MiniMax-AI/MiniMax-M3

MiniMax-AI/MiniMax-M3

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Created: 2026-06-01T06:05:17Z

Pushed: 2026-06-03T03:45:29Z

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README:

MiniMax-M3 is Coming

MiniMax-M3 is the next generation of the MiniMax series, building on the agent harness, software engineering, and professional-work foundations established by MiniMax-M2.7. The model is not yet released — this repository exists so the community can share what they need next.

We Want Your Feedback

Before M3 lands, we are listening. If you are using MiniMax-M2.7 (via the API, Agent, or locally) and have something to say about it, please tell us — every report directly shapes M3.

We are especially interested in:

• 🐛 Bugs and regressions — anything that broke, hallucinated, or behaved unexpectedly in M2.7.
• 💡 Capability requests — what M2.7 still can't do well for your workload (agent harnesses, SWE, professional work, entertainment, multilingual, long context, tool use, …).
• 📊 Benchmark gaps — public or internal evals where you would like to see M3 improve.
• 🧰 Deployment pain points — issues with SGLang, vLLM, Transformers, ModelScope, NIM, or the API.
• 🧠 Agent / skill feedback — anything you observed while building Agent Teams, Skills, or dynamic tool search on top of M2.7.

How to send feedback

| Channel | Use for | |---|---| | 📮 Open an Issue | Bugs, capability requests, M2.7 → M3 comparisons. Pick a template. | | 💬 WeChat | Chinese-speaking community discussion. | | 🧩 Discord | English-speaking community discussion. | | [✉️ model@minimax.io](mailto:model@minimax.io) | Private feedback, partnership, or evaluation requests. |

If you are reporting a bug from M2.7, please include: 1. Which inference path you used (MiniMax API / Agent / SGLang / vLLM / Transformers / NIM / ModelScope). 2. Inference parameters (temperature, top_p, top_k, system prompt). 3. A minimal reproduction — prompt, expected output, actual output.

In the Meantime — Use M2.7

While M3 is in development, M2.7 remains our latest released model:

• MiniMax Agent: https://agent.minimax.io/
• MiniMax API: https://platform.minimax.io/
• Token Plan: https://platform.minimax.io/subscribe/token-plan
• Weights & deployment guides: MiniMax-M2.7 (SGLang / vLLM / Transformers / ModelScope / NVIDIA NIM)
• Model card: https://huggingface.co/MiniMaxAI/MiniMax-M2.7

Recommended inference parameters for M2.7: temperature=1.0, top_p=0.95, top_k=40.

Stay Updated

Watch this repository for the M3 announcement, release notes, weights, and deployment guides.

Contact Us

Contact us at [model@minimax.io](mailto:model@minimax.io).