🚀 MiniMax-M2 Outsmarts Claude Opus 4.1 — And It’s Open Source

MiniMax has just open-sourced its new flagship model, MiniMax-M2 — and it’s already shaking up the intelligence rankings.

October 27, 2025

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The “Agent & Code Native” model is built specifically for developer workflows and agentic reasoning, combining deep reasoning ability with high-speed coding efficiency. Despite its 230 B total parameters, only 10 B activate per inference, delivering frontier-level performance at a fraction of the cost.

According to MiniMax, M2 runs nearly twice as fast as Claude Sonnet and costs only 8 % as much per query. That’s not just optimization — that’s a redefinition of AI economics.

🧠 The Numbers: MiniMax-M2 Beats Claude Opus 4.1

On the Artificial Analysis Intelligence Index v3.0, MiniMax-M2 achieved a score of 61, placing 8th overall — above Claude Opus 4.1 (59) and ahead of other major open-source players like Qwen 3 72B (58) and DeepSeek-V3.2 (57).

The benchmark aggregates 10 key evaluations, including:

  • MMLU-Pro for general knowledge reasoning

  • GPQA Diamond for graduate-level question answering

  • AIME 2025 for mathematical reasoning

  • SciCode for code synthesis

  • Terminal-Bench Hard for real-world coding and agentic tool-use

Together, these form one of the most rigorous public intelligence rankings yet — and MiniMax-M2 lands firmly in the top tier.

💻 Coding & Tool-Use: Real-World Power

MiniMax-M2’s coding metrics are staggering:

  • 46.3 on Terminal-Bench, beating Claude Sonnet 4.5 and Gemini 2.5 Pro

  • 44 on BrowseComp, dwarfing Claude Sonnet 4.5’s 19.6

These scores suggest MiniMax-M2 isn’t just reasoning — it’s building, debugging, and autonomously handling tool-based tasks faster than many proprietary models.

🔓 Free & Open for Everyone

MiniMax has released the model weights on Hugging Face and GitHub, and the company is offering free access through its Agent and API platforms for a limited period.

This transparency signals a clear shift: open-source AI is catching up to — and in some cases surpassing — closed frontier models.

⚙️ Why It Matters

MiniMax-M2 represents a new phase in AI evolution — where efficiency + accessibility + intelligence finally converge.
It’s a blueprint for how future models could operate:

  • Sparse activation for massive parameter efficiency

  • Native support for agentic reasoning

  • Real-time coding and tool integration

  • Open accessibility for independent developers

The open-source frontier is no longer lagging behind — it’s defining the next generation of practical intelligence.

🔭 The Bigger Picture

The AI landscape is shifting from “closed vs open” to “expensive vs efficient.”
MiniMax-M2’s debut shows that affordable, high-performance AI can thrive outside Big Tech’s walled gardens — a trend that could permanently change who controls the future of artificial intelligence.

📰 Source: MiniMax official release, Artificial Analysis v3.0
📂 Model access: Hugging Face | GitHub | MiniMax Agent Platform
📈 Editor’s note: FutureGen News will be tracking benchmark updates and industry adoption metrics over the coming weeks.