ML engineers comparing instruction-tuned model variants (e.g., choosing between a base fine-tune, RLHF-tuned, and DPO-tuned version of the same model) need a structured evaluation suite that goes beyond perplexity to measure instruction following, format compliance, safety, and task-specific quality.