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What is Syn?

Syn is an advanced Japanese large language model, developed through a collaboration between Upstage and Karakuri, featuring nearly 14 billion parameters and specifically designed for enterprise use in various fields such as finance, manufacturing, legal, and healthcare. It excels in benchmark evaluations on the Weights & Biases Nejumi Leaderboard, demonstrating top-tier performance in accuracy and alignment while maintaining cost-effectiveness through its efficient architecture, which draws inspiration from Solar Mini. Furthermore, Syn showcases outstanding capabilities in Japanese "truthfulness" and safety, skillfully understanding intricate expressions and specialized jargon relevant to different industries. Its flexible fine-tuning options allow for the seamless integration of proprietary data and domain knowledge. Built for widespread deployment, Syn is versatile enough to operate in on-premises environments, AWS Marketplace, and cloud infrastructures, reinforced by strong security and compliance protocols tailored to meet enterprise demands. Impressively, by leveraging AWS Trainium, Syn can reduce training costs by approximately 50 percent compared to traditional GPU setups, enabling rapid customization for a variety of applications. This cutting-edge model not only boosts operational efficiency but also opens doors to more agile and responsive solutions for enterprises, ultimately transforming how businesses approach their challenges. Enhancing productivity and innovation, Syn positions itself as a vital tool for organizations looking to thrive in an increasingly competitive landscape.

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.

Media

Media

Integrations Supported

AWS Marketplace
AWS Trainium
Amazon Web Services (AWS)
Solar Mini
Upstage AI

Integrations Supported

ExecuTorch
Hugging Face
Microsoft Azure
Microsoft Foundry
Microsoft Foundry Models

API Availability

API Availability

Has API

Pricing Information

$0.1 per 1M tokens

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard 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

Upstage AI

Date Founded

2020

Company Location

United States

Company Website

www.upstage.ai/news/introducing-upstage-japan

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/

Categories and Features

AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Small Language Models

Not specified

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