White Label SEO Agency Drafting + Which AI Models To Use, With Real GoldieBench Scores

A white label SEO agency that uses AI for drafts has to pick models that produce clean, client-ready output on the first pass, because every edit eats into the turnaround clients expect.

GoldieBench does not test SEO itself, but its one-shot page builds are the closest public signal for landing pages and client deliverables.

Every score below was read on live goldiebench.com pages on 11 November 2026, and each one names the page it came from.

Prefer people over models? Talk to Julian's team for free, or pick a time and Book a free SEO strategy session yourself.

How GoldieBench Scores A Model

The methodology page sets the rules: one fixed prompt per task, no iteration and no best-of-several tries.

Each result must be a single self-contained HTML file that runs in a browser.

Scores are Julian's own 0 to 10 numbers, and the leaderboard ranks models by their average across every task they were scored on.

That makes it a test of first-draft quality, which is exactly what matters when a partner is producing work for many clients at once.

It says nothing about keyword research, link outreach or how AI search engines choose sources.

The Shortlist, By Overall Average

These averages come from the models page.

Fusion leads the same page at 8.59 across 47 tasks, but it is a multi-model panel rather than one model, so it sits outside this comparison.

All five models above were scored on 50 tasks, which keeps the averages comparable.

Scores On The Three Page Tasks

Page tasks are the nearest match to client landing pages and service pages.

Each figure is from that model's own page on the bench.

GPT-5.6 Sol posts the top Landing Page score in this group at 8.7.

Claude Opus 5 and Claude Opus 5.5 share the top Webos Page score at 8.7.

Kimi K3 is strong on two page tasks but drops to 6.5 on Aipbpromo Page, which shows why one average can hide uneven results.

Matching Models To White-Label Deliverables

Here is how we would split the drafting work, based only on the scores above.

Briefs, schema and monthly report summaries are not tested on the bench.

For those, pick the model your team reviews most easily, and check every fact against the client's own details.

Why Uneven Scores Matter For Agencies

A white-label partner might produce dozens of pages for dozens of clients each month.

A model that swings from 8.6 to 6.5 between similar tasks, as Kimi K3 does on the page tasks, needs closer review on every draft.

Steadier results across the three page tasks, as GPT-5.6 Sol and Claude Opus 5 show, mean fewer surprises at the editing stage.

None of this replaces a human edit.

What No Model Can Do For A White-Label Client

Models do not carry responsibility, and Google is clear that site owners are responsible for any company they hire, per its hiring guidance.

They also cannot judge policy risk on their own.

Google's spam policies cover scaled content abuse, meaning many pages made mainly to manipulate rankings, whatever tool produced them.

The same page's site reputation policy names white-label services as a source of third-party content and targets pages placed on a host site mainly to ride its ranking signals.

Google's AI optimisation guide adds that AI-assisted content must still meet Search Essentials.

Quality Rules For AI Drafts On Client Sites

• Every page answers a real customer question for that client, not a keyword variation.
• Facts, prices and service areas come from the client, never from the model.
• A person edits and approves every draft before it goes live.
• Paid link placements in any content carry rel="sponsored", following Google's outbound links guide.
• Nobody promises a ranking or an AI citation in the copy or the sales pitch.

Learning to run this process yourself is what the AI Profit Boardroom covers.

How To Test A Model On Your Own Client Work

Bench scores give you a shortlist, not a final answer.

Run a small trial before you switch a whole client roster to one model.

1. Pick three real client pages: a service page, a location page and a blog post.
2. Write one brief for each, with the client's facts and tone.
3. Give the same brief to two shortlisted models, once each, as the bench does.
4. Score each draft out of 10 for accuracy, structure and how much editing it needs.
5. Keep the model that needs the least editing for that page type.

Log the results with dates, because models change and today's leader may not hold next quarter.

The bench itself re-scores new models as they land, so check the live pages again before any big switch.

The Human And Agency Side

Models write drafts; the rest of white-label SEO is people work.

That means technical fixes on live sites, outreach to real editors, client calls and reports built on each client's Search Console data.

His about page, Julian Goldie's own published figures, counts 1,000+ campaigns in SEO and link building, plus 240+ Upwork clients with a 100% Job Success Score.

Goldie Agency's site describes its link building as manual outreach with no PBNs, alongside AI SEO and site audits.

Nobody can guarantee a #1 ranking, as Google says, and a good partner will say so before you sign.

You can learn the rest in the AI Profit Boardroom or hand it to Julian's team.

Also On Our Network

• Agent Operatorsthe nine operator steps for running a white-label SEO partner cleanly
• AI Income Deskwhether reselling SEO makes sense for a small business, with the risks
• AI Tool Verdictfive ways to handle reseller SEO, scored out of 10 with a verdict
• agentos.guidefive draft-only Agent OS prompts to prep a client for a white-label partner

Pick the model for each draft, keep a person on every edit, and book a free strategy session when you want a team behind your white label SEO agency work.