MiniMax M2.7 Open-Sourced: Self-Evolving 230B MoE Agent Model Matches GPT-5.3-Codex on SWE-Pro at 56.22%

MarkTechPost / MiniMax·medium signal

MiniMax open-sourced M2.7, a 230B-parameter sparse MoE model scoring 56.22% on SWE-Pro and 57% on Terminal Bench 2, matching GPT-5.3-Codex on real-world software engineering tasks. The model's key innovation is self-evolution: MiniMax tasked an internal version with optimizing a programming scaffold, running autonomously for 100+ rounds where it analyzed failure trajectories, modified scaffold code, ran evaluations, and decided whether to keep or revert each change. Available on HuggingFace with SGLx, vLLM, and NVIDIA NIM support.