ChatGPT answers, unedited

Yes. What you’re describing is generally called AI visibility / LLM visibility tracking or GEO (Generative Engine Optimization) tracking.

A few tools specifically show the distribution of your brand’s appearances by AI model/platform, rather than just giving you one overall score:

• gumshoe.ai — probably the closest match if you care about model/version-level detail. It tracks 11 AI models and shows visibility by model, including variants such as Google Gemini 3 Flash, Claude Opus, GPT-5.4, DeepSeek Reasoner, Grok 4, etc. It also distinguishes pretrained vs. web-search variants and provides time-series tracking. Gumshoe AI
• zumihq.com — tracks up to 9 AI engines and gives mention rate, share of voice, and position by engine, with daily monitoring. Zumi
• synectgeo.io — has an explicit “Distribution by LLM” view. For example, its dashboard can show something like ChatGPT 37%, Gemini 28%, Claude 21%, Perplexity 14%. SynectGEO
• visimatrix.com — tracks 7 assistants and breaks out score, mention rate, and average rank per provider. VisiMatrix
• rankr.so — focuses on daily visibility, position, sentiment, and mentions across ChatGPT, Claude, Perplexity, Gemini, etc. Rankr
• ahrefs.com — a more established SEO-oriented option. It breaks mentions down by platform (ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews) and can benchmark competitors. Ahrefs

If you specifically mean model + version

That's an important distinction. A dashboard saying:

ChatGPT 42% / Gemini 31% / Claude 27%

isn't necessarily telling you what you want.

You may instead want something like:

Gumshoe appears to be the strongest fit for that level of granularity based on the current product descriptions. Gumshoe AI

One caveat: these tools generally run controlled prompts against the models and measure the resulting answers. They aren't literally measuring every conversation happening inside ChatGPT, Claude, etc. So “30% of appearances” means 30% of the tool's tracked/tested AI responses, not 30% of all real-world AI conversations.

If you tell me what you mean by “distribution”—e.g. % of total mentions by model, share of voice vs competitors, rank/position, or actual consumer exposure—I can narrow this down to the 2–3 tools that best fit and compare their pricing/data methodology.

Yes. What you’re describing is usually called AI visibility / LLM brand visibility tracking: a dashboard that runs a consistent set of prompts across AI models and shows how often your brand appears, where it ranks, sentiment, citations, and share of voice.

A few tools that specifically do this:

• gumshoe.ai — Probably the closest match if you want distribution across models and versions. It tracks 11 AI models and can break visibility down by model, including different model variants, plus competitors, personas, topics, sentiment, and trends. Gumshoe AI
• zumihq.com — Tracks up to 9 AI engines, including ChatGPT, Gemini, Claude, Perplexity, Copilot, Grok, DeepSeek, AI Overviews and AI Mode. Good if you want broad engine coverage. Zumi
• keysonar.com — Explicitly provides per-model breakdowns, including mentions, citations and top-1 positions. KeySonar
• nightwatch.io — Tracks ChatGPT, Claude, Gemini, Perplexity and Copilot, with mention volume, sentiment, share of voice and competitor monitoring. Nightwatch
• ahrefs.com — Good lightweight/free starting point. It reports total mentions and breaks them down by ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews. Ahrefs

If by "distribution" you mean this

For example, you want to see something like:

…and ideally drill down to model/version → prompt → exact response → competitor mentions → citations.

Then Gumshoe, Zumi, and Keysonar look particularly relevant. There are also newer platforms such as riffanalytics.ai that explicitly advertise cross-model visibility across ChatGPT, Gemini, Claude, Perplexity, DeepSeek and Grok. Riff Analytics

One important distinction: "ChatGPT" isn't necessarily one model/version from a measurement perspective. A serious tracker should tell you whether it's testing, for example, a specific GPT model, a web-search variant, or an AI-search surface. Otherwise the apparent distribution can be misleading.

If you tell me what you mean by “brand appearances” (e.g. mentions in answers, recommendations, citations, or share of voice), I can narrow this down to the 3 best tools and compare pricing, model coverage, API/export capability, and version-level granularity.

Yes. What you’re describing is usually called AI visibility, AI share of voice, or increasingly share of model: tracking how often your brand is mentioned/recommended/cited across AI assistants, broken down by model/engine. theStacc Repliq

A few tools currently do this:

• ahrefs.com — tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews, with breakdowns by platform, topics, and cited domains. Good if you already use Ahrefs.
• zumihq.com — particularly close to what you're asking for. It tracks up to 9 AI engines, including ChatGPT, Gemini, Claude, Perplexity, Copilot, Grok, DeepSeek, Google AI Overviews and AI Mode, and provides per-engine visibility and share-of-voice metrics.
• mentionhq.com — tracks ChatGPT, Claude, Gemini, Perplexity, DeepSeek and Grok, including mentions, positions, citations and competitors.
• synectgeo.io — has an explicit “Distribution by LLM” view, e.g. ChatGPT 37%, Gemini 28%, Claude 21%, Perplexity 14%, along with mentions and citations.
• searchprism.io — tracks ChatGPT, Claude, Gemini and Perplexity and shows per-platform visibility plus overall share of voice.
• rank.ai — tracks ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek and Google AI Overviews, with daily checks and share-of-voice reporting.

