Minimax/Minimax-M2

The Minimax-M2 is engineered as a high-efficiency Mixture-of-Experts architecture, designed to balance massive total parameter capacity with a lean active parameter footprint. This design intent focuses on delivering near-frontier intelligence while maintaining the low latency and high concurrency required for demanding agentic environments. By optimizing for responsiveness, the architecture supports complex, multi-step task execution, making it particularly effective for developers and systems that require rapid, reliable performance in automated workflows.

The model lineage emphasizes specialized training for agentic tool use and complex reasoning, with a specific focus on maintaining stability during long-horizon planning and execution. It has been refined to excel in iterative development cycles, such as compile-run-fix loops and test-validated repairs. While the supplied evidence highlights its proficiency in these areas, it does not detail the specific pre-training datasets or the proprietary post-training alignment recipes used to achieve its current performance levels.