Best Large Language Models for Xiaomi MiMo

MiMo-V2-Flash is a large language model created by Xiaomi that utilizes a Mixture-of-Experts (MoE) framework, combining remarkable performance with efficient inference capabilities. With a total of 309 billion parameters, it activates just 15 billion parameters during each inference, allowing it to effectively balance reasoning quality and computational efficiency. This model is well-suited for handling lengthy contexts, making it ideal for tasks such as long-document comprehension, code generation, and multi-step workflows. Its hybrid attention mechanism integrates both sliding-window and global attention layers, which helps to minimize memory consumption while preserving the ability to understand long-range dependencies. Additionally, the Multi-Token Prediction (MTP) design enhances inference speed by enabling the simultaneous processing of batches of tokens. MiMo-V2-Flash boasts impressive generation rates of up to approximately 150 tokens per second and is specifically optimized for applications that demand continuous reasoning and multi-turn interactions. The innovative architecture of this model reflects a significant advancement in the field of language processing.

Xiaomi MiMo-V2-Pro is an advanced AI foundation model engineered to support real-world agentic workloads and complex workflow orchestration. It serves as the central intelligence for agent systems, enabling seamless coordination of coding, search, and multi-step task execution. The model is built on a large-scale architecture with over a trillion parameters, supporting extended context lengths for handling complex scenarios. It demonstrates strong benchmark performance, particularly in coding and agent-based evaluations, placing it among top-tier global models. MiMo-V2-Pro is optimized for real-world usability, focusing on reliability, efficiency, and practical task completion rather than just theoretical performance. It features improved tool-calling accuracy and stability, making it suitable for integration into production environments. The model also excels in software engineering tasks, offering structured reasoning and high-quality code generation. With its ability to handle long-context interactions, it supports advanced workflows across development and automation use cases. Its API accessibility and competitive pricing make it attractive for developers and enterprises. Overall, MiMo-V2-Pro delivers a balance of scale, intelligence, and real-world performance for modern AI applications.

Xiaomi MiMo-V2.5-Pro is a next-generation open-source AI model designed for advanced reasoning, coding, and long-horizon task execution. It uses a Mixture-of-Experts architecture with over one trillion parameters and a large active parameter set for efficient performance. The model supports an extended context window of up to one million tokens, allowing it to handle complex, multi-step workflows. It is built to perform autonomous tasks, including software development, system design, and engineering optimization. Benchmark results show strong performance across coding, reasoning, and agent-based evaluation tests. MiMo-V2.5-Pro incorporates hybrid attention mechanisms to improve efficiency while maintaining accuracy across long contexts. It is optimized for token efficiency, reducing the computational cost of running complex tasks. The model can integrate with development tools and frameworks to support real-world applications. It is designed to complete tasks that would typically require significant human effort over extended periods. Xiaomi has made the model open source, enabling developers to access and customize it. By combining performance, scalability, and efficiency, MiMo-V2.5-Pro pushes the boundaries of modern AI capabilities.

Xiaomi MiMo-V2.5 is a next-generation open-source AI model that combines agentic intelligence with multimodal capabilities. It is designed to process and understand text, images, and audio within a single architecture. The model uses a sparse Mixture-of-Experts framework with a large parameter count to deliver efficient and scalable performance. It supports a context window of up to one million tokens, allowing it to handle long and complex workflows. MiMo-V2.5 integrates visual and audio encoders to improve perception and cross-modal reasoning. It is capable of performing tasks such as coding, reasoning, and multimodal analysis with strong accuracy. Benchmark results show competitive performance compared to leading AI models in both agentic and multimodal tasks. The model is optimized for token efficiency, balancing performance with lower computational cost. It is designed for real-world applications that require both reasoning and perception. Xiaomi has open-sourced the model, making it accessible for developers and researchers. By combining multimodality, scalability, and efficiency, MiMo-V2.5 pushes forward the development of advanced AI systems.

MiMo-V2-Omni is a powerful multimodal AI model engineered to process and understand multiple types of data, including text, code, and structured inputs, within a unified system. It is designed to power agent-based workflows, enabling the execution of complex, multi-step tasks with improved accuracy and efficiency. The model combines advanced reasoning capabilities with strong tool integration, allowing it to interact with external systems and automate workflows effectively. It supports a wide range of applications, from software development and data analysis to enterprise automation and research tasks. With enhanced contextual understanding, it can maintain coherence across long interactions and complex scenarios. MiMo-V2-Omni is optimized for real-world performance, ensuring reliability in practical use cases rather than just benchmark results. Its architecture enables efficient handling of large-scale tasks while maintaining speed and responsiveness. The model also supports seamless integration into existing platforms and workflows. By combining multimodal understanding with agentic execution, it provides a flexible and scalable solution for modern AI applications. Overall, it delivers a balance of intelligence, versatility, and efficiency for diverse use cases.