The distinction I'd make

If by “distribution of our brand appearances” you mean something like:

“Of all the times our brand appeared in AI answers, what percentage came from ChatGPT vs Gemini vs Claude vs Perplexity vs Grok, and how has that changed over time?”

then SynectGEO or Zumi look especially aligned with that use case.

If instead you mean:

“When people ask AI about our category, what percentage of answers mention us vs competitors, broken down by model/version?”

that's AI share of voice, and I'd prioritize a platform that lets you define a consistent prompt set and run it repeatedly. This matters because AI responses are nondeterministic, so a single query isn't a particularly reliable measurement; rigorous measurement uses multiple prompts and repeated runs. OrganiKPI Verity Score

One caveat: “model/version” is harder to measure than “AI platform.” A dashboard may say “ChatGPT,” but the underlying model, search/retrieval behavior, personalization, and product surface can change. Some tools query APIs rather than the consumer applications, so their “ChatGPT” result isn't necessarily identical to what a consumer sees in ChatGPT. NYFTY Labs

If you tell me which models/versions you care about (e.g. GPT-5.6 vs GPT-5, Gemini 3 vs 2.5, Claude Opus/Sonnet, etc.), I can compare the available tools specifically on model-level tracking, historical data, API vs consumer results, competitor share of voice, and pricing.

Yes. What you’re describing is usually called AI visibility / LLM visibility / Generative Engine Optimization (GEO) tracking.

A few tools specifically show where your brand appears across different AI models, including breakdowns by model:

• Ahrefs Brand Radar / AI Visibility Checker — tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode, etc. It can break down mentions by platform and track historical visibility and share of voice.
• Indexly — particularly close to what you described: share of voice by platform, daily mention counts, citation probability, sentiment, and trends across ChatGPT, Claude, Gemini, Perplexity, Grok, and AI Overviews.
• VisiMatrix — gives a provider-by-provider visibility score, mention rate, average rank, sentiment, and citations across ChatGPT, Gemini, Claude, Perplexity, DeepSeek, Mistral, and Grok.
• Rankr — shows visibility, position, sentiment, and mentions by individual model, with an overall comparison.
• SynectGEO — has almost exactly the visualization you're describing: “Distribution by LLM”, e.g. ChatGPT 37%, Gemini 28%, Claude 21%, Perplexity 14%.

One important distinction

If by “across different chat AI models and versions” you mean something like:

Our brand was mentioned 42% of the time in GPT-5.6, 31% in GPT-5.5, 18% in Claude Opus 4.1, etc.

—that's a more granular requirement than most AI-visibility products provide. Many aggregate at the platform/provider level (ChatGPT, Claude, Gemini, etc.) rather than exposing every underlying model/version.

If you're trying to build a dashboard for your company, I'd look for these dimensions:

Brand → Prompt → Model/version → Mentioned? → Position → Sentiment → Citation → Competitors

That lets you produce a distribution like:

genui{"chart":{"chartType":"bar","meta":{"title":"Illustrative brand appearance by AI model","description":"Example distribution showing how a brand's mentions could be distributed across model versions."},"layout":"vertical","xKey":"model","series":[{"dataKey":"share","label":"Share of appearances","valueSuffix":"%"}],"data":[{"model":"GPT-5.6","share":38},{"model":"Claude Opus","share":24},{"model":"Gemini","share":19},{"model":"Perplexity","share":12},{"model":"Grok","share":7}]}}

If you tell me what you mean by “brand appearances”—mentions in answers, recommendations, citations, or share of voice—I can point you to the 2–3 best tools for that exact metric, including whether they expose model/version-level data rather than just ChatGPT vs. Claude vs. Gemini.

Yes. What you’re describing is generally called AI visibility / LLM visibility / Generative Engine Optimization (GEO) tracking.

A few tools now specifically show how often your brand appears across different AI models, with model-by-model breakdowns:

• Gumshoe — probably closest to what you described. It tracks visibility across 11 AI models, including ChatGPT, Claude, Gemini, Perplexity, DeepSeek and Grok, and gives model-level visibility, competitor comparisons, sentiment, and trends. gumshoe.ai
• Riff Analytics — tracks brand mentions across ChatGPT, Perplexity, Gemini, Claude, DeepSeek and Grok in one dashboard. www.riffanalytics.ai
• rank.ai — tracks ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek and Google AI Overviews, including daily checks and share of voice. www.rank.ai
• Rankr — gives a particularly clean per-model table showing visibility, sentiment and mentions, e.g. ChatGPT vs. Claude vs. Gemini vs. Perplexity. rankr.so
• Ahrefs AI Visibility Checker — useful if you already use Ahrefs. It reports total mentions and a breakdown by ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews. ahrefs.com

One important distinction

If by “distribution” you mean something like:

“Of all the times our brand was mentioned by AI, what % came from GPT-5.4, GPT-5, Claude Opus, Gemini 3, Perplexity Sonar, etc.?”

then yes, some platforms can get close, but this is a more specific metric than ordinary “AI visibility.”

