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What is Phi-4-reasoning-plus?

Phi-4-reasoning-plus is an enhanced reasoning model that boasts 14 billion parameters, significantly improving upon the capabilities of the original Phi-4-reasoning. Utilizing reinforcement learning, it achieves greater inference efficiency by processing 1.5 times the number of tokens that its predecessor could manage, leading to enhanced accuracy in its outputs. Impressively, this model surpasses both OpenAI's o1-mini and DeepSeek-R1 on various benchmarks, tackling complex challenges in mathematical reasoning and high-level scientific questions. In a remarkable feat, it even outshines the much larger DeepSeek-R1, which contains 671 billion parameters, in the esteemed AIME 2025 assessment, a key qualifier for the USA Math Olympiad. Additionally, Phi-4-reasoning-plus is readily available on platforms such as Azure AI Foundry and HuggingFace, streamlining access for developers and researchers eager to utilize its advanced features. Its cutting-edge design not only showcases its capabilities but also establishes it as a formidable player in the competitive landscape of reasoning models. This positions Phi-4-reasoning-plus as a preferred choice for users seeking high-performance reasoning solutions.

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

Hugging Face
Claude Code
Microsoft Azure
Microsoft Foundry
Xiaomi MiMo
Xiaomi MiMo Studio

Integrations Supported

Hugging Face
Claude Code
Microsoft Azure
Microsoft Foundry
Xiaomi MiMo
Xiaomi MiMo Studio

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/blog/one-year-of-phi-small-language-models-making-big-leaps-in-ai/

Company Facts

Organization Name

Xiaomi Technology

Date Founded

2010

Company Location

China

Company Website

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

Categories and Features

Categories and Features

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