Evaluation · beginner
Offline Evaluation (offline eval, pre-production eval)
Offline evaluation runs a fixed dataset of inputs through a candidate model or prompt, scores each output, and reports aggregate quality — the standard way to compare changes before shipping.
Explanation
The setup: an eval dataset of (input, optional expected output, optional context) rows, a scoring function (exact match, LLM-as-judge, faithfulness, custom regex, etc.), and a runner that produces a score per row plus aggregate metrics (accuracy, win rate, mean latency, cost).
Offline eval is the cheap iteration loop. It runs in CI, takes minutes, and gives a deterministic answer to "did this prompt change make things better or worse on these 200 cases?"
Failure modes: eval set is unrepresentative (production has 10× more failure modes), eval set is contaminated (the same examples were used to write the prompt), or the scorer is biased (LLM-as-judge prefers verbose answers).
Best paired with online eval, which catches the failure modes offline eval misses.
Examples
- A RAG team's offline eval: 500 (question, gold answer) pairs, scored by LLM-as-judge on faithfulness and relevance, run on every prompt PR.
- A coding agent's offline eval: 100 SWE-bench-style tasks, scored pass/fail on whether tests pass after the agent's patch.
Frequently asked
What is Offline Evaluation?
Offline evaluation runs a fixed dataset of inputs through a candidate model or prompt, scores each output, and reports aggregate quality — the standard way to compare changes before shipping.
What is an example of offline evaluation?
A RAG team's offline eval: 500 (question, gold answer) pairs, scored by LLM-as-judge on faithfulness and relevance, run on every prompt PR.
How is Offline Evaluation related to Online Evaluation?
Offline Evaluation and Online Evaluation are both evaluation concepts. Online evaluation runs scoring functions over live production traffic — usually a sample of recent traces — to monitor quality continuously instead of relying solely on a fixed offline dataset.
Is Offline Evaluation considered beginner?
Offline Evaluation is generally considered beginner-level material in the AI and LLM space.