Most tools actually measure things like:

Brand appearance rate
→ % of tracked prompts where you're mentioned

Share of voice
→ your mentions vs. competitors

Position
→ how prominently you appear in the answer

Citation share
→ how often your site/content is cited

Per-model visibility
→ appearance rate separately for ChatGPT, Claude, Gemini, etc.

And increasingly they distinguish model/version + search-enabled variants, which matters because “GPT-5” in an API and what a user sees in ChatGPT aren't necessarily equivalent environments.

If your goal is marketing/brand intelligence, I'd shortlist Gumshoe, Riff, and rank.ai. If you tell me what you mean by “distribution” (e.g. % of mentions by model, share of voice by model, or historical trend by model/version), I can find the tool that matches it most precisely.

Yes. What you’re describing is usually called AI visibility / AI search visibility / GEO (Generative Engine Optimization) tracking.

A few tools are particularly close to your use case:

• Gumshoe — probably the closest match if you want brand appearances broken down by individual AI models and model versions. It says it tracks 11 AI models and can show model-level visibility, including examples such as GPT-5.4, Claude Opus, Gemini, Grok, DeepSeek, and Perplexity. gumshoe.ai
• Ahrefs AI Visibility Checker — good for a quick snapshot across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode. It reports total mentions and a platform-by-platform breakdown. ahrefs.com
• Indexly — more analytics-oriented: tracks mentions, citations, sentiment and share of voice across ChatGPT, Claude, Gemini, Perplexity, Grok and AI Overviews, with daily tracking. indexly.ai
• Birdeye Search AI — useful if you want enterprise reporting. Its Visibility Reports can break performance out by ChatGPT, Gemini, Perplexity, Claude, Grok, Google AI Mode and AI Overviews, with trends and competitor comparisons. support.birdeye.com
• Rank.ai — tracks ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek and Google AI Overviews, including daily mention/citation rates and share of voice. www.rank.ai

The important distinction

If by “distribution” you mean something like:

“Of all the times our brand appears in AI answers, what percentage is in GPT-5.4 vs Claude Opus vs Gemini vs Perplexity, and how does that change over time?”

then Gumshoe or Indexly look closest to what you want.

If you mean:

“How visible is our brand within each model, e.g. what percentage of relevant prompts produce a brand mention?”

then most of these platforms can do that too. That's arguably the more meaningful metric because raw appearance counts are heavily affected by how many prompts each platform is queried with.

For example, the ideal dashboard would look something like:

One caveat: “model” and “AI product” aren't always the same thing. ChatGPT, for example, can have different underlying models, search behavior, personalization, and system instructions. So if you're doing serious brand measurement, I'd look for a tool that lets you distinguish model + version + surface (e.g. ChatGPT Search vs regular ChatGPT) rather than simply reporting “ChatGPT.”

If you tell me which models/versions you care about (e.g. GPT-5.4, Claude Opus 4.1, Gemini 2.5 Pro, Perplexity Sonar, etc.), I can compare the current tools specifically on model/version granularity, historical tracking, share-of-voice, API access, and price.

Yes. What you’re describing is generally called AI visibility / AI search visibility / share of voice tracking: tools repeatedly run relevant prompts against different AI assistants/models and show how often your brand appears, where it ranks, and which competitors appear alongside it.

A few good options:

• Ahrefs AI Visibility Checker / Brand Radar — probably the most established option. It breaks visibility down by ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode, and can track mentions, citations, topics, and competitors. ahrefs.com
• Gumshoe — particularly interesting if you want model-level distribution. Its dashboard shows visibility across individual models such as GPT, Claude, Gemini, DeepSeek, Grok and Perplexity, plus persona/topic breakdowns and competitive rankings. gumshoe.ai
• Prism — tracks ChatGPT, Claude, Gemini and Perplexity and gives mention rate, position, sentiment, and share of voice by model. www.searchprism.iogumshoe.ai
• rank.ai — useful if you want to define your own customer prompts and monitor them daily across ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek and Google AI surfaces. www.rank.ainyftylabs.com
• Search Visibility — broader model coverage, including ChatGPT, Claude, Gemini, Perplexity, DeepSeek, Grok, Mistral, Llama and Qwen, with visibility-by-model and historical tracking. search-visibility.ai

If by "distribution" you mean something more specific

For example, you might want a dashboard like:

Gumshoe and Prism are closest to this out of the box. www.searchprism.iogumshoe.ai

One important caveat: these aren't measuring a literal census of all ChatGPT/Gemini/Claude conversations. They sample predefined or custom prompts and measure the resulting answers. Since LLM responses are stochastic, good platforms run many prompts repeatedly rather than treating one answer as representative. www.rank.ainyftylabs.com

If you're evaluating this for your company's marketing/brand team, I can also compare the top 5 tools specifically on model/version granularity, share-of-voice, historical trends, competitor tracking, APIs, and pricing and tell you which one I'd pick.

