Comparison
LLM Listed vs Share of Model: define the work before you choose
Share of Model and LLM Listed offer different routes to AI visibility work. Share of Model presents a platform spanning perception, search visibility, assets, and activation, with support varying by package. LLM Listed is a done-for-you agency that agrees research and implementation responsibilities with each client.
Choose around the actual scope and ownership you need. A product name alone does not tell you whether software, services, or both are included.
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Disclosure
LLM Listed is an AI visibility agency, not a software tool. We track AI visibility across 650+ accounts with our own technology and data, and our team does the work to improve it. We are not a neutral reviewer. Here is how we put this comparison together.
At a glance
| Question | Share of Model | LLM Listed |
|---|---|---|
| Identity | Product presented at shareofmodel.ai, associated with Jellyfish | AI visibility agency |
| Published scope | Brand perception, search visibility, asset evaluation, and activation | Research and agreed content, technical, and authority implementation |
| Service model | Product and support arrangements vary by package | Done-for-you engagement with explicit responsibilities |
| Measurement | Evaluate selected modules, methods, and evidence | Client-specific method informed by tracking 650+ accounts |
| Pricing | Search AI Essentials listed at $799/month; Strategic Suite custom | Scope-based proposal, with no universal rate quoted here |
| Contract | Confirm term, support, exports, and renewal in the proposal | Confirm deliverables, approvals, ownership, and handover in the proposal |
Product identity and pricing checked against the official site and pricing page on November 11, 2026. The listed monthly price does not establish the terms of a particular purchase.
When is Share of Model worth investigating?
Investigate it when brand interpretation, asset evaluation, or campaign activation is part of the requirement alongside search visibility. Ask how the proposed modules connect to the decisions your team actually makes.
A useful demonstration follows a specific question: what did the answer say, which evidence supports the observation, and what action is proposed? Then inspect how your organization would approve and execute that action.
Do not assume every package has the same support. Request the precise division between product access, onboarding, strategic assistance, and implementation. A broader proposal may address needs that a self-serve label would obscure.
When is LLM Listed worth considering?
Consider our agency when the purchase is primarily a defined team and delivery scope for improving AI visibility. We track across 650+ accounts using our own technology and data, and we carry out agreed work rather than leave responsibilities implied.
That scope can connect prompt research with page changes, technical investigation, credible authority work, and repeated evidence review. The proposal should specify what is included and what remains with your own development, editorial, or compliance team.
Our AEO agency page describes the process. Our client work provides attributed examples, with different metrics and scopes that should not be combined into a promise of typical performance.
How should you compare perception and visibility?
An answer can describe a brand favorably without citing its website or recommending it for the buyer's specific need. A source citation can also appear without the brand being selected. Define each observation before comparing reports.
Ask how sentiment and attribute labels are assigned and how a reviewer can inspect an ambiguous example. A derived score can help summarize a sample, but the business should still understand the underlying evidence and the limits of the method.
The same discipline applies to our work. Account experience is useful context, not proof that every observation is accurate or that one methodology is universally best. Inspect the plan and the source records.
Can you use both?
You may be able to combine platform evidence with an external implementation program, subject to the actual contracts and access. Decide which system provides the baseline and which team owns research maintenance and actions.
Avoid conflicting metrics or duplicate work. If one report uses a different prompt set or denominator, explain that difference rather than choosing the most favorable number. A common decision record is often more useful than an extra dashboard.
Who should choose each approach?
Choose Share of Model when the configured modules and support arrangement suit the organization's measurement and activation workflow. Evaluate those capabilities on their own terms, rather than assume the whole product is a narrow tracker.
Choose LLM Listed when an agreed specialist team and implementation responsibility are the principal need. Ask us for deliverables, review owners, access requirements, and how the business can evaluate progress.
Frequently asked questions
Is Share of Model the same as a generic share metric?
No. This page concerns the product at shareofmodel.ai, which identifies its relationship with Jellyfish. Share of model is also used more generally as a visibility concept, so confirm the vendor and product when comparing documentation. A generic metric definition does not establish the features or ownership of this offering.
Is Share of Model self-serve software only?
Its current pricing distinguishes packages with different support arrangements. It would be inaccurate to describe the entire offering as purely self-serve without examining the selected proposal. Ask which people, modules, strategic support, and implementation responsibilities are included, then compare that operating model with the agency engagement you are considering.
Which approach is better for brand perception?
That depends on the research question, method, evidence, and people who will act. Define the attributes and claims you need to examine, then inspect actual answers and classifications. This guide has not performed a controlled accuracy test and does not rank either approach as universally superior for brand interpretation.
Should we choose software or a done-for-you agency?
Choose around responsibility. Software and associated support may fit a team with the capacity to operate the program. A done-for-you agency may fit when the organization needs external ownership of agreed tasks. Compare the actual deliverables, approvals, costs, and handover instead of relying only on the product or agency label.
How we compared
We reviewed the vendors' own product pages, public documentation, and pricing pages on November 11, 2026. This is a comparison of published offerings and buying decisions, not a hands-on benchmark or an accuracy test. Vendor statements describe their products; they are not independently verified performance results.
Software and agency engagements solve different operational needs. Some software includes recommendations, agents, content production, or implementation features. Check which people, services, approvals, and deliverables are included in the actual agreement instead of assuming that a product category tells you who will do the work.
Prices are snapshots in the stated currency and billing configuration. Confirm current models, limits, taxes, add-ons, renewal terms, and cancellation provisions with the vendor before purchasing. Where this guide omits a price, it has not established a comparable amount, rather than established that no price exists.
LLM Listed has not assigned numerical scores, created a neutral ranking, or tested every product against the same prompt set. The shortlist is organized around needs. Our own service appears as a disclosed done-for-you option. A stronger fit for one team may be a poor fit for another.
Last reviewed: November 11, 2026. Spotted an error? Email hello@llmlisted.com.
Discuss the operating model
Book a call about a defined implementation scope, or run a free scan. The AI visibility tools guide provides a wider shortlist by use case.