I’m testing DeepSeek on a task where small differences between runs can make evaluation tricky. With the same prompt and settings, do you usually get substantially the same answer, or does the reasoning wander enough to affect the result?

I’d be interested in what you hold constant during a comparison—model version, sampling settings, or anything else—and whether you’ve found a practical way to distinguish normal variation from a real change in behavior.