ModelRefs / Eval (Production Evaluation) — AI Glossary
Eval (Production Evaluation) — AI Glossary
Automated tests that score LLM outputs against criteria — exact match, LLM-as-judge, rubric, or programmatic checks. Production evals are not benchmarks.
Overview
Production evals catch regressions when prompts, models, or RAG sources change. The modern stack runs evals in CI on a golden dataset and on a rolling sample of live traffic. Key dimensions: correctness, coherence, groundedness, safety, latency.
Reference details
| Topic | evaluation |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Example: The regression a demo will not catch
A prompt tweak lifts summary quality and quietly breaks date extraction in 4% of cases. Nobody notices until a customer does. A golden set of a few hundred labelled cases, run in CI on every prompt or model change, turns that into a failing build. The point is not proving quality — it is catching the change you did not intend.
Commonly confused with
Production evals are not benchmarks. A benchmark compares models on a shared public task; an eval tests your system on your data with your success criteria. A model that tops a leaderboard can still fail your eval, which is the only one that governs your release.
When to use it
Reach for it when:
- Anything reaching production, from the first prompt change onward
- You change models, prompts, retrieval or chunking — each can regress the others
- You need evidence of quality over time rather than a single impression
Reach for something else when:
- As a substitute for looking at real outputs; judges miss what humans catch immediately
- With an LLM judge you have never validated against human labels
- On a golden set so stale it no longer resembles live traffic
Referenced by
This term is used by the following ModelRefs references:
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Frequently asked questions
What is Eval (Production Evaluation)?
Automated tests that score LLM outputs against criteria — exact match, LLM-as-judge, rubric, or programmatic checks.
What concepts are related to Eval (Production Evaluation)?
Closely related concepts include evaluation benchmark, llm as judge, regression.