Share of Model
Share of model is how often an AI model names or recommends your brand from its own internal knowledge, without live retrieval, reflecting how well-established you are in what the model learned.
Share of model is your presence in the AI's baked-in knowledge. It measures how frequently a model brings you up on its own — when asked a question without browsing — reflecting how prominently your brand featured in its training data. It's distinct from retrieval-based visibility, which depends on live citation.
The distinction sharpens strategy. Citation share and share of voice measure whether you're retrieved and cited now; share of model measures whether the model already "knows" you. The first you influence with on-page and authority work that pays off quickly; the second builds slowly, as broad, lasting reputation makes its way into future training runs. Tracking both — the adaptability pillar — tells you where your visibility comes from and where the gaps are.
Example. Ask a model with browsing off "name some good project management tools." The brands it lists from memory have share of model. Earning a place on that unprompted list is a slower game than winning a single retrieved citation, but a durable one.
Relevant pillar
Related terms
- Share of Voice (AI)Share of voice in AI search is the proportion of relevant AI answers in which your brand appears, measured across a fixed set of questions, as a gauge of how present you are in the conversation.
- Citation ShareCitation share is the percentage of AI answers to your target questions in which your site is specifically cited as a source, the strictest measure of whether you're winning the citation, not just being mentioned.
- Training DataTraining data is the body of text and other content an AI model learns from during training, shaping what it knows by default before any live retrieval is involved.