Share of Model
Share of model is the portion of an AI model's 'mindshare' a brand occupies within its category — how often, how prominently, and how favorably the model surfaces the brand relative to competitors when relevant questions are asked. The term frames LLMs as a market to win presence in, analogous to share of market or share of search.
Share of search — branded search volume as a fraction of the category — proved to be a useful leading indicator of market share. Share of model applies the same logic to generative engines: if models disproportionately surface a competitor when buyers describe your category, that bias propagates into shortlists before any marketing touch.
Unlike share of search, share of model cannot be read from a public dataset; it must be sampled through prompt simulation and computed from the answers — mention share, first-position share, recommendation share. The metric is only as good as the prompt set and cadence behind it.
It is also model-specific in a way search never was: each engine (and each model version within an engine) has its own distribution. Reporting share of model responsibly means reporting it per engine, with the model refresh dates annotated on the trend.
Related terms
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