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What is MiniMax M3?

MiniMax M3 is an open-weight multimodal foundation model from MiniMax that brings together coding capability, agentic reasoning, native multimodality, and long-context processing in one model. It is designed for demanding AI workflows where a system needs to understand large amounts of information, reason through multi-step tasks, use tools, and work with different input types. MiniMax M3 supports a context window of up to 1 million tokens, making it useful for large code repositories, long documents, multi-file analysis, research workflows, enterprise automation, and persistent agent memory. The model uses MiniMax Sparse Attention, an architecture built to improve efficiency at very long context lengths by reducing the cost of attention. MiniMax M3 is natively multimodal and can work with text, images, and video inputs, allowing it to support richer workflows than text-only language models. It is positioned for coding, software engineering, tool invocation, browser-style retrieval, computer-use-style tasks, and autonomous task decomposition. The model’s architecture includes a large total parameter count with a smaller number of activated parameters, supporting more efficient inference through a mixture-of-experts design. Developers can use MiniMax M3 to build coding assistants, AI agents, document intelligence systems, multimodal analysis tools, and automated enterprise workflows. Its long-context design helps reduce the need to compress or split large inputs, allowing teams to keep more project context available during reasoning. The model is available through open-weight releases and hosted API providers, giving developers multiple ways to test, deploy, or integrate it into applications. MiniMax M3 helps organizations build advanced AI systems that combine long memory, multimodal understanding, coding strength, and agentic execution.

What is LTM-1?

Magic’s innovative LTM-1 technology enables context windows that are 50 times greater than the standard ones found in traditional transformer models. Consequently, Magic has created a Large Language Model (LLM) capable of efficiently handling extensive contextual information for generating recommendations. This breakthrough empowers our coding assistant to thoroughly examine and utilize your entire code repository. By drawing on a wealth of factual knowledge and its own previous interactions, larger context windows greatly improve the accuracy and cohesiveness of AI-generated responses. We are enthusiastic about the possibilities this research presents for enhancing user experiences in coding assistance tools, paving the way for smarter, more intuitive interactions. Ultimately, we believe these advancements will significantly transform how developers engage with their coding environments.

Media

Media

Integrations Supported

APIFree
BLACKBOX AI
Clawd.run
Cline
ClinePass
Factory Droid
Hermes Agent
MaxHermes
MiniMax Agent
MiniMax Code
MiniMax Mavis
Ollama
OpenCode Go
OpenCode Zen
Pi Agent
Roo Code
Tabbit Browser
Together AI
Vision Agents

Integrations Supported

Quickwork

API Availability

Has API

API Availability

Pricing Information

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

MiniMax

Date Founded

2021

Company Location

Singapore

Company Website

www.minimax.io

Company Facts

Organization Name

Magic AI

Date Founded

2022

Company Location

United States

Company Website

magic.dev/blog/ltm-1

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

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