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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.

Description

The MiniMax‑M1 model, introduced by MiniMax AI and licensed under Apache 2.0, represents a significant advancement in hybrid-attention reasoning architecture. With an extraordinary capacity for handling a 1 million-token context window and generating outputs of up to 80,000 tokens, it facilitates in-depth analysis of lengthy texts. Utilizing a cutting-edge CISPO algorithm, MiniMax‑M1 was trained through extensive reinforcement learning, achieving completion on 512 H800 GPUs in approximately three weeks. This model sets a new benchmark in performance across various domains, including mathematics, programming, software development, tool utilization, and understanding of long contexts, either matching or surpassing the capabilities of leading models in the field. Additionally, users can choose between two distinct variants of the model, each with a thinking budget of either 40K or 80K, and access the model's weights and deployment instructions on platforms like GitHub and Hugging Face. Such features make MiniMax‑M1 a versatile tool for developers and researchers alike.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hugging Face Yes 
AI-FLOW Yes 
AlphaCorp Yes 
Amazon Bedrock Yes 
Anuma No 
Deep Infra Yes 
Echo AI Yes 
Fleak Yes 
GMTech Yes 
Graydient AI Yes 
HumanLayer Yes 
LM-Kit.NET Yes 
Mammouth AI Yes 
Microsoft Foundry Agent Service Yes 
Ministral 3B Yes 
Mirascope Yes 
PromptPal Yes 
Toolmark Yes 
bolt.diy Yes 
promptmate.io Yes 

Integrations

Hugging Face Yes 
AI-FLOW No 
AlphaCorp No 
Amazon Bedrock No 
Anuma Yes 
Deep Infra No 
Echo AI No 
Fleak No 
GMTech No 
Graydient AI No 
HumanLayer No 
LM-Kit.NET No 
Mammouth AI No 
Microsoft Foundry Agent Service No 
Ministral 3B No 
Mirascope No 
PromptPal No 
Toolmark No 
bolt.diy No 
promptmate.io No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version 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 

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) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
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

Mistral AI

Founded

2023

Country

France

Website

mistral.ai/news/mathstral/

Vendor Details

Company Name

MiniMax

Founded

2021

Country

Singapore

Website

www.minimax.io/news/minimaxm1

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