MiniMax M2.7 takes part in its own model and harness evolution
Original titleMiniMax M2.7: Early Echoes of Self-Evolution
MiniMax says M2.7 is its first model to deeply participate in its own evolution, building agent harnesses and running reinforcement learning experiment workflows.
The post reports 56.22% on SWE-Pro, 55.6% on VIBE-Pro, 57.0% on Terminal Bench 2, and a 30% improvement on an internal evaluation set after more than 100 autonomous optimization rounds.
It also states that M2.7 handles 30%-50% of its research team's workflow, though human researchers still make critical decisions.
The post ties M2.7's self-evolution claims to specific benchmark numbers and workflow details, helping readers judge how much of the iteration loop is autonomous.
Source: MiniMax Blog · minimax.ioPublished · added here