Yes. What you’re describing is generally called AI visibility / LLM visibility / GEO (Generative Engine Optimization) tracking.

The useful distinction is between tools that merely count mentions and tools that actually show how your brand’s appearances are distributed by model, model version, prompt, competitor, and time.

Tools worth looking at

• Gumshoe — probably closest to your description. It reports brand visibility across 11 AI models, with a model-by-model breakdown and time-series trends. It explicitly distinguishes variants such as Google Gemini 3 Flash, Claude Opus, DeepSeek Reasoner, GPT-5.4, Perplexity Sonar, etc. gumshoe.ai
• Ahrefs AI Visibility / Brand Radar — tracks ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode, with mentions, citations, topics, competitors, and historical tracking in Brand Radar. ahrefs.comwww.elmohq.comwww.getmint.ai
• rank.ai — tracks ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek and Google AI Overviews, including daily prompt-level checks and share of voice. www.rank.ai
• Elmo — interesting if you want more control. It's open-source/self-hosted and can track essentially any model through APIs/OpenRouter, including ChatGPT, Claude, Gemini, Grok, Mistral, DeepSeek, etc. www.elmohq.com
• GetMint — focuses on visibility, citations, sentiment and share of voice across major AI models, with filtering by competitor, market, language and intent. www.getmint.ai

If you specifically want a distribution like this

For example:

genui{"chart":{"chartType":"bar","meta":{"title":"Illustrative brand appearances by AI model","description":"Example of the kind of model-level distribution an AI visibility platform can provide. Values are illustrative, not measured data."},"xKey":"model","series":[{"dataKey":"appearances","label":"Brand appearances","valueFormat":"integer"}],"data":[{"model":"ChatGPT","appearances":420},{"model":"Gemini","appearances":310},{"model":"Claude","appearances":185},{"model":"Perplexity","appearances":140},{"model":"Grok","appearances":85},{"model":"DeepSeek","appearances":60}]}}

Then Gumshoe is the one I'd investigate first, because it gets unusually granular about the specific model/variant, rather than treating "ChatGPT" or "Gemini" as a single bucket. gumshoe.ai

One caveat: "brand appearances" can mean several different things. The better platforms let you distinguish:

1. Mention rate — % of prompts where you're mentioned.
2. Share of voice — your mentions vs. competitors.
3. Position — where you appear in the answer.
4. Recommendation rate — how often you're actually recommended.
5. Citation rate — how often your site/content is cited.
6. Sentiment — how the model describes you.
7. Model/version — e.g. GPT-5.x vs. another GPT variant.
8. Prompt/topic — why the model mentioned you.
9. Geography/language — whether visibility differs by market.

If by "distribution" you mean "What percentage of all the times our brand appears in AI answers comes from GPT-5.x vs Claude vs Gemini vs Perplexity, etc.?", that's a slightly more specific analytics requirement. I can compare the current tools specifically on model/version-level distribution, historical data, API access, exports, and pricing and tell you which one best fits that use case.

Yes. The category is usually called AI visibility tracking, LLM visibility monitoring, AEO (Answer Engine Optimization) tracking, or GEO (Generative Engine Optimization) tools. These tools measure how often and where your brand appears in answers from different AI assistants, often broken down by model. ahrefs.com

Some tools that provide model-by-model brand appearance distributions:

The kind of dashboard you’re describing usually looks like:

Brand: Acme

AI model distribution of appearances

ChatGPT       ███████████████  62%
Claude        ██████████       41%
Gemini        ███████          29%
Perplexity    █████████████    55%
Grok          █████            21%

Share of AI voice vs competitors
Sentiment by model
Top prompts triggering mentions
Cited sources/domains
Trend over time

A few caveats:

• These tools generally do not measure all real user conversations (those are private). They run controlled prompt sets against public AI interfaces/APIs and analyze the responses. www.mentionhq.com
• Results can vary significantly by prompt wording, geography, model version, whether web search is enabled, and whether the model has browsing or retrieval features.
• If you specifically care about model versions (for example, GPT-5.x vs GPT-4.x, Claude versions, Gemini versions), check whether the vendor exposes version-level tracking; many focus on the platform/model family rather than every underlying release. www.riffanalytics.ai

If you’re evaluating this for a brand/marketing team, I’d look for four metrics rather than just “mentions”:

1. Presence rate — % of tracked prompts where you appear
2. Share of voice — your mentions vs competitors
3. Position/rank — where you appear in the answer
4. Citation/source attribution — which sites are causing the model to mention you ahrefs.comrankr.so

Yes. What you’re describing is usually called AI visibility tracking, LLM visibility, or GEO/AEO monitoring.

These tools repeatedly run a set of relevant prompts against multiple AI platforms and show how often your brand appears, where it ranks, what competitors appear instead, and how visibility changes over time.

