MiniMax M3

MiniMax M3

MiniMax
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About

Gemini 3.7 Flash is Google’s most intelligent workhorse model yet for coding and agents, delivering substantial improvements across software engineering, knowledge work, web development, and complex business workflows. It shows stronger performance in debugging and issue resolution, higher first-pass code accuracy, and improved generation of production-ready code. For web development, the model creates more functional layouts and feature-complete applications in fewer prompts, with strong design adherence when working from screenshots, images, or complete design systems. In knowledge-dense fields such as finance, law, and biosciences, it provides improved reasoning, accuracy, and complex-document understanding. Gemini 3.7 Flash also performs more effectively on real-world workflow automation and multimodal tasks, supporting use cases ranging from interactive web experiences and data stories to robotics and dynamically generated 3D content.

About

MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers, enterprises, and engineering teams seeking to build agents, automate complex workflows, generate production-ready software, and perform multimodal tasks

Audience

MiniMax M3 is best suited for developers, AI engineers, coding assistant builders, enterprise automation teams, research teams, data teams, agent developers, and organizations that need open-weight AI for coding, long-context reasoning, multimodal understanding, tool use, repository analysis, and autonomous workflows

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$0.75 per 1M tokens (input)
$0.75/1M input and $3.75/1M output tokens
Free Version
Free Trial

Pricing

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

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • The biggest draw is the focus on complex software engineering, web development, and autonomous agent workflows. If it really improves planning and instruction-following, that matters a lot for coding agents that need to work across multiple steps without drifting. The lower price is a big win too. Flash models are supposed to be the workhorses, so cutting the cost while improving coding quality makes it much more appealing for high-volume use.

Cons

  • Fast models like Gemini 3.7 Flash can be great for everyday development, but I would not hand it a production repo and blindly accept every change.

Pros & Cons from Real Users

Pros

  • The multimodal side also makes it more flexible than a code-only model. Being able to work across text, images, video-style understanding, and code gives it more room to support real workflows instead of being boxed into one narrow use case. For agent builders, the best part is that M3 is clearly designed around tool use and multi-step execution. MiniMax specifically calls out autonomous task decomposition and tool invocation, which is exactly what matters when a model is powering coding assistants, workflow agents, or automated dev tools.

Cons

  • The main catch is infrastructure and trust. Even with sparse attention and MoE efficiency, this is still a large model, so deployment is not casual. I would also want to benchmark it on my own repos before depending on it for production work.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
google.com

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io

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Categories

Categories

Integrations

Factory Droid
OpenClaw
APIFree
Agent Search on Gemini Enterprise Agent Platform
Alibaba AI Coding Plan
CSS
Cursor
Gemini 3.5 Flash-Lite
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Go
Google AI Mode
JavaScript
OfoxAI
Pi Agent
R
Ruby
Tabbit Browser
Together AI
Vision Agents

Integrations

Factory Droid
OpenClaw
APIFree
Agent Search on Gemini Enterprise Agent Platform
Alibaba AI Coding Plan
CSS
Cursor
Gemini 3.5 Flash-Lite
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Go
Google AI Mode
JavaScript
OfoxAI
Pi Agent
R
Ruby
Tabbit Browser
Together AI
Vision Agents
Claim Gemini 3.7 Flash and update features and information
Claim Gemini 3.7 Flash and update features and information
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Claim MiniMax M3 and update features and information