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What is Ministral 3?

Mistral 3 marks the latest development in the realm of open-weight AI models created by Mistral AI, featuring a wide array of options ranging from small, edge-optimized variants to a prominent large-scale multimodal model. Among this selection are three streamlined “Ministral 3” models, equipped with 3 billion, 8 billion, and 14 billion parameters, specifically designed for use on resource-constrained devices like laptops, drones, and various edge devices. In addition, the powerful “Mistral Large 3” serves as a sparse mixture-of-experts model, featuring an impressive total of 675 billion parameters, with 41 billion actively utilized. These models are adept at managing multimodal and multilingual tasks, excelling in areas such as text analysis and image understanding, and have demonstrated remarkable capabilities in responding to general inquiries, handling multilingual conversations, and processing multimodal inputs. Moreover, both the base and instruction-tuned variants are offered under the Apache 2.0 license, which promotes significant customization and integration into a range of enterprise and open-source projects. This approach not only enhances flexibility in usage but also sparks innovation and fosters collaboration among developers and organizations, ultimately driving advancements in AI technology.

What is Beam?

Beam marks the launch of Reflection’s first open-weight model, distinguished by its sparse Mixture-of-Experts architecture, which boasts an impressive 501 billion parameters, with 23 billion actively engaged, specifically designed for tasks related to coding, reasoning, and agentic functions. This model's capabilities stem from rigorous pretraining and reinforcement learning, built upon a massive dataset of 23.8 trillion diverse, high-quality tokens obtained from various sources, including the internet, public domains, and proprietary licenses. By focusing on optimizing coding and agentic functionalities, Beam aims to deliver competitive performance in the open-weight space while prioritizing efficient inference computation. It is proficient in managing a diverse range of tasks, such as complex software development, terminal commands, STEM-related activities, web searches, tool application, and general knowledge queries. Utilizing reinforcement learning methods enhances its proficiency in multi-step reasoning, effective tool use, and adaptability to environmental cues. Furthermore, users can customize the model's output by adjusting a reasoning effort parameter, allowing for a tailored balance between efficiency and performance to meet their individual requirements. In essence, Beam is not only a technological advancement but also a versatile tool that empowers users to navigate complex tasks with precision.

Media

Media

Integrations Supported

NexaSDK
Oxlo.ai

Integrations Supported

API Availability

API Availability

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mistral-3

Company Facts

Organization Name

Reflection

Company Location

United States

Company Website

reflection.ai/blog/introducing-beam

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

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