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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Phi-4-reasoning is an advanced transformer model featuring 14 billion parameters, specifically tailored for tackling intricate reasoning challenges, including mathematics, programming, algorithm development, and strategic planning. Through a meticulous process of supervised fine-tuning on select "teachable" prompts and reasoning examples created using o3-mini, it excels at generating thorough reasoning sequences that optimize computational resources during inference. By integrating outcome-driven reinforcement learning, Phi-4-reasoning is capable of producing extended reasoning paths. Its performance notably surpasses that of significantly larger open-weight models like DeepSeek-R1-Distill-Llama-70B and nears the capabilities of the comprehensive DeepSeek-R1 model across various reasoning applications. Designed for use in settings with limited computing power or high latency, Phi-4-reasoning is fine-tuned with synthetic data provided by DeepSeek-R1, ensuring it delivers precise and methodical problem-solving. This model's ability to handle complex tasks with efficiency makes it a valuable tool in numerous computational contexts.

Description

Tiny Aya represents a collection of open-weight multilingual language models developed by Cohere Labs, aimed at providing robust and flexible AI capabilities that function seamlessly on local devices such as smartphones and laptops, all without the need for continuous cloud access. This innovative model is dedicated to facilitating superior text comprehension and generation in over 70 languages, notably including numerous lower-resource languages that typically receive less attention from conventional models. Engineered with lightweight structures comprising around 3.35 billion parameters, Tiny Aya has been fine-tuned for optimal multilingual representation and practical computational efficiency, making it ideal for deployment in edge environments and offline scenarios. Furthermore, the models are designed to support downstream adaptation and instruction tuning, enabling developers to tailor the models’ behaviors for specific use cases while ensuring strong performance across languages. As a result, Tiny Aya not only enhances access to advanced AI solutions but also empowers developers to create customized applications that meet diverse linguistic needs.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hugging Face
Microsoft Azure
Microsoft Foundry
Microsoft Foundry Models

Integrations

Hugging Face
Microsoft Azure
Microsoft Foundry
Microsoft Foundry Models

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

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

Vendor Details

Company Name

Cohere AI

Founded

2019

Country

Canada

Website

cohere.com/blog/cohere-labs-tiny-aya

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