What is OpenAI's deployment simulation?

Deployment simulation is a pre-release safety method that replays anonymized past user conversations with a new candidate model to predict how it will behave before it reaches users. OpenAI published the technique on June 16, 2026, according to OpenAI's research page.

The method strips the original assistant responses from recent conversations and has the candidate model regenerate them. Researchers then evaluate those completions for new failure modes and estimate how often undesired behaviors would appear in real deployment traffic.

How does deployment simulation differ from traditional evaluations?

Traditional pre-release evaluations rely on synthetic, manually written, or adversarial prompts. Those prompts are built to stress-test models in rare or high-severity scenarios. They work well for that purpose, but they carry three known weaknesses.

Here is how the two approaches compare, as reported by OpenAI: