Melissa vs Loqate
Zero of fourteen models named Melissa first on the direct prompt; one named Loqate. Melissa was named by fourteen of the fourteen models and Loqate by thirteen and Melissa carries 39 labels and Loqate 33, so the shares are not directly comparable.
Rancho Santa Margarita, United States, founded 1985. Named in one category this edition.
Named in one category 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 address verification tools page.
By framing
MelissaFirst choices, of fourteen modelsLoqate
Across every category in the October 2026 Edition, Melissa and Loqate were named in the same answer sixty-four times, of the 110 answers naming Melissa and the 98 naming Loqate. In those answers Loqate took the first choice seven times and Melissa five.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | | | |||
| Gemini 3.5 Flash | | | | | ||
| Perplexity Sonar | | | | |||
| Grok 4.1 Fast | | | | | ||
| Mistral Small | | |||||
| DeepSeek V4 Flash | | | | | ||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | | ||
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | ||||
| MiniMax M2.5 | | | | |||
| GPT-6 Luna | | | | | ||
| Muse Glimmer 30B | | |
Melissa Loqate first choice named as an alternative argued againstblank: not namedEach cell is one answer, Melissa on the left and Loqate on the right.The direct prompt
Loqate first, Melissa an alternative
1 of 14 modelsMelissa was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 of 14 modelsThe answer made no first choice from these two in this category.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.
By buyer segment
Melissa13%#2 of 8Loqate13%#3 of 8What the models said about Melissa
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“General cautions for all address verification tools (e.g., Smarty, Melissa, Quadient, Shufti Pro, SumSub, Veriff, DataFlow)” Grok 4.1 Fast · negative prompt · soft negative
“Melissa is generally heavier and more complex to implement. It is less of an "add-on" tool for a website” Qwen 3.7 Flash · comparative prompt · soft negative
“Melissa - Offers a comprehensive address verification API with features such as real-time address validation, standardization, and enrichment.” Llama 4 Maverick · paraphrase prompt · first choice
“The Industry Standards (High accuracy, widely used): Smarty (formerly SmartyStreets), Loqate (Onbuka), Melissa (DataBox).” Qwen 3.7 Flash · scale prompt · first choice
“Melissa offers the best free tier for small businesses needing additional validation features” MiniMax M2.5 · budget prompt · first choice
What the models said about Loqate
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“The Industry Standards (High accuