Testing MiniMax M2.7 via API on three real ML and coding workflows
Summary
The article evaluates MiniMax M2.7 via API integrated with Claude Code across three real-world ML and coding workflows, comparing it against Claude Opus 4.7. It highlights that M2.7 performs best when task constraints are explicit, discusses setup details, cost, and throughput, and emphasizes the importance of harness design and human-in-the-loop for open-ended tasks. The piece also covers practical lessons for applying agentic models to reproducible workflows and Kaggle competition work.