MiniMax M2.1: Significantly Enhanced Multi-Language Programming, Built for Real-World Complex Tasks
MiniMax has been continuously transforming itself in a more AI-native way. The core driving forces of this process are models, Agent scaffolding, and organization. Throughout the exploration process, we have gained increasingly deeper understanding of these three aspects. Today we are releasing updates to the model component, namely MiniMax M2.1, hoping to help more enterprises and individuals find more AI-native ways of working (and living) sooner.
In M2, we primarily addressed issues of model cost and model accessibility. In M2.1, we are committed to improving performance in real-world complex tasks: focusing particularly on usability across more programming languages and office scenarios, and achieving the best level in this domain.
- Exceptional Multi-Programming Language Capabilities
Many models in the past primarily focused on Python optimization, but real-world systems are often the result of multi-language collaboration.
In M2.1, we have systematically enhanced capabilities in Rust, Java, Golang, C++, Kotlin, Objective-C, TypeScript, JavaScript, and other languages. The overall performance on multi-language tasks has reached industry-leading levels, covering the complete chain from low-level system development to application layer development. - WebDev and AppDev: A Comprehensive Leap in Capability and Aesthetics
Addressing the widely recognized weakness in mobile development across the industry, M2.1 significantly strengthens native Android and iOS development capabilities.
Meanwhile, we have systematically enhanced the model's design comprehension and aesthetic expression in Web and App scenarios, enabling excellent construction of complex interactions, 3D scientific scene simulations, and high-quality visualization, making vibe coding a sustainable and deliverable production practice. - Enhanced Composite Instruction Constraints, Enabling Office Scenarios
As one of the first open-source model series to systematically introduce Interleaved Thinking, M2.1's systematic problem-solving capabilities have been further upgraded. The model not only focuses on code execution correctness but also emphasizes integrated execution of "composite instruction constraints," providing higher usability in real office scenarios. - More Concise and Efficient Responses
Compared to M2, MiniMax-M2.1 delivers more concise model responses and thought chains. In practical programming and interaction experiences, response speed has significantly improved and token consumption has notably decreased, resulting in smoother and more efficient performance in AI Coding and Agent-driven continuous workflows. - Outstanding Agent/Tool Scaffolding Generalization Capabilities
M2.1 demonstrates excellent performance across various programming tools and Agent frameworks. It exhibits consistent and stable results in tools such as Claude Code, Droid (Factory AI), Cline, Kilo Code, Roo Code, and BlackBox, while providing reliable support for Context Management mechanisms including Skill.md, Claude.md/agent.md/cursorrule, and Slash Commands. - High-Quality Dialogue and Writing
M2.1 is no longer just "stronger in coding capabilities." In everyday conversation, technical documentation, and writing scenarios, it also provides more detailed and structured responses.
First Impressions
"We're excited for powerful open-source models like M2.1 that bring frontier performance (and in some cases exceed the frontier) for a wide variety of software development tasks. Developers deserve choice, and M2.1 provides that much needed choice!"
Eno Reyes
Co-Founder, CTO of Factory AI
“MiniMax M2.1 performed exceptionally well across our internal benchmarks, showing strong results in complex instruction following, reranking, and classification, especially within e-commerce tasks. Beyond its general versatility, it has proven to be an excellent model for coding. We are impressed by these results and look forward to a close collaboration with the MiniMax team as we continue to support their latest innovations on the Fireworks platform.”
Benny Chen
Co-founder of Fireworks
“Minimax M2 series has demonstrated powerful code generation capability, and has quickly became one of the most popular model on Cline platform during the past few months. We already see another huge advancement in capability for M2.1 and very excited to continue partner with minimax team to advance AI in coding”
Saoud Rizwan
Founder, CEO of Cline
“We could not be more excited about M2.1! Our users have come to rely on MiniMax for frontier-grade coding assistance at a fraction of the cost, and early testing shows M2.1 excelling at everything from architecture and orchestration to code reviews and deployment. The speed and efficiency are off the charts!”
Scott Breitenother
Co-Founder, CEO of Kilo
"Our users love MiniMax M2 for its strong coding ability and efficiency. The latest M2.1 release builds on that foundation with meaningful improvements in speed and reliability, performing well across a wider range of languages and frameworks. It's a great choice for high-throughput, agentic coding workflows where speed and affordability matter."
Matt Rubens
Co-Founder, CEO of RooCode
“Integrating the MiniMax M2 series into our platform has been a significant win for our users, and M2.1 represents a clear step forward in what a coding-specific model can achieve. We’ve found that M2.1 handles the nuances of complex, multi-step programming tasks with a level of consistency that is rare in this space. By providing high-quality reasoning and context awareness at scale, MiniMax has become a core component of how we help developers solve challenging problems faster. We look forward to seeing how our community continues to leverage these updated capabilities.”
Robert Rizk
Co-Founder, CEO of BlackBox AI
Benchmarks
Furthermore, across specific benchmarks—including test case generation, code performance optimization, code review, and instruction following—MiniMax-M2.1 demonstrates comprehensive improvements over M2. In these specialized domains, it consistently matches or exceeds the performance of Claude Sonnet 4.5.
MiniMax-M2.1 delivers outstanding performance on the VIBE aggregate benchmark, achieving an average score of 88.6—demonstrating robust full-stack development capabilities. It excels particularly in the VIBE-Web (91.5) and VIBE-Android (89.7) subsets.
