Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • TrustInSoft Analyzer Reviews & Ratings
    4.3 out of 5 stars 6 Ratings
    Company Website for TrustInSoft Analyzer
  • Evertune Reviews & Ratings
    5.0 out of 5 stars 1 Rating
    Company Website for Evertune
  • RetailEdge Reviews & Ratings
    4.8 out of 5 stars 201 Ratings
    Company Website for RetailEdge
  • Buildium Reviews & Ratings
    4.5 out of 5 stars 2,563 Ratings
    Company Website for Buildium
  • RaimaDB Reviews & Ratings
    4.8 out of 5 stars 12 Ratings
    Company Website for RaimaDB
  • ARGOS Identity Reviews & Ratings
    4.9 out of 5 stars 8 Ratings
    Company Website for ARGOS Identity
  • AthenaHQ Reviews & Ratings
    4.9 out of 5 stars 41 Ratings
    Company Website for AthenaHQ
  • Dialpad Support Reviews & Ratings
    4.4 out of 5 stars 1,629 Ratings
    Company Website for Dialpad Support
  • Runpod Reviews & Ratings
    4.2 out of 5 stars 230 Ratings
    Company Website for Runpod
  • ONLYOFFICE Docs Reviews & Ratings
    4.6 out of 5 stars 715 Ratings
    Company Website for ONLYOFFICE Docs

What is Phi-4-mini-reasoning?

Phi-4-mini-reasoning is an advanced transformer-based language model that boasts 3.8 billion parameters, tailored specifically for superior performance in mathematical reasoning and systematic problem-solving, especially in scenarios with limited computational resources and low latency. The model's optimization is achieved through fine-tuning with synthetic data generated by the DeepSeek-R1 model, which effectively balances performance and intricate reasoning skills. Having been trained on a diverse set of over one million math problems that vary from middle school level to Ph.D. complexity, Phi-4-mini-reasoning outperforms its foundational model by generating extensive sentences across numerous evaluations and surpasses larger models like OpenThinker-7B, Llama-3.2-3B-instruct, and DeepSeek-R1 in various tasks. Additionally, it features a 128K-token context window and supports function calling, which ensures smooth integration with different external tools and APIs. This model can also be quantized using the Microsoft Olive or Apple MLX Framework, making it deployable on a wide range of edge devices such as IoT devices, laptops, and smartphones. Furthermore, its design not only enhances accessibility for users but also opens up new avenues for innovative applications in the realm of mathematics, potentially revolutionizing how such problems are approached and solved.

What is MiniMax M1?

The MiniMax‑M1 model, created by MiniMax AI and available under the Apache 2.0 license, marks a remarkable leap forward in hybrid-attention reasoning architecture. It boasts an impressive ability to manage a context window of 1 million tokens and can produce outputs of up to 80,000 tokens, which allows for thorough examination of extended texts. Employing an advanced CISPO algorithm, the MiniMax‑M1 underwent an extensive reinforcement learning training process, utilizing 512 H800 GPUs over a span of about three weeks. This model establishes a new standard in performance across multiple disciplines, such as mathematics, programming, software development, tool utilization, and comprehension of lengthy contexts, frequently equaling or exceeding the capabilities of top-tier models currently available. Furthermore, users have the option to select between two different variants of the model, each featuring a thinking budget of either 40K or 80K tokens, while also finding the model's weights and deployment guidelines accessible on platforms such as GitHub and Hugging Face. Such diverse functionalities render MiniMax‑M1 an invaluable asset for both developers and researchers, enhancing their ability to tackle complex tasks effectively. Ultimately, this innovative model not only elevates the standards of AI-driven text analysis but also encourages further exploration and experimentation in the realm of artificial intelligence.

Media

Media

Integrations Supported

Hugging Face
ExecuTorch
Microsoft Azure
Microsoft Foundry
Microsoft Foundry Models

Integrations Supported

Hugging Face
Anuma
GitHub
SiliconFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

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

MiniMax

Date Founded

2021

Company Location

Singapore

Company Website

www.minimax.io/news/minimaxm1

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Popular Alternatives

Phi-4-reasoning Reviews & Ratings

Phi-4-reasoning

Microsoft

Popular Alternatives

MiniMax M3 Reviews & Ratings

MiniMax M3

MiniMax
5.0 out of 5 stars
MiniMax M3.1 Flash Reviews & Ratings

MiniMax M3.1 Flash

MiniMax
5.0 out of 5 stars
DeepSeek-V3.2 Reviews & Ratings

DeepSeek-V3.2

DeepSeek