Term
Share of Model
Share of model is a metric that measures how often a brand is mentioned in the answers of AI language models, relative to the mentions of all competitors in the same category. It is considered the AI counterpart to the classic share of voice.
Share of Model — explained in detail
Share of model is a metric common in 2026 that captures how visible a brand is in the answers of AI language models. It measures the proportion of a brand’s mentions among all brand mentions in a category across systems such as ChatGPT, Claude, Gemini, or Perplexity. In simple terms, the metric answers the question of how often a model recommends or mentions a particular brand when users ask about products or solutions.
The background is a shift in information behavior. As people increasingly direct their research to AI assistants, they often receive direct answers instead of browsing a list of search results. Which brands are named in these answers therefore helps decide who even makes it into consideration. Share of model attempts to make this presence measurable.
Measurement is usually done by repeatedly sending a defined set of typical questions to several models. It is then evaluated in what proportion of the answers the brand and those of competitors appear. This yields a percentage share. Specialized tools automate these queries and often additionally consider tone and source citations.
Caution is needed when interpreting the figure. Language model answers fluctuate, depend on how the question is phrased, and change with model updates. Share of model is therefore an approximation and a snapshot, not an exact, stable measurement.
Example / Practical context
A provider of project management software defines twenty typical user questions, for example about tools for small teams. These questions are regularly sent to several AI assistants. In 6 of 20 answers the brand is mentioned, which yields a share that is set against the mentions of competitors. If this share declines over the months, it is a signal to prepare the content more deliberately for AI answers.
Distinction from similar terms
Share of model is a metric for measuring visibility, not an optimization method. The measures used to try to improve that visibility fall under generative engine optimization and answer engine optimization.
In terms of content, the metric refers to mentions by an LLM, that is, a large language model. Compared to the classic share of voice, which measures presence in advertising or search, share of model shifts the focus to mentions within AI-generated answers.
Entdecke mehr
GEO — Generative Engine Optimization
GEO is the discipline of shaping content for visibility in AI answer engines — AI Overviews, Perplexity, ChatGPT Search, Claude. The goal is not the classic SERP click, but appearing as a cited source inside the generated answer.
LexikonGEO — Generative Engine Optimization Explained
What GEO is, how generative engines cite sources, and which factors raise citation likelihood. Honestly framed, without the hype.
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