MiniMax M3 vs. GLM 5.2: Codegen comparison across autonomous coding tasks
10 hours ago
- #Model Comparison
- #Greenfield Builds
- #AI Coding Benchmark
- Thinkbench was used to evaluate GLM 5.2 and MiniMax M3 in autonomous coding tasks, including greenfield builds, bug fixes, feature additions, and repair-to-green tasks.
- GLM 5.2 achieved a 92% full-pass rate and a 0.976 mean score, while MiniMax M3 achieved 84% full-pass and a 0.961 mean score.
- MiniMax M3 was cheaper ($6.67 vs. $18.47) and faster (45s vs. 80s avg latency) compared to GLM 5.2.
- Performance differences were concentrated in greenfield builds, with GLM being steadier in packaging and complete delivery, while MiniMax sometimes excelled in individual hard builds.
- In tasks with ambiguous instructions, MiniMax tended to add more production-shaped machinery, while GLM stayed closer to the plain reading of the brief.
- For existing-code work, both models performed similarly, with mean scores ranging from 0.999 to 1.000.
- GLM is recommended for hard from-scratch builds requiring complete, runnable projects, while MiniMax is a value pick for bug fixes, feature additions, or repair-to-green tasks under review.
- Neither model is recommended as a top-level coordinator; a frontier coordinator like GPT-5.5 or Claude Opus is suggested for delegating and checking work.