Showcases
Multilingual Coding
3D Interactive Animation
MiniMax M2.1 built a "3D Dreamy Christmas Tree" based on React Three Fiber and InstancedMesh, successfully rendering over 7,000 instances. It supports gesture interaction and complex particle animation, demonstrating advanced 3D rendering capabilities.
Try it out: https://yuyl27wq92.space.minimax.io/
Avant-Garde Web UI Design
M2.1 generated a minimalist photographer's personal homepage using an asymmetrical layout and a black-white-red contrasting color scheme. By combining immersive imagery with brutalist typography, it achieved a high-impact visual effect.
Try it out:https://m6xkaf07udss.space.minimax.io/
Website - Skincare Brand
M2.1 designed a landing page for a high-end organic skincare brand. Adopting a "Clean & Minimalist" style, it accurately presented the brand's premium identity and international visual appeal.
Try it out: https://2drpfocv00n9.space.minimax.io/
Web 3D Lego Sandbox
M2.1 developed a high-freedom 3D brick building application based on Three.js, implementing precise grid snapping algorithms and collision detection mechanisms. The project perfectly replicates the glossy texture of plastic bricks, supporting multi-angle rotation, drag-and-drop assembly, and instant color switching, providing users with an immersive 3D creative building experience.
Try it out: https://8e6nunemyuzh.space.minimax.io/
Native App Development - Android
M2.1 used Kotlin to develop a native Android gravity sensor simulator. Utilizing the gyroscope for a silky-smooth control experience, it features clever visual easter eggs that elegantly present the "MERRY XMAS MiniMax M2.1" message through natural UI transitions and collision effects.
Native App Development - iOS
M2.1 wrote an interactive iOS Home Screen widget, designing a "Sleeping Santa" click-to-wake mechanism. The logic is complete with native-level animation effects—Santa lives in your widget; tap him ten times to wake him up for a surprise! 🎅🎁
Web Audio Simulation Development
M2.1 developed a 16-step drum machine simulator based on the Web Audio API. It integrates synthesized drum sounds, non-linear rhythm algorithms, and real-time glitch sound effects, providing an avant-garde electronic music experience! (Turn on the sound in the video below to listen!)
Try it out: https://21okxwno2u.space.minimax.io
Rust TUI
M2.1 built a powerful Linux security audit tool with dual CLI + TUI modes using Rust, supporting one-click low-level scanning and intelligent risk rating for critical items such as processes, networks, and SSH.
Python Data Dashboard
M2.1 created a Web3 cryptocurrency price dashboard in the style of The Matrix. Use Python (backend for real-time price API fetching), HTML (structure), and CSS (Matrix aesthetic: green digital rain on black background, monospaced font, glowing neon green text, terminal-like UI).
C++ Image Rendering
M2.1 utilized C++ and GLSL to implement complex light transport algorithms, accurately rendering the physical refraction of a crystal ball, detailed SDF modeling of a snowman, and shimmering snow effects in a real-time environment.
Java Real-time Danmaku
M2.1 implemented a high-performance real-time Danmaku (bullet chat) system based on Java, a clean and intuitive user interface, and millisecond-level response capabilities.
SVG Generation
M2.1 generated an interactive isometric SVG island map, constructing a detailed miniature world that supports one-click zooming to freely explore four major themed areas.
Try it out: https://08tmc3aada59.space.minimax.io/
Agentic Tool Use
Tool Use Capability: Excel Market Research
M2.1 demonstrated its tool-use capabilities by autonomously invoking Excel and Yahoo Finance to complete an end-to-end task, ranging from market research data cleaning and analysis to chart generation.
Digital Employee
End-to-End Office Automation
Demo 1: Administrative tasks
Task Requirements: Proactively collect employees' equipment requests on communication software, then search for relevant documents on the enterprise's internal server to obtain equipment prices, calculate the total cost and determine whether the department budget is sufficient, and then record equipment changes.
Demo 2: Project management tasks
Task Requirements: Search for blocked or backlogged issues on the project management software, then find relevant employees on the communication software and consult them for solutions, and update the status of the issues based on the employees' feedback.
Demo 3: Software development tasks
Task Requirements: A colleague wants to know which is the most recent Merge Request that modified a certain file. Search for the relevant Merge Request, find its number, and inform the colleague.
Local Deployment Guide
We recommend using the following inference frameworks (listed alphabetically) to serve the model:
SGLang
We recommend using SGLang to serve MiniMax-M2.1. Please refer to our SGLang Deployment Guide.
Transformers
We recommend using Transformers to serve MiniMax-M2.1. Please refer to our Transformers Deployment Guide.
Inference Parameters
We recommend using the following parameters for best performance:temperature=1.0,top_p = 0.95,top_k = 40
How to Use
- The MiniMax-M2.1 API is now live on the MiniMax Open Platform: https://platform.minimax.io/docs/guides/text-generation
- Our product MiniMax Agent, built on MiniMax-M2.1, is now publicly available: https://agent.minimax.io/
- The MiniMax-M2.1 model weights are now open-source, allowing for local deployment and use: https://huggingface.co/MiniMaxAI/MiniMax-M2.1
Contact Us
Business Cooperation: [email protected]
MiniMax X: https://x.com/MiniMax__AI
MiniMax LinkedIn: https://www.linkedin.com/company/81521159
MiniMax Discord: https://discord.gg/minimax