MiniMax M2.7 on OpenRouter

Reddit r/LocalLLaMA / 3/19/2026

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Key Points

MiniMax-M2.7 on OpenRouter is a next-generation large language model designed for autonomous, real-world productivity with agentic multi-agent collaboration to plan, execute, and refine tasks in dynamic environments.
It is trained for production-grade performance and supports workflows such as live debugging, root-cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint.
It reports benchmarks including 56.2% on SWE-Pro, 57.0% on Terminal Bench 2, and a 1495 ELO on GDPval-AA, claiming to set a new standard for multi-agent systems in real-world digital workflows.
It uses a 204,800-token context window and pricing of $0.30 per million input tokens and $1.20 per million output tokens.

204,800 context
$0.30/M input tokens
$1.20/M output tokens

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments.

Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

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