A few worth looking at:

• Gumshoe — probably closest to your exact question if you want distribution by model/version. It reports brand visibility across 11 AI models and can distinguish things such as GPT versions, Claude variants, Gemini variants, etc. It also shows competitor rankings, sentiment, and trends. gumshoe.ai
• OtterlyAI — strong cross-platform monitoring across ChatGPT, Gemini, Claude, Perplexity, Copilot, Google AI Overviews/AI Mode, with brand mentions and share-of-visibility reporting. otterly.ai
• Riff Analytics — specifically positions itself around seeing how often ChatGPT, Perplexity, Gemini, Claude, DeepSeek and Grok mention/rank your brand in one dashboard. www.riffanalytics.ai
• Rankr — simpler dashboard focused on visibility, position and sentiment across ChatGPT, Claude, Perplexity and Gemini. rankr.so
• Ahrefs AI Visibility Checker — useful for a quick baseline; it reports total mentions and breaks them down by AI platform, topics and cited domains/pages. ahrefs.com

One important distinction

If by “distribution across different chat AI models and versions” you mean something like:

Yes—Gumshoe and Riff are particularly aligned with that use case. The more sophisticated platforms are moving beyond simply counting mentions and are measuring which model/version, which prompt/persona, which competitors, position, sentiment, and citations.

One caveat: these aren't measuring the universe of actual ChatGPT/Gemini conversations. They generally create a controlled prompt set and repeatedly query the models, so the result is best interpreted as measured brand visibility under a defined set of representative queries, not “X% of all ChatGPT conversations mention us.” Otterly, for example, explicitly describes its methodology as sending queries to the platforms and aggregating the resulting answers. otterly.ai

If you're evaluating this for a brand/marketing analytics stack, I can also compare Gumshoe vs Profound vs Peec vs Otterly vs Riff specifically on model/version-level tracking, API access, historical data, share of voice, prompt volume, and pricing.

Yes. What you’re looking for is generally called AI visibility tracking, LLM visibility, or Generative Engine Optimization (GEO) tracking.

A few tools currently do this:

• Ahrefs AI Visibility Checker — probably the easiest starting point. It checks your brand across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews, and reports total mentions, platform breakdown, topics, and cited sources. ahrefs.com
• MentionHQ — specifically built around cross-model brand monitoring. It tracks ChatGPT, Claude, Gemini, Perplexity, DeepSeek, and Grok, including position, competitors, and cited URLs. www.mentionhq.com
• Rankr — gives a particularly useful dashboard view of visibility, position, sentiment, mentions, and share of voice by model. rankr.so
• Riff Analytics LLM Brand Visibility Tracker — tracks how often your brand is mentioned/ranked across ChatGPT, Claude, Gemini, Perplexity, DeepSeek and Grok, with competitor share-of-voice analysis. www.riffanalytics.ai
• Prism — combines AI visibility with traditional search data and shows model-by-model visibility and share of voice. www.searchprism.io

If by “distribution” you mean something more specific

For example, you might want a dashboard like:

That's basically AI share of voice / brand visibility by model.

One important caveat: model/version-level measurement is harder than platform-level measurement. AI responses are stochastic, so asking the same question repeatedly can produce different answers. Recent research argues that AI visibility should be treated as a distribution with uncertainty rather than a single fixed percentage. arxiv.org

So if you specifically need “How often does our brand appear in GPT-5.6 vs GPT-5.5 vs Claude Sonnet vs Gemini 2.x, etc.?”, I'd evaluate the tools differently from someone who just wants ChatGPT vs Gemini vs Perplexity.

If you tell me what you mean by “brand appearances” (mentions, recommendations, citations, rankings, sentiment, or all of them), I can narrow this down to the 2–3 best tools for your use case and compare pricing/features.

Yes. What you’re describing is generally called AI visibility, AI search visibility, or GEO (Generative Engine Optimization) tracking.

A few tools specifically provide a cross-model view of where a brand appears:

• Ahrefs Brand Radar / AI Visibility Checker — tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews, and others. It can break down total mentions by platform, prompts, competitors, and cited sources. ahrefs.com
• SearchInsight AI — particularly relevant if you want a dashboard showing visibility across ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI. www.searchinsight.ai
• Surva.ai — tracks brand mentions and historical visibility/share-of-voice across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews, including the actual responses. www.surva.ai
• DeepSmith — tracks mention rate, citation rate, and share of voice by AI engine, which is close to the "distribution of appearances" metric you're asking about. deepsmith.ai

The metric you're probably looking for

If, for example, you wanted to know:

…and then see how that changes by model/version, geography, prompt category, competitor, and date, that's absolutely a thing you can measure.

One important caveat: "model/version" is harder than "platform." Many tools report ChatGPT or Claude as a whole rather than reliably distinguishing something like a specific GPT version. Also, AI responses are nondeterministic, so a single query isn't a reliable measurement; repeated sampling is much more meaningful. Recent research specifically recommends treating AI visibility as a distribution with uncertainty rather than as a fixed percentage. arxiv.org

If you tell me what your brand is and which models/versions you care about, I can compare the available tools and tell you which one gives the closest thing to a "brand appearances by AI model/version" dashboard.

