GPT-6.1 Sol vs Claude Sonnet 5.5 for SEO

Give both models the same product sheet, reference pages and client constraints. Ask for an audience, outline, facts to retain and unresolved questions. A useful answer separates information in the documents from information that still needs checking.

Watch details that often get lost during rewriting: prices, plan allowances, dates, country coverage and exceptions. An elegant outline that turns an optional feature into an included one is not ready for a writer. Count the corrections required rather than choosing on style alone.

Use public or anonymized data with dates, filters and units. The small dataset below was created to check reasoning; it is neither our traffic nor a test already performed on both models.

Ask for totals, weighted CTR and the change in clicks, followed by observations separated from hypotheses. Do not add countries or conversions that are absent from the file.

Expected result: 200 clicks from 2,000 impressions in A, versus 216 from 2,800 in B. Clicks rise by 8%, while overall CTR falls from 10% to 7.71%. Divide total clicks by total impressions rather than averaging the two page-level CTRs.

An answer reporting an overall decline in clicks is therefore wrong, even though CTR fell. An answer blaming a Google update invents a cause absent from the dataset. For a large export, prefer executed, inspectable calculations where the interface provides a suitable tool, then manually check a few rows.

Provide a short text, approved facts and a list of details that must not change. Request a clearer version for a defined audience. Check amounts, conditions and nuance before fluency; also count repetition and newly invented promises.

Then ask for a small revision. Does the model retain earlier constraints? Does it fix the requested passage or rewrite the whole document? This second step often reveals the real collaboration cost. Neither model name guarantees a more natural voice for your audience.

Sources: the Sol 6.1 model page, Sonnet 5.5 model page and OpenAI / Anthropic pricing, checked October 30, 2026. Both accept text and image input and produce text. API ceilings are not subscription or application limits.

At fixed billed token counts, 20,000 uncached input tokens and 2,000 output tokens cost US$0.06 with either model, before tools and other options. This is a rate calculation, not a measured cost for the same article: tokenization, reasoning, retries and tools can change consumption.

Long context changes the calculation. Above 272,000 input tokens, Sol applies double input/cache rates and 1.5 times output rates to the entire request. Sonnet 5.5 retains Standard rates across its million-token window. For 350,000 uncached input tokens and 2,000 billed output tokens, the theoretical totals are US$1.43 for Sol and US$0.72 for Sonnet, before tools and other options. That is not a reason to send unnecessary material.

Cache-read rates match, but cache writes and retention periods need a separate comparison. Processing modes and some regional options also affect billing. OpenAI additionally lists a 500,000-token default for Sol in Work and Codex: do not assume the full API ceiling in every application.

• Accuracy: are figures, citations and conditions preserved?
• Verifiability: can you trace a claim and reproduce its calculation?
• Discipline: does the answer flag missing information rather than fill gaps at random?
• Rework: how many follow-ups and human corrections are needed before acceptance?
• Total cost: include review time and, for API use, actual billed tokens and tools.

Record the exact model, application, allowed tools and effort. Sol defaults to medium in the API, Sonnet to high; even matching labels do not establish equal compute budgets. Repeat important cases and retain outputs so you can revisit your choice.

Be careful with older tables: the Sonnet 5.5 announcement compares against GPT-6 Sol, not GPT-6.1 Sol. Coding and general knowledge-work scores are not measurements of SEO brief quality. We therefore do not combine them into an artificial winner here.

ChatGPT Pro and Claude access are part of Rankerfox Premium. The exact version remains the one shown in your session's model selector. OpenAI offers Sol 6.1 through Work or Codex, rather than the selector in a regular ChatGPT conversation. The API rates above do not imply included API credits in Rankerfox.

For launch details and published evaluations, see our Sol 6.1 guide. The Claude family guide places Sonnet alongside Haiku and Opus. The AI tools and Rankerfox plans help with access choices, without replacing that model check.

Which costs less for writing?

The basic Standard token rates do not separate them. For a normal text, measure consumption, retries and review time. For a very long API input, context surcharges can change the comparison.

Can they read a Search Console screenshot?

Both accept images. A screenshot still omits rows, periods or dimensions; provide an export for complete analysis and reliable calculations.

Should both review every text?

Not necessarily. Keep a primary model for validated tasks and a second opinion for ambiguous or costly errors. Two similar answers do not establish that a fact is correct.