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What is Xiaomi MiMo Desktop?

The Xiaomi MiMo Desktop represents a groundbreaking application that leverages artificial intelligence to streamline complex workflows across multiple domains, including presentations, documents, spreadsheets, scheduling, file management, programming, and research. Its sophisticated scheduling capability assesses the characteristics, complexity, and resource demands of tasks to identify the optimal execution strategy, effectively routing work to suitable frameworks for office-related tasks, coding endeavors, or research activities while intelligently selecting the appropriate models and tools required. Users can break down intricate projects into manageable subtasks, which can be tackled simultaneously by various agents, all while enjoying full transparency of progress from initiation to completion, supported by a Self-Evolve engine that persistently refines the application's codebase. Moreover, the application simplifies the process of providing context by allowing users to drag and drop files, enabling them to create a wide array of outputs such as slides, web pages, 3D models, and applications, which can be actively utilized and interacted with in real-time within the session or preview interface. In addition to these features, the application offers the capability to target specific local areas for focused edits, perform bulk changes, and utilize version rollback options, ensuring that users can make precise adjustments to their work without the need to regenerate all content. As Xiaomi MiMo Desktop continues to evolve and improve its capabilities, it stands out as an invaluable resource for boosting productivity and effectiveness across diverse professional settings, making it a go-to solution for users seeking to enhance their workflow.

What is MiMo-V2-Flash?

MiMo-V2-Flash is an advanced language model developed by Xiaomi that employs a Mixture-of-Experts (MoE) architecture, achieving a remarkable synergy between high performance and efficient inference. With an extensive 309 billion parameters, it activates only 15 billion during each inference, striking a balance between reasoning capabilities and computational efficiency. This model excels at processing lengthy contexts, making it particularly effective for tasks like long-document analysis, code generation, and complex workflows. Its unique hybrid attention mechanism combines sliding-window and global attention layers, which reduces memory usage while maintaining the capacity to grasp long-range dependencies. Moreover, the Multi-Token Prediction (MTP) feature significantly boosts inference speed by allowing multiple tokens to be processed in parallel. With the ability to generate around 150 tokens per second, MiMo-V2-Flash is specifically designed for scenarios requiring ongoing reasoning and multi-turn exchanges. The cutting-edge architecture of this model marks a noteworthy leap forward in language processing technology, demonstrating its potential applications across various domains. As such, it stands out as a formidable tool for developers and researchers alike.

Media

Media

Integrations Supported

Xiaomi MiMo
MiMo-V2.6-Flash
MiMo-V2.6-Pro

Integrations Supported

Xiaomi MiMo
Claude Code
Hugging Face
Xiaomi MiMo Studio

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

Windows
Mac

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Xiaomi Technology

Date Founded

2010

Company Location

China

Company Website

mimo-ai.xiaomimimo.com/desktop/

Company Facts

Organization Name

Xiaomi Technology

Date Founded

2010

Company Location

China

Company Website

mimo.xiaomi.com/blog/mimo-v2-flash

Categories and Features

AI Agents

Not specified

AI Tools

Not specified

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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