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MiniMax-M1 - AI Language Models Tool

Overview

MiniMax-M1 is an open-weight, large-scale hybrid-attention reasoning model built with a Mixture-of-Experts architecture and lightning attention. It supports extended context lengths up to 1,000,000 tokens and is optimized with reinforcement learning for tasks from mathematical reasoning to complex software engineering environments.

Key Features

  • Open-weight large-scale reasoning model
  • Hybrid Mixture-of-Experts architecture
  • Lightning attention mechanism for efficient attention
  • Supports extended context length up to 1,000,000 tokens
  • Optimized with reinforcement learning for task performance
  • Targeted for mathematical reasoning and software engineering tasks

Ideal Use Cases

  • Mathematical reasoning and formal problem solving
  • Complex software engineering environment modeling and reasoning
  • Long-context document and codebase analysis up to 1,000,000 tokens
  • Research and development of large-scale reasoning models

Getting Started

  • Visit the GitHub repository: https://github.com/MiniMax-AI/MiniMax-M1
  • Read the repository README and documentation for requirements
  • Clone the repository to your local environment
  • Install dependencies listed in the project documentation
  • Load the model weights following the provided instructions
  • Run the provided example scripts or evaluation notebooks

Pricing

Pricing not disclosed in the repository or project description

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
Visit Official Website

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