GEO Specialist Work + Which AI Models To Use For Briefs, Schema And Landing Pages (Real GoldieBench Scores)

A GEO specialist now leans on AI models for the grunt work behind AI-search visibility: drafting briefs, structured data and the landing pages that AI answers end up citing.

So which models are worth handing that work to?

This page uses only scores published on GoldieBench, quoted with the page each one comes from, then covers the part no model can do for you.

For the human side, book a free strategy session with Julian's team.

What GoldieBench measures, and what it doesn't

The methodology page says every model gets the same fixed prompt, one shot, and must return a single self-contained HTML file.

Scores are Julian's own 0–10 judgements from his head-to-head guides.

That makes the bench a good read on building pages and interfaces.

It doesn't score brief writing, schema accuracy or outreach drafts directly.

So treat the page-building scores below as the closest proxy, and check any SEO output by hand.

The landing page task: the closest match to GEO work

GoldieBench's Landing Page task asks for a modern marketing landing page in one shot.

The task page lists 26 models tested, 21 of them scored, and an average of 8.11/10.

Four models share the top score here, so the choice between them comes down to how they handle your own brief.

A gap of a few tenths on one task is small; run your own prompt through two of them before committing.

Overall averages from the leaderboard

The GoldieBench leaderboard ranks models by average score across every task they ran.

Fusion sits at #1 with an 8.59 average.

Claude Opus 5 is #2 at 8.27, and GPT-5.6 Sol is #4 at 8.16, tagged "best at Pages".

GLM-5.2 is also tagged best at Pages, with a 7.77 average.

Gemini 3.6 Flash averages 7.08 across 50 tasks.

For GEO, the "Pages" tag matters more than the overall rank, because most of the job is pages rather than games or simulations.

Second page task: a promo build

The AIPB Promo task, also in the Page category, averages 7.48/10 with Qwen 3.8 listed as the winner.

GPT-5.6 Sol scored 8.3/10 there.

Claude Opus 5's model page lists 8.3 on the same task and 8.7 on the Webos page task.

Across both page tasks, GPT-5.6 Sol and Claude Opus 5 stay near the top, which makes them steady picks for page drafts.

Matching models to the tasks behind GEO

A small-business example: a garden design studio

1. Pick two models from the Landing Page table, say GPT-5.6 Sol and Fusion.
2. Give both the same brief: a service page for "small courtyard garden design", written from the studio's own project notes.
3. Compare the drafts for invented claims and cut anything the studio can't back up.
4. Ask one model to draft LocalBusiness JSON-LD from the contact page, then check every value.
5. Publish only the human-edited version, and track it in Search Console's AI report.

How to run your own two-model test

The bench tells you who builds good pages from a fixed prompt; your own test tells you who handles your business.

Write one brief that includes your real service details, three customer questions and two facts you can prove.

Send it, unchanged, to two models from the tables above.

Score each draft out of 10 on three things: did it answer the questions, did it invent anything, and would a customer trust it.

Keep the better draft, then rewrite the opening in your own words with a first-hand detail.

That's the same one-prompt, same-rubric idea the bench uses, applied to your own pages.

What the platforms say the content needs

The model only drafts; the page still has to meet each platform's bar.

Google's AI optimisation guide asks for content with a unique point of view rather than a summary of what's already out there.

It also says Google Search ignores llms.txt files, so don't ask a model to generate one for Google.

OpenAI says ChatGPT search needs OAI-SearchBot access, and Bing asks for clearly defined entities.

A model can draft all of it, but only a person knows which claims are true.

Where the GEO specialist takes over from the model

Models are quick at drafting; they're weak at judgement.

A specialist decides which pages matter, which bots to allow, how to earn genuine mentions and what to measure.

Google's guide to hiring an SEO now asks whether a provider's GEO advice matches Google's AI guidance, and says no one can guarantee a #1 ranking.

That's the human part of the job, and it's where Goldie Agency fits: it describes itself as an SEO, GEO, AEO and link building agency, with link building done through "manual outreach, no PBNs".

Julian's own published numbers include 1,000+ SEO and link building campaigns and 425K+ YouTube subscribers.

If you'd rather learn AI SEO yourself, the AI Profit Boardroom covers model workflows for this inside the Agent OS.

Measuring whether the model-built pages worked

Use first-party data, not chatbot screenshots.

Google's generative AI reports in Search Console show impressions and pages inside AI features.

Bing's AI Performance report counts citations in Copilot.

Our own observation: ChatGPT visits usually show chatgpt.com as the referrer in analytics.

Compare each new page against its own baseline after a few weeks.

For a related read, see how an AEO specialist uses the same toolkit.

Also On Our Network

• Agent Operatorsthe eight-step run-sheet for a GEO specialist engagement, with robots.txt lines
• AI Income Deskwhether a small business should hire a GEO specialist, and what to ask first
• AI Tool Verdicta scorecard rating DIY, freelance GEO specialists and agencies out of 10
• agentos.guidefive draft-only Agent OS prompts that do the GEO specialist groundwork

Pick a page-strong model from the bench, edit every draft by hand, and book a free strategy session or join the AI Profit Boardroom for the judgement calls only a geo specialist makes.