GPT-5.6 scores 56 on Senior Engineer Benchmark

The low benchmark score for GPT-5.6 is misleading because its primary failure mode is over-engineering rather than poor problem-solving capability. Highly capable LLMs naturally default to verbose architectural overhauls when simpler, cleaner modifications would be far more effective.

• –Legacy Code Bloat: GPT-5.6 lost significant points for failing to prune dead code during refactoring tasks.
• –Over-Engineering Bias: The model consistently preferred multi-layered abstractions over minimal, targeted diffs.
• –Prompt Engineering Implication: Developers using advanced models must explicitly prompt for minimal diffs and conciseness to counteract the model's default verbosity.