Zero of fourteen models named Moz Local first on the direct prompt; zero named Uberall. Moz Local was named by thirteen of the fourteen models and Uberall by thirteen and Moz Local carries 48 labels and Uberall 36, so the shares are not directly comparable.
Named in two categories this edition.
Berlin, Germany, founded 2013. Named in three 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 October 2026 Edition, Moz Local and Uberall were named in the same answer sixty-five times, of the 133 answers naming Moz Local and the 133 naming Uberall. In those answers Uberall took the first choice eleven times and Moz Local nine.
| Model | DirectML | ParaphraseML | ComparativeML | Budget-constrainedML | Scale-constrainedML | NegativeML |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ML | ML | ||||
| GPT-5.4 mini | ML | ML | ||||
| Gemini 3.5 Flash | ML | ML | ML | |||
| Perplexity Sonar | ML | ML | ||||
| Grok 4.1 Fast | ML | ML | ML | ML | ML | |
| Mistral Small | ML | ML | ML | ML | ||
| DeepSeek V4 Flash | ML | ML | ML | ML | ||
| Llama 4 Maverick | ML | ML | ||||
| Qwen 3.7 Flash | ML | ML | ML | ML | ||
| Kimi K2 | ML | ML | ML | ML | ||
| GLM 4.7 FlashX | ML | ML | ML | |||
| MiniMax M2.5 | ML | ML | ML | ML | ||
| GPT-6 Luna | ||||||
| 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.
“Moz Local does not cover as many secondary directories as competitors... Acceptable for very simple needs, but insufficient for multi-location” Qwen 3.7 Flash · negative prompt · soft negative
“Outdated technology compared to direct-API solutions like Yext; lacks modern engagement features” Qwen 3.7 Flash · comparative prompt · soft negative
“too simplistic for multi-location B2B needs (no deep rank tracking or competitor analysis)” DeepSeek V4 Flash · paraphrase prompt · soft negative
“Moz Local is the strongest default choice because it is consistently described as one of the cheapest credible paid options” Perplexity Sonar · budget prompt · first choice
“The best local listings management platform for a company with a limited budget is Moz Local, which starts at $14/month” Llama 4 Maverick · budget prompt · first choice
“look for monthly, non-contract tools like BrightLocal or Moz Local, which are a fraction of the cost” Gemini 3.5 Flash · negative prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Uberall is positioned for "growth at scale" and uses request-based pricing for some plans ... but these are generally pricier” GPT-5.4 mini · budget prompt · soft negative
“like Yext or Uberall) are designed for large enterprises and franchises. They are expensive” Gemini 3.5 Flash · budget prompt · soft negative
“generally cost more and are better suited to larger budgets or multi-location enterprises” Perplexity Sonar · budget prompt · soft negative
“Uberall is positioned as built for multi-location brands to control, optimize and protect listings across 150+ directories.” Muse Glimmer 30B · scale prompt · first choice
“Choose Yext or Uberall for enterprise‑grade automation, compliance, and direct publisher integrations.” GLM 4.7 FlashX · comparative prompt · first choice
“Best for distributing data to a vast number of obscure directories/APIs. | Interface can be complex; pricier than BrightLocal.” Qwen 3.7 Flash · paraphrase 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.