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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 Olive?

AI should concentrate on its fundamental strengths, and Olive’s AI workforce significantly boosts the efficiency, cost-effectiveness, and personal touch of leading health systems in the nation. Our focus is on enhancing your existing operations, which empowers you to reimagine the future landscape of healthcare. Specifically engineered to tackle the distinct challenges faced in the healthcare sector, Olive smoothly integrates with current administrative frameworks, industry standards such as FHIR and HL7, and a variety of technologies. Rather than complicating existing workflows, Olive simplifies them while ensuring top-notch security tailored for the healthcare environment. Although Olive is not directly involved in patient care, health systems should not be required to become experts in AI technologies. From uncovering automation potentials that yield optimal returns to overseeing and refining the performance of your AI workforce, Olive takes care of every detail. Additionally, the insights gained by one instance of Olive are shared throughout the network, ensuring that hospitals do not repeatedly encounter the same challenges, thus highlighting the significant network effect. This collaborative learning framework not only encourages ongoing enhancement but also propels innovation in healthcare delivery, ultimately benefiting patients and providers alike. As healthcare continues to evolve, the role of AI will become increasingly vital in shaping efficient systems.

Media

Media

Integrations Supported

ExecuTorch
Hugging Face
Microsoft Azure
Microsoft Foundry
Microsoft Foundry Models

Integrations Supported

MSIGHTS

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

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

Not specified

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

Olive

Date Founded

2012

Company Location

United States

Company Website

oliveai.com

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Small Language Models

Not specified

Categories and Features

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