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What is Mistral Saba?

Mistral Saba is a sophisticated model featuring 24 billion parameters, developed from meticulously curated datasets originating from the Middle East and South Asia. It surpasses the performance of larger models—those exceeding five times its parameter count—by providing accurate and relevant responses while being remarkably faster and more economical. Moreover, it acts as a solid foundation for the development of highly tailored regional applications. Users can access this model via an API, and it can also be deployed locally, addressing specific security needs of customers. Like the newly launched Mistral Small 3, it is designed to be lightweight enough for operation on single-GPU systems, achieving impressive response rates of over 150 tokens per second. Mistral Saba embodies the rich cultural interconnections between the Middle East and South Asia, offering support for Arabic as well as a variety of Indian languages, with particular expertise in South Indian dialects such as Tamil. This broad linguistic capability enhances its flexibility for multinational use in these interconnected regions. Furthermore, the architecture of the model promotes seamless integration into a wide array of platforms, significantly improving its applicability across various sectors and ensuring that it meets the diverse needs of its users.

What is Mathstral?

This year marks the 2311th anniversary of Archimedes, and in his honor, we are thrilled to unveil our first Mathstral model, a dedicated 7B architecture crafted specifically for mathematical reasoning and scientific inquiry. With a context window of 32k, this model is made available under the Apache 2.0 license. Our goal in sharing Mathstral with the scientific community is to facilitate the tackling of complex mathematical problems that require sophisticated, multi-step logical reasoning. The introduction of Mathstral aligns with our broader initiative to bolster academic efforts, developed alongside Project Numina. Much like Isaac Newton's contributions during his lifetime, Mathstral builds upon the groundwork established by Mistral 7B, with a keen focus on STEM fields. It showcases exceptional reasoning abilities within its domain, achieving impressive results across numerous industry-standard benchmarks. Specifically, it registers a score of 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, highlighting the performance enhancements in comparison to its predecessor, Mistral 7B, and underscoring the strides made in mathematical modeling. In addition to advancing individual research, this initiative seeks to inspire greater innovation and foster collaboration within the mathematical community as a whole.

Media

Media

Integrations Supported

Mistral AI
StackAI

Integrations Supported

Mistral AI
1min.AI
APIPark
AlphaCorp
DataChain
Deep Infra
Echo AI
HumanLayer
Klee
LibreChat
Literal AI
Ministral 3B
Mistral 7B
Mistral Large
Mixtral 8x22B
Msty
Noma
bolt.diy
promptmate.io

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mistral-saba

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mathstral/

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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