Yes. The category is usually called AI visibility tracking, LLM visibility monitoring, GEO (Generative Engine Optimization) analytics, or AEO (Answer Engine Optimization) tools. They measure how often a brand appears in answers from different AI systems and can break results down by model, prompt, competitor, and sometimes model version. www.measurellm.comwww.riffanalytics.ai

Some tools that do this:

The metric you’re describing is usually represented as something like:

• Brand appearance rate — % of tested prompts where your brand appears
• Share of voice — your share of all brand mentions in AI answers
• Model distribution — e.g., “40% of appearances come from ChatGPT, 25% Gemini, 20% Claude…”
• Rank/position — whether you appear as the first recommendation, among alternatives, etc.
• Citation share — which sources AI models use when mentioning your brand
• Version tracking — whether visibility changes after model updates (availability varies by vendor) www.brandbeacon.ai

A caveat: most tools do not have access to a model’s internal logs or every user conversation. They typically run a controlled set of prompts against available AI interfaces/APIs and estimate visibility from sampled outputs. www.reddit.com

If you mean specifically a dashboard like “our brand appears 62% in GPT-5, 48% in Claude Sonnet, 31% in Gemini, broken down by model version”, look for tools that support prompt-level tracking + model/version segmentation, because not all AI visibility platforms expose that granularity. www.measurellm.comwww.riffanalytics.ai

Yes. What you’re describing is usually called AI visibility tracking, LLM visibility, or Generative Engine Optimization (GEO) tracking.

A few tools now specifically measure how often a brand appears/recommends across AI systems:

• Ahrefs Brand Radar — tracks brand mentions across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews, and others. It gives platform-level visibility, prompts, competitors, and cited sources. ahrefs.com
• MeasureLLM — particularly relevant if you want a dashboard across ChatGPT, Gemini, Claude, Perplexity, Meta AI, etc., with visibility and competitor analysis. www.measurellm.com
• Surva.ai — tracks mentions/recommendations across ChatGPT, Claude, Gemini, Perplexity and AI Overviews, including prompts and citations. www.surva.ai
• GetMentioned — more focused on daily brand visibility and prompt-level tracking across ChatGPT, Gemini and Perplexity. www.getmentioned.co

But there's an important distinction

If by "distribution across different chat AI models and versions" you mean something like:

Our brand was mentioned in 38% of AI answers

ChatGPT GPT-5.6 — 42%
ChatGPT GPT-5.5 — 37%
Claude Opus — 29%
Claude Sonnet — 34%
Gemini — 51%
Perplexity — 44%
Grok — 21%

…and then showing how that distribution changes over time

That's a more specialized requirement. Most commercial AI-visibility tools report at the platform/engine level (ChatGPT vs. Gemini vs. Claude), rather than giving you clean statistical distributions for specific underlying model versions.

And there's a methodological reason: AI responses are stochastic. The same prompt can produce different answers at different times, so a meaningful measurement should run many samples rather than treat one response as definitive. Recent research specifically recommends treating AI visibility as a distribution with uncertainty rather than a single point estimate. arxiv.org

If you tell me what you mean by "distribution" (e.g. % of answers mentioning you, share of voice vs competitors, model/version breakdown, geographic distribution, or citations), I can identify the closest existing tool and tell you whether it actually supports that level of granularity.

If you mean tracking how often your brand appears in answers from different AI assistants/models (ChatGPT, Claude, Gemini, Perplexity, etc.) and across model versions, there are emerging AI visibility / LLM monitoring tools that do this. They are often described as LLM SEO, AI search optimization, or Generative Engine Optimization (GEO) platforms.

Some tools in this space include:

• Profound — Tracks brand visibility and mentions across AI search experiences, including citation and appearance analysis.
• Scrunch AI — Monitors how brands appear in AI-generated answers and provides optimization insights.
• Peec AI — Tracks brand presence and competitor visibility across AI answer engines.
• Otterly.ai — Provides AI search monitoring for prompts, rankings, and brand mentions.
• Writesonic AI Traffic Analytics — Includes AI search visibility tracking features.

Typical metrics these tools provide:

• Share of voice: percentage of AI responses where your brand appears vs. competitors
• Appearance distribution by model: e.g., ChatGPT vs. Claude vs. Gemini vs. Perplexity
• Model/version tracking (where supported): changes after model updates
• Prompt-level visibility: which user questions trigger your brand
• Sentiment/context: whether the mention is positive, neutral, or negative
• Citation tracking: which websites/sources AI systems rely on when mentioning you

A few caveats:

• There is no universal API or dashboard that has complete coverage of every AI model/version because providers expose different amounts of information.
• Model version attribution can be tricky: many consumer AI products silently update models or route queries dynamically.
• The most reliable approach is usually a prompt monitoring program: define hundreds/thousands of representative queries, run them periodically across models, and measure brand presence.

