Zero of fourteen models named Moz Local first on the direct prompt; two named Semrush Local. Both were named by all fourteen models and Moz Local carries 50 labels and Semrush Local 47, so the shares are not directly comparable.
Named in three categories this edition.
By Semrush, Boston, United States, founded 2008. Named in two categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the local listings management page.
Across every category in the November 2026 Edition, Moz Local and Semrush Local were named in the same answer eighty-two times, of the 141 answers naming Moz Local and the 122 naming Semrush Local. In those answers Semrush Local took the first choice two times and Moz Local twenty-three.
| Model | DirectML | ParaphraseML | ComparativeML | Budget-constrainedML | Scale-constrainedML | NegativeML |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ML | ML | ML | |||
| GPT-5.4 mini | ML | ML | ML | |||
| Gemini 3.5 Flash | ML | ML | ML | |||
| Perplexity Sonar | ML | ML | ML | |||
| Grok 4.20 | ML | ML | ML | ML | ML | |
| Mistral Small | ML | ML | ML | |||
| DeepSeek V4 Flash | ML | ML | ML | ML | ||
| Llama 4 Maverick | ML | ML | ||||
| Qwen 3.7 Flash | ML | ML | ||||
| Kimi K2 | ML | ML | ML | ML | ML | |
| GLM 4.7 FlashX | ML | ML | ML | ML | ||
| MiniMax M2.5 | ML | ML | ML | |||
| GPT-6 Luna | ML | |||||
| Muse Glimmer 30B | ML | ML | ML |
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Why to avoid: - Email overload — Users report excessive, unmanageable notifications” GLM 4.7 FlashX · negative prompt · hard negative
“Who should avoid: Agencies, enterprises, or anyone needing fast syncing/automation.” Grok 4.20 · negative prompt · hard negative
“Other platforms like BrightLocal and Moz Local have also received some negative feedback, but they also offer useful features” Llama 4 Maverick · negative prompt · soft negative
“The best local listings management platform for a company with a limited budget is Moz Local, as it is the most affordable option” Llama 4 Maverick · budget prompt · first choice
“Moz Local is best for affordable automated listing distribution, offering the best entry price with solid core features.” Claude Haiku 4.5 · budget prompt · first choice
“For a single-location company on a tight budget, Moz Local at $16/month is the sweet spot” DeepSeek V4 Flash · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“more cost-effective, but usually better for smaller footprints or simpler needs than a typical mid-market B2B rollout” GPT-5.4 mini · direct prompt · soft negative
“generally more expensive or more enterprise-oriented, so usually not ideal for a limited budget” GPT-5.4 mini · budget prompt · soft negative
“the per-location cost can be difficult to justify if listings are your only requirement” Perplexity Sonar · negative prompt · soft negative
“BrightLocal and Semrush tend to offer the best balance of features, control, and affordability for mid-market companies.” Claude Haiku 4.5 · direct prompt · first choice
“I'd recommend starting with SOCi or SEMrush” MiniMax M2.5 · direct prompt · first choice
“Combines listings with broader SEO tools (rank tracking, audits). Great if your team already uses Semrush.” Grok 4.20 · scale prompt · alternative
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.