The MiMo-V2.5 series serves as a flagship architecture specifically engineered for intelligent agent scenarios. Designed to handle both general agentic tasks and highly complex, long-horizon operations, the model excels at professional-grade software engineering and autonomous problem-solving. Its design intent focuses on deep integration with agent frameworks, allowing it to execute intricate workflows that involve over a thousand individual tool calls. By prioritizing native agentic capabilities, the model is built to independently manage tasks that would traditionally require significant human intervention over extended periods.

Developed under the leadership of Luo Fuli, the MiMo-V2.5 lineage emphasizes rapid iteration and high-performance reasoning, drawing on expertise from advanced AI research circles. The model incorporates self-correcting mechanisms that enhance its reliability during complex execution, making it a robust choice for developers building persistent, memory-aware agents. With strong performance across benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, the series is optimized for efficiency and scalability. Future-facing development continues to push the boundaries of agentic autonomy, positioning the model as a versatile tool for modern software development and automated system integration.