MiniMax M3
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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 Llama 4 Scout?
Llama 4 Scout represents a leap forward in multimodal AI, featuring 17 billion active parameters and a groundbreaking 10 million token context length. With its ability to integrate both text and image data, Llama 4 Scout excels at tasks like multi-document summarization, complex reasoning, and image grounding. It delivers superior performance across various benchmarks and is particularly effective in applications requiring both language and visual comprehension. Scout's efficiency and advanced capabilities make it an ideal solution for developers and businesses looking for a versatile and powerful model to enhance their AI-driven projects.
Integrations Supported
BLACKBOX AI
OpenTag
Factory Droid
MaxHermes
Integrations Supported
BLACKBOX AI
OpenTag
Groq
HTML
Julia
Llama
Llama 4 Behemoth
Meta AI
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
Free
Open source
Free Version
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
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
Meta
Date Founded
2004
Company Location
United States
Company Website
ai.meta.com
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
Open-Weight AI Models
Not specified
Categories and Features
AI Models
Not specified
AI Reasoning Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified
Small Language Models
Not specified