Qwen prompt volatility tracking
qwenprompt_volatilityAccount required
Qwen's commercial answers are noticeably more volatile than its informational ones, because product surfaces beneath it change faster than reference content does.
How it renders
Derived across the sample set, reported per intent bucket.
Sampling
Volatility is what tells you the right n for every other field. We recommend using it to allocate credits: sample noisy prompts deeply, stable prompts lightly.
Gotcha
High volatility on a commerce prompt often reflects genuine catalogue churn rather than model instability. Diagnose before you report it as noise.
What the API returns
A single collection call against Qwen for the prompt volatility field, sampled n times and returned as one object per prompt.
{
"engine": "qwen",
"field": "prompt_volatility",
"prompt": "best ai visibility tracking tool",
"country": "GB",
"language": "en",
"n": 30,
"volatility": {
"jaccard": 0.42,
"mention_variance": 0.11,
"recommended_n": 75,
"band": "moderate"
}
}Response fields
| Key | Type | Notes |
|---|---|---|
| jaccard | float | Mean pairwise citation-set overlap across samples. |
| mention_variance | float | Variance in brand presence across samples. |
| recommended_n | integer | Samples needed for a ±10 point interval on this prompt. |
| band | string | stable | moderate | volatile. |
Qwen prompt volatility FAQ
- Why are Qwen commerce prompts volatile?
- The underlying product data changes constantly. The model is stable; its inputs are not.
- Should I sample commerce prompts harder?
- Yes. We usually recommend a larger n on the commercial bucket.
Size your Qwen sampling per intent
We will run a volatility pass and recommend n for each bucket.
Other Qwen data
Across every engine
Compare how prompt volatility behaves on every engine we track.
Prompt volatility across all engines →