MiniMax
@minimax-ai • Intelligence with Everyone. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
58%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
28 repos
Visible snapshot
11 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (14), Unknown (8), TypeScript (4)
Average size
1.2K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2026-06-15(17d ago)GitHub API fallback28 repositories
58%
of the visible star count comes from this organization's top three repositories.
1.2K
stars per repository in this same snapshot.
Python
is the most common language here, with 11 repositories updated in the last 90 days.
Why this rank
This organization stands out because its public portfolio is relatively balanced across 28 repositories.
Balanced portfolio across 28 reposTop 3 share 58%
Organization pages work best when you separate portfolio breadth from flagship concentration. In MiniMax's case, the visible top three repositories account for about 58% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (14), Unknown (8), TypeScript (4). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars | 🍴 Forks | Updated |
|---|---|---|---|---|---|
| 1 | minimax-ai/skills | C# | 12.9K | 1.1K | 2 months ago |
| 2 | minimax-ai/MiniMax-01 The official repo of MiniMax-Text-01 and MiniMax-VL-01, large-language-model & vision-language-model based on Linear Attention | Python | 3.4K | 330 | 12 months ago |
| 3 | minimax-ai/MiniMax-M1 MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. | Python | 3.2K | 284 | 12 months ago |
| 4 | minimax-ai/Mini-Agent A minimal yet professional single agent demo project that showcases the core execution pipeline and production-grade features of agents. | Python | 2.8K | 416 | 4 months ago |
| 5 | minimax-ai/MiniMax-M2 MiniMax-M2, a model built for Max coding & agentic workflows. | 2.6K | 215 | 7 months ago | |
| 6 | minimax-ai/cli Generate text, images, video, speech, and music by MiniMax. | TypeScript | 2K | 140 | 3 weeks ago |
| 7 | minimax-ai/MiniMax-MCP Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs. | Python | 1.5K | 271 | 1 months ago |
| 8 | minimax-ai/OpenRoom A browser-based desktop where AI Agent operates every app through natural language. | TypeScript | 1.2K | 159 | 4 weeks ago |
| 9 | minimax-ai/MiniMax-M2.5 | 585 | 77 | 3 months ago | |
| 10 | minimax-ai/MiniMax-M2.1 MiniMax M2.1, a SOTA model for real-world dev & agents. | 542 | 46 | 5 months ago | |
| 11 | minimax-ai/VTP [ECCV 2026] Towards Scalable Pre-training of Visual Tokenizers for Generation | Python | 494 | 15 | 2 months ago |
| 12 | minimax-ai/MiniMax-M3 | 383 | 36 | Yesterday | |
| 13 | minimax-ai/MSA | Python | 369 | 35 | 2 weeks ago |
| 14 | minimax-ai/MiniMax-M2.7 | 348 | 61 | 2 months ago | |
| 15 | minimax-ai/One-RL-to-See-Them-All The official repo of One RL to See Them All: Visual Triple Unified Reinforcement Learning | Python | 331 | 17 | 1 years ago |
| 16 | minimax-ai/SynLogic [NeurIPS 2025] The official repo of SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond | Python | 203 | 22 | 12 months ago |
| 17 | minimax-ai/MiniMax-MCP-JS Official MiniMax Model Context Protocol (MCP) JavaScript implementation that provides seamless integration with MiniMax's powerful AI capabilities including image generation, video generation, text-to-speech, and voice cloning APIs. | TypeScript | 123 | 38 | 11 months ago |
| 18 | minimax-ai/MiniMax-Coding-Plan-MCP Specialized MiniMax Model Context Protocol (MCP) server designed for coding-plan users, featuring AI-powered search and vision analysis APIs optimized for code development workflows | Python | 93 | 25 | 4 months ago |
| 19 | minimax-ai/awesome-minimax-integrations Explore these applications integrating MiniMax's multimodal API to see how text, vision, and speech processing capabilities are incorporated into various software. | 76 | 17 | 5 months ago | |
| 20 | minimax-ai/MiniMax-AI.github.io The official GitHub Page for MiniMax | HTML | 71 | 14 | 7 months ago |
| 21 | minimax-ai/minimax_search MiniMax Search is an MCP (Model Context Protocol) server that provides web search and browsing capabilities. | Python | 56 | 13 | 8 months ago |
| 22 | minimax-ai/audio-tools A collection of optimized utilities for text-to-audio processing, enhancing both training and inference workflows. This repository contains robust implementations adapted from open-source libraries. | Python | 49 | 8 | 1 years ago |
| 23 | minimax-ai/MiniMax-Provider-Verifier MiniMax-Provider-Verifier offers a rigorous, vendor-agnostic way to verify whether third-party deployments of the Minimax M2 model are correct and reliable. | Python | 48 | 12 | Today |
| 24 | minimax-ai/minimax-code | 40 | 7 | 2 weeks ago | |
| 25 | minimax-ai/mini-vela | Python | 35 | 5 | 3 months ago |
| 26 | minimax-ai/vllm A high-throughput and memory-efficient inference and serving engine for LLMs | Python | 15 | 11 | 8 months ago |
| 27 | minimax-ai/vercel-minimax-ai-provider minimax-ai-provider is a community provider that use minimax-m2 to provide language model support for the AI SDK. | TypeScript | 11 | 6 | 3 weeks ago |
| 28 | minimax-ai/MiniMax-Hackathon | 3 | 0 | 9 months ago |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
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