If you mean internal enterprise analytics (e.g., “we want a dashboard showing our brand’s share of AI answers by model/version”), you may also want to look at building a custom pipeline using model APIs plus a prompt evaluation framework rather than relying only on third-party GEO tools.

Yes. The category you’re looking for is usually called AI visibility tracking, AI search visibility, or Share of AI Voice (SAOV).

A few tools currently do this:

• urlAhrefs AI Visibility Checker / Brand Radarturn0search0 — tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and others. It can show total mentions and breakdown by platform, plus competitors, prompts, and cited sources.
• urlSearch-Visibility.aiturn0search2 — particularly broad model coverage: ChatGPT, Claude, Gemini, DeepSeek, Grok, Perplexity, Mistral, Llama, Qwen, etc. It explicitly provides visibility by model and historical trends.
• urlSurva.aiturn0search1 — monitors ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews, with prompt tracking, citations, and visibility analysis.
• urlHubSpot AI Visibilityturn0search3 — more marketing/SEO-oriented; provides an AI visibility score and comparison against competitors across ChatGPT, Perplexity and Gemini.

If by “distribution” you mean something more specific

For example, you might want a dashboard like:

That's possible, but there's an important distinction: most commercial tools measure platform/answer-engine visibility rather than giving you a statistically rigorous distribution across every underlying model version.

That's because AI responses are stochastic—the same prompt can produce different answers at different times. Recent research specifically argues that AI-visibility metrics should be treated as sample distributions with uncertainty, rather than a single definitive visibility score. arxiv.org

So if your goal is “What percentage of all our AI mentions comes from GPT vs Claude vs Gemini, and how does that change by model/version over time?”, I'd look for a tool with raw response-level data + model/version metadata, rather than just an AI visibility score.

If you tell me what your brand is and which models you care about, I can identify the best tool for exactly that distribution and compare the available options.

Yes. A growing category of tools is designed to measure AI brand visibility (sometimes called LLM visibility, AI search visibility, or AI mention share). These tools track how often your brand appears in responses from models like ChatGPT, Claude, Gemini, Perplexity, and others, and often break results down by model and prompt set.

Some of the better-known options include:

The types of metrics these platforms commonly provide are:

• Brand appearance rate (e.g., your brand appears in 42% of relevant prompts)
• Share of voice versus competitors
• Breakdown by model, such as GPT-5.5 vs. Claude Sonnet vs. Gemini vs. Perplexity
• Breakdown by prompt category (informational, commercial, local, product recommendations, etc.)
• Citation sources used when models provide references
• Historical trends showing whether visibility is increasing or decreasing

One important caveat is that these tools generally do not have access to OpenAI's internal telemetry. Instead, they continuously run large prompt sets against public APIs or web interfaces and aggregate the responses. That means they're measuring observed behavior under their testing methodology, not the complete distribution of what every user sees.

If your goal is specifically "What percentage of ChatGPT responses mention my brand compared with Claude and Gemini?", these platforms can estimate that from sampled prompts.

If your goal is "How many real users actually saw my brand inside ChatGPT?", there isn't a public tool that can provide that. Only the platform operators have access to aggregate usage data, and they don't expose brand-level appearance statistics.

Could you share what you're trying to measure?

• Marketing/SEO (AI visibility)
• PR/brand monitoring
• Product recommendations inside LLMs
• API usage analytics
• Something else

Yes. There are now a few categories of tools that track or estimate brand visibility across AI assistants, though no tool has perfect access to every model's internal outputs. They generally work by prompting models at scale and measuring how often your brand appears, in what context, and with what sentiment.

Some of the better-known options include:

Typical dashboards include:

• Share of voice (% of prompts where your brand appears)
• Ranking position (first recommendation, second, etc.)
• Which competitors appear alongside you
• Citation sources used by AI
• Sentiment and messaging
• Changes over time
• Differences between models

Model/version breakdown

Whether you can see results by specific model version depends on the platform.

Many tools let you compare outputs across assistants such as:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Copilot

Some also distinguish between model variants (for example, different generations or reasoning models) if those APIs are available. However, very granular version-level reporting (such as every dated model snapshot) is often limited because providers update models frequently and don't always expose stable version identifiers.

If you're looking for enterprise-grade monitoring

Platforms like Profound are designed specifically for marketing teams and usually provide:

• Prompt libraries
• Brand visibility over time
• Competitor benchmarking
• Geographic comparisons
• AI citation analysis
• Alerts when visibility changes

If you want to build your own

Many companies also create internal dashboards by:

1. Maintaining a library of hundreds or thousands of representative prompts.
2. Running those prompts periodically against APIs from multiple AI providers.
3. Recording:
   • whether the brand appears,
   • its position in the response,
   • cited sources,
   • competitors mentioned,
   • response quality.
4. Visualizing trends in a BI tool such as Tableau or Power BI.

This approach gives complete control over the prompts and metrics, though it requires engineering effort and API costs.

