# Evaluating LLMs in Production
Moving LLMs from prototype to production requires a robust evaluation framework. Standard machine learning metrics often fail to capture the nuances of generative AI.
1. Beyond ROUGE and BLEU
Traditional NLP metrics like ROUGE and BLEU are insufficient for evaluating creative or complex outputs. Instead, focus on:
* **LLM-as-a-Judge**: Using a larger model (GTP-4) to grade the output of a smaller model.
* **Deterministic Tests**: Checking for specific keywords, JSON structure, or valid code.
2. Human-in-the-Loop
Automated metrics are only half the story. Implement a "thumbs up/down" feedback loop in your UI to collect ground-truth data from actual users.
3. Latency vs. Quality
In production, every millisecond counts. We measure "Time to First Token" (TTFT) and "Tokens Per Second" (TPS) alongside semantic accuracy.