LLM Visibility Tools in 2026: 9 Trackers Compared on Citations and API Access

The unit of currency for brand visibility has changed. For two decades, marketers chased rankings and mentions, but in AI answers the metric that matters more is the cited link. As AI Overviews and chatbots insert themselves between you and your customer, being named is no longer enough: you need to be the source the engine trusts enough to link to, and LLM visibility tools exist to measure exactly that.

This guide compares nine LLM visibility tools (trackers that put your buyers' questions to ChatGPT, Gemini, Perplexity and the rest on a schedule, and log whether you are named and linked) on engines covered, published price and API access. Honeyb is our product and is listed first; every competitor price was read on the vendor's pricing page on 2 October 2026.

This is not an academic distinction. When an AI summary appears in search results, clicks on the traditional blue links fall from 15% to 8%, according to analysis reported by Silverback Marketing citing Pew Research. For a site that is not cited inside the answer, that is roughly half its clicks gone from the queries that trigger one.

Why citations are the metric to track

A mention is your brand name appearing in an AI-generated answer. A citation is a clickable link from that answer back to a page on your site. A mention buys some awareness; a citation is an endorsement that sends traffic and can be checked.

The unreliability of uncited claims is measurable. A September 2026 study from Washington University in St. Louis found that approximately 11% of verifiable claims in Google AI Overviews were unsupported by or even contradicted their cited sources. A citation at least gives the reader a path to check; an unlinked mention gives them nothing.

The answers are also volatile. Analysis from Wrodium suggests cited domains can change by 40 to 60% month over month for the same prompt, and SparkToro found less than a 1-in-100 chance that two runs of the same AI query return the same list of brands. A single spot-check is a photograph of a river: accurate for a moment and useless for planning.

Legacy brand monitoring and rank tracking were built to count names on social media and positions on a static results page. They rarely separate a citation from a mention, and they cannot see sources that ChatGPT and Gemini often leave unlinked. That gap is why a separate category of LLM visibility trackers now exists, built to query models at scale and log the cited URLs.

Nine LLM visibility tools compared

How we compared: for each tool we read the vendor's pricing page on 2 October 2026 and recorded the engines on its cheapest self-serve plan and its top tier, the cheapest monthly price, where the API sits and the cheapest way to try it. Prices are in US dollars, billed monthly, as each vendor shows them to a US visitor; LLM Pulse's dollar figures are its own approximate conversion.

Honeyb tracks up to eight engines daily and separates linked citations from unlinked mentions, with sentiment on each, then turns the gaps into recommendations and content. Plans run from $29 a month for one engine to $199 for all eight. Strength: the widest engine list at a self-serve price and an API sold per answer. Weakness: the $29 plan covers one engine and ten prompts, so serious tracking starts at the higher tiers.

Profound is the enterprise option, tracking up to nine engines with exports, all-time history and an API on Enterprise, which is now its only paid plan, at custom pricing. Strength: depth for large teams. Weakness: no published price, and the free trial covers three engines for seven days.

Peec AI is the value pick: $95 a month for 50 prompts daily on three of six models, with source analytics down to the URL and a citation-share metric. Strength: a low cost per answer for a 50-prompt daily plan. Weakness: Claude and the API are reserved for Enterprise.

Ahrefs Brand Radar covers ChatGPT, Perplexity, Gemini, Copilot, AI Overviews and AI Mode, and researches any brand across more than 449 million prompts in Ahrefs' database. Strength: competitor research with no prompt set to build, and API access on every paid plan. Weakness: no free trial, and your own prompts are metered by the check.

Semrush sells AI visibility inside its SEO + AI Search plans, from $199 a month with AI prompts tracked daily. Strength: one login for rankings and AI answers. Weakness: the API needs the $549 Advanced plan.

SE Ranking offers an AI Search add-on ($89 a month for 200 prompts) that tracks brand mentions, citations and sentiment across AI Overviews, AI Mode, Perplexity and ChatGPT, on top of its $129 Core plan. Strength: a 14-day trial with no card and API credits on Core. Weakness: four engines, with no Gemini or Claude.

AthenaHQ covers 11 models on its $295 Starter plan, including Claude, Grok and DeepSeek, with citation intelligence and content actions. Strength: a free Essential plan to start. Weakness: 3,600 responses a month across 11 engines is thin, and the API is an add-on priced on request.

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Scrunch is $250 a month for 125 prompts on four engines, with citation and source data on the entry plan. Strength: agent-traffic analysis and a seven-day trial. Weakness: Claude, Gemini and the query API are Enterprise-only.

LLM Pulse tracks mentions and citations on five engines from about $59 a month with weekly runs. Strength: the cheapest five-engine plan. Weakness: the API, Looker Studio connector and CLI start on the Scale plan, about $355 a month.

LLM visibility tools with an API

Five of the nine LLM visibility tools sell API access on a published plan, and two sell it without a subscription: Honeyb's prepaid credits and SE Ranking's $50 Wallet top-up. The other four keep it behind an Enterprise contract or a quote, which matters if the point is to put citation data into your own reporting rather than log in to someone else's dashboard.

The pricing models differ more than the table suggests. A plan-based API caps you at the plan's prompts, so pulling more answers means upgrading the whole subscription; a per-answer API charges for what you run. At Honeyb's $0.08, tracking 100 prompts weekly on four engines is about 1,730 answers a month, or roughly $139, and a one-off audit of 50 prompts on all eight engines is $32.

Before choosing, ask three things of any LLM visibility API: whether it returns the full answer text or only a score, whether each cited URL comes back with its position in the answer, and whether sentiment is scored per brand. A score alone cannot be audited, and an API that cannot be audited is a dashboard with extra steps. The Honeyb AI visibility API returns all three.

How to earn citations: the factors to work on

Measuring citations is the first step; improving them is the point. Research from Index Lab suggests that five core factors consistently influence whether an LLM will recommend and cite a brand. Understanding them is the basis of any plan to get cited by AI.

1. Mention frequency: how often your brand is discussed online in relevant contexts. Models learn from the open web, and brands that are discussed often are treated as prominent.

2. Source authority: where the mentions appear. A mention in a major industry publication outweighs a forum post, which is where digital PR and AEO (answer engine optimisation, or getting the robot to name you before it names anyone else) overlap.

3. Review sentiment: the tone of the conversation. Positive reviews on sites such as G2 and Trustpilot shape whether an engine recommends you.

4. Query fit: whether your content directly answers the questions buyers put to AI assistants.

5. Structured data: whether your pages use schema markup that tells crawlers, in machine-readable form, what the page is about.

For the wider market, including tools that track mentions without separating citations, see the 10 best AI visibility tools and the explainer on what AI visibility is.

The first number worth having is your own. Run the free AI visibility checker to see whether AI recommends your brand for your category's buyer questions today, and which competitors it names instead.