If your goal is marketing/SEO for AI search (often called GEO or LLM optimization), I can also recommend which platforms are strongest for enterprise, mid-market, or startup budgets.

Yes. A small but growing category of tools now measures AI brand visibility (sometimes called LLM share of voice, AI search visibility, or AI citations). They track how often your brand appears in responses from models like ChatGPT, Claude, Gemini, Perplexity, Copilot, and others.

Some of the better-known options include:

Most of these platforms can show:

• Your brand's share of voice versus competitors.
• Which prompts trigger mentions of your brand.
• How frequently your brand is recommended.
• Which sources or websites the AI appears to rely on.
• Changes over time after PR, SEO, or content updates.

If you're specifically asking about model versions

This is more difficult.

Very few tools can reliably tell you something like:

• GPT-5.5: 42% mention rate
• GPT-5: 38%
• Claude Opus 4: 51%
• Gemini 3: 47%

The reasons include:

• Many providers don't expose historical versions through public APIs.
• ChatGPT users are often automatically routed to updated models.
• Responses vary due to randomness and personalization.

Instead, most platforms report at the assistant level, such as:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Microsoft Copilot

Some enterprise platforms let you pin specific API models (for example, a particular OpenAI or Anthropic model) and benchmark those separately if you're running your own evaluation suite.

If you need detailed model-by-model analytics

If your goal is rigorous benchmarking (for example, "How often does GPT-5.5 recommend us versus Claude Opus?"), many companies build a custom evaluation pipeline using model APIs. They:

1. Maintain thousands of representative prompts.
2. Run those prompts across fixed model versions.
3. Record mentions, rankings, sentiment, and citations.
4. Produce dashboards showing share of voice by model, version, geography, and topic.

This approach gives much finer control than most off-the-shelf AI visibility platforms.

If you're evaluating vendors, I can also recommend which tools are strongest for:

• enterprise brands,
• startups/SaaS,
• ecommerce,
• or agencies managing multiple client brands.

Yes. A category of tools has emerged specifically for tracking AI visibility or LLM brand presence—essentially the equivalent of SEO rank tracking, but for ChatGPT, Claude, Gemini, Perplexity, and other AI assistants.

Some well-known platforms include:

What these tools typically measure

Most of them let you see things like:

• Share of voice across AI platforms
• Frequency your brand is mentioned
• Whether you're recommended versus competitors
• Citation sources used by AI
• Prompt-by-prompt performance
• Trends over time
• Geographic or language differences (on some platforms)

About model/version breakdowns

A true breakdown like:

is less common.

Most vendors compare platforms (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.) rather than every individual model version. There are a few reasons:

• Public-facing products often update models behind the scenes.
• Different users may be routed to different versions.
• Providers don't always expose the exact model version consistently.

Some enterprise platforms let you run your own prompt sets against specific model APIs (for example, GPT-5.5 vs. another OpenAI model) if you connect your own API keys, giving you more granular comparisons.

If you want the most detailed analytics

For enterprise marketing teams, a common setup is:

1. Maintain a library of hundreds or thousands of representative prompts.
2. Execute those prompts on a schedule against each target model/API.
3. Record mentions, rankings, citations, sentiment, and competitors.
4. Build dashboards (often in a BI tool) showing share of voice by model, prompt category, geography, and time.

That approach provides a true model-by-model view instead of relying only on consumer-facing AI apps.

If your goal is brand monitoring for a company, SEO/GEO optimization, or competitive intelligence, I can also recommend which tools are strongest in each area.

Yes. A new category of tools—often called AI visibility, LLM visibility, or AI search observability platforms—does exactly this. They monitor how often your brand appears across AI assistants, compare visibility by model, and track changes over time. wellows.comtrackmyvisibility.com

The strongest platforms typically show:

• Brand appearances by AI model (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.)
• Breakdown by model/version where supported (for example, GPT-5 vs GPT-4.x if the platform can consistently query those versions)
• Share of voice versus competitors
• Prompt-level performance (which prompts mention your brand)
• Citations and source URLs used by AI
• Sentiment and positioning (recommended, neutral, or negative)
• Historical trends over days, weeks, or months. wellows.com

Some notable options include:

One important limitation: no tool has direct access to the internal usage or recommendation statistics of proprietary AI models. Instead, these platforms repeatedly run large libraries of prompts against each model and measure:

• how often your brand appears,
• where it ranks,
• what sources are cited,
• how results change over time.

That means their metrics are statistically useful but are estimates based on sampled prompts rather than official data from OpenAI, Anthropic, Google, or others. trackmyvisibility.com

If your goal is specifically to see something like:

Brand X

• ChatGPT GPT-5: 34% appearance rate
• ChatGPT GPT-4.1: 27%
• Claude Opus: 41%
• Gemini 3: 18%
• Perplexity Sonar: 52%

there are platforms working toward that level of model-specific reporting, though support depends on whether those model versions are publicly queryable and stable over time. wellows.comwww.riffanalytics.ai