX file that have names starting with Co?" --task_file_name="data/FSI-2023-DOWNLOAD.xlsx"

πŸŽ‰ Expected Output: Your agent should return \boxed{Congo Democratic Republic} 😊

πŸ’‘ Tip: If you encounter issues, check that your API key is correctly set in the .env file and that all dependencies are installed.


πŸ€– What is MiroFlow?

MiroFlow is a high-performance, modular framework for building intelligent AI agents that deliver state-of-the-art results on complex reasoning tasks like future event prediction. The framework features advanced multi-turn conversation capabilities, extensive tool ecosystem integration, and hierarchical sub-agent orchestration for optimal task completion. Learn more about our agent framework.

MiroFlow Architecture
Research Assistant Demo - Read CVPR 2025 Best Paper and Provide Research Advice
Demo-Research-Assistant.mp4

🌟 Highlights

  • Reproducible State-of-the-Art Performance: #1 ranking across multiple representative agentic benchmarks, including FutureX, GAIA, HLE, xBench-DeepSearch, and BrowserComp benchmarks)
  • High Concurrency & Reliability: Built with robust concurrency management and fault-tolerant design, MiroFlow efficiently handles rate-limited APIs and unstable networks, ensuring seamless trajectory collection and reliable execution of complex tasks.
  • Cost-Effective Deployment: Powered by the open-source MiroThinker model, MiroFlow can run a research agent service on a single RTX 4090. The entire stack relies on free, open-source tools, making it simple to deploy, scale, and reproduce. See MiroThinker.

πŸ”§ Supported Models & Tools


πŸ“ˆ Performance on Benchmarks

We achieved the #1 ranking on the FutureX Benchmark Leaderboard as of September 10, 2025, boosting GPT-5's prediction accuracy for future events by 11%.

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We benchmark MiroFlow on a series of benchmarks, including GAIA, HLE, BrowseComp, and xBench-DeepSearch, and achieved SOTA results.

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Model/Framework GAIA Val HLE HLE-Text BrowserComp-EN BrowserComp-ZH xBench-DeepSearch
MiroFlow 82.4% 27.2% 29.5% 33.2% 47.1% 72.0%
OpenAI Deep Research 67.4% 26.6% - 51.5% 42.9% -
Gemini Deep Research - 26.9% - - - 50+%
Kimi Researcher - - 26.9% - - 69.0%
WebSailor-72B 55.4% - - - 30.1% 55.0%
Manus 73.3% - - - - -
DeepSeek v3.1 - - 29.8% - - 71.2%

Follow our detailed guides to reproduce benchmark results in our Benchmarks Documentation


❓ FAQ

What API keys do I need?
You only need an OpenRouter API key to get started. OpenRouter provides access to multiple language models through a single API.
Can I use other language models besides OpenRouter?
Yes, MiroFlow supports various language models. Check our documentation for configuration details.
How do I reproduce the benchmark results?
Follow our detailed Benchmarks Documentation for step-by-step reproduction guides.
Is there commercial support available?
For commercial inquiries and enterprise support, please contact us through our website.

🀝 Contributing

We welcome contributions from the community! Whether you're fixing bugs, adding features, or improving documentation, your help is appreciated.

  • πŸ“‹ Issues: Report bugs or request features via GitHub Issues.
  • πŸ”€ Pull Requests: Submit improvements via pull requests.
  • πŸ’¬ Discussions: Join our Discord community for questions and discussions.

πŸ“„ License

This project is licensed under the Apache License 2.0.

πŸ™ Acknowledgments

Benchmark Contributors for the comprehensive evaluation datasets.

Open Source Community for the tools and libraries that make this possible.

We thank all contributors who have helped make MiroFlow better:

Join our community and help us build the future of AI agents!

References

The technical report is coming soon!

@misc{2025mirothinker,
    title={MiroFlow: A High-Performance Open-Source Research Agent Framework},
    author={MiroMind AI Team},
    howpublished={\url{https://github.com/MiroMindAI/MiroFlow}},
    year={2025}
}

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