Summary
Fahd Mirza pits GLM 5.1 from Zhipu AI against MiniMax M2.7 in a structured four-part coding comparison run entirely through OpenClaw, an open-source terminal AI interface. Unlike most model comparisons that rely on simple prompts, this test uses identical servers, identical repository codebases, and identical prompts across four distinct challenge types: cold code creation from scratch, legacy codebase modernization, feature addition, and bug fixing plus refactoring on a purpose-built threat intelligence API built with FastAPI, async SQLAlchemy, Celery workers, and a full IOC ingestion pipeline.
The opening cold-creation test asks both models to render a world map in raw SVG with Bezier arc animation in vanilla JavaScript — no libraries permitted. MiniMax returns output faster, but a visual side-by-side favors GLM’s result. In the codebase modernization segment, GLM progresses significantly faster, actively rewriting and refactoring files while MiniMax is still reviewing the repository structure at the same elapsed time.
The video is one of the more methodologically honest model comparisons available for agentic coding tasks, using real-world code that would appear in production environments rather than toy exercises. Both models are accessed via OpenClaw’s TUI, making the setup straightforward to replicate. GLM 5.1 comes out ahead in the majority of tests, particularly in sustained multi-file reasoning tasks, though viewers can judge the raw output directly from the screen recordings.
📺 Source: Fahd Mirza · Published March 29, 2026
🏷️ Format: Comparison
