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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.

What is Beam?

Beam marks the launch of Reflection’s first open-weight model, distinguished by its sparse Mixture-of-Experts architecture, which boasts an impressive 501 billion parameters, with 23 billion actively engaged, specifically designed for tasks related to coding, reasoning, and agentic functions. This model's capabilities stem from rigorous pretraining and reinforcement learning, built upon a massive dataset of 23.8 trillion diverse, high-quality tokens obtained from various sources, including the internet, public domains, and proprietary licenses. By focusing on optimizing coding and agentic functionalities, Beam aims to deliver competitive performance in the open-weight space while prioritizing efficient inference computation. It is proficient in managing a diverse range of tasks, such as complex software development, terminal commands, STEM-related activities, web searches, tool application, and general knowledge queries. Utilizing reinforcement learning methods enhances its proficiency in multi-step reasoning, effective tool use, and adaptability to environmental cues. Furthermore, users can customize the model's output by adjusting a reasoning effort parameter, allowing for a tailored balance between efficiency and performance to meet their individual requirements. In essence, Beam is not only a technological advancement but also a versatile tool that empowers users to navigate complex tasks with precision.

Media

Media

Integrations Supported

Claude Code
Hugging Face
Xiaomi MiMo
Xiaomi MiMo Studio

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Xiaomi Technology

Date Founded

2010

Company Location

China

Company Website

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

Company Facts

Organization Name

Reflection

Company Location

United States

Company Website

reflection.ai/blog/introducing-beam

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

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