MiniMax M2.5

MiniMax M2.5 is built as a 230B Mixture-of-Experts model that utilizes 10B active parameters to balance high-level performance with operational efficiency. Designed specifically for real-world productivity, the architecture is optimized for complex agentic tasks, including software engineering, advanced tool use, and search-based workflows. By focusing on efficient text generation, the model serves as a robust engine for office-style automation, providing a scalable solution for users who require consistent, high-quality reasoning across diverse and demanding professional environments.

The model benefits from advanced training methodologies, including reinforcement learning scaling and agent-native frameworks that enhance its ability to perform step-by-step verification. These techniques allow the model to function effectively as a professional employee, maintaining high performance while remaining cost-effective for continuous, long-running agentic operations. With support for modern inference backends and quantization, it is well-suited for self-hosted deployments and enterprise-grade applications that prioritize both accuracy and computational throughput.