# MiniMax-AI/MiniMax-M1

<https://repo.masters-masters.com/en/repos/MiniMax-AI/MiniMax-M1>

[Home](https://repo.masters-masters.com/en) › [MiniMax-AI](https://repo.masters-masters.com/en/owners/MiniMax-AI) › [MiniMax-M1](https://repo.masters-masters.com/en/repos/MiniMax-AI/MiniMax-M1)

MiniMax-AI/MiniMax-M1 has 3,186 stars on GitHub. Its RepoMasters card: RC tier. MiniMax-M1, the world's first open-weight, large-scale hybrid-attention…

| Field | Value |
| --- | --- |
| Owner | [MiniMax-AI](https://repo.masters-masters.com/en/owners/MiniMax-AI) |
| Stars | 3,186 |
| Forks | 281 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2025 |
| Topics | large-language-models, llm, reasoning-models, minimax-m1 |
| Tier | [RC (2,000 to 4,999 ★)](https://repo.masters-masters.com/en/ranks/blockbuster) |
| View on GitHub | [MiniMax-AI/MiniMax-M1](https://github.com/MiniMax-AI/MiniMax-M1) |

## Repository

MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

The tier for repos with 2,000 to 4,999 ★. Published odds per card pulled: 3%. Rarity: Epic.

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Data: GitHub · Illustration: the project’s public image, pixelated by RepoMasters.