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Description

K2 Think represents a groundbreaking open-source advanced reasoning model that has been developed in collaboration between the Institute of Foundation Models at MBZUAI and G42. Even with its relatively modest 32 billion parameters, K2 Think achieves performance that rivals that of leading models with significantly larger parameter counts. Its strength lies in mathematical reasoning, where it has secured top rankings on prestigious benchmarks such as AIME ’24/’25, HMMT ’25, and OMNI-Math-HARD. This model is part of a wider initiative of UAE-developed open models, which includes Jais (for Arabic), NANDA (for Hindi), and SHERKALA (for Kazakh), and it builds upon the groundwork established by the K2-65B, a fully reproducible open-source foundation model released in 2024. K2 Think is crafted to be open, efficient, and adaptable, featuring a web app interface that facilitates user exploration, and its innovative approach to parameter positioning marks a significant advancement in the realm of compact architectures for high-level AI reasoning. Additionally, its development highlights a commitment to enhancing access to state-of-the-art AI technologies in various languages and domains.

Description

In honor of Archimedes, whose 2311th anniversary we celebrate this year, we are excited to introduce our inaugural Mathstral model, a specialized 7B architecture tailored for mathematical reasoning and scientific exploration. This model features a 32k context window and is released under the Apache 2.0 license. Our intention behind contributing Mathstral to the scientific community is to enhance the pursuit of solving advanced mathematical challenges that necessitate intricate, multi-step logical reasoning. The launch of Mathstral is part of our wider initiative to support academic endeavors, developed in conjunction with Project Numina. Much like Isaac Newton during his era, Mathstral builds upon the foundation laid by Mistral 7B, focusing on STEM disciplines. It demonstrates top-tier reasoning capabilities within its category, achieving remarkable results on various industry-standard benchmarks. Notably, it scores 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, showcasing the performance differences by subject between Mathstral 7B and its predecessor, Mistral 7B, further emphasizing the advancements made in mathematical modeling. This initiative aims to foster innovation and collaboration within the mathematical community.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Airtrain No 
Arize Phoenix No 
Codestral Mamba No 
DataChain No 
Deep Infra No 
Diaflow No 
Expanse No 
GaiaNet No 
Literal AI No 
Ministral 3B No 
Mistral Large No 
Nutanix Enterprise AI No 
PI Prompts No 
Ragas No 
SydeLabs No 
Verta No 
WebLLM No 
Wordware No 
bolt.diy No 

Integrations

Airtrain Yes 
Arize Phoenix Yes 
Codestral Mamba Yes 
DataChain Yes 
Deep Infra Yes 
Diaflow Yes 
Expanse Yes 
GaiaNet Yes 
Literal AI Yes 
Ministral 3B Yes 
Mistral Large Yes 
Nutanix Enterprise AI Yes 
PI Prompts Yes 
Ragas Yes 
SydeLabs Yes 
Verta Yes 
WebLLM Yes 
Wordware Yes 
bolt.diy Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Institute of Foundation Models

Country

United States

Website

www.k2think.ai/k2think

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

mistral.ai/news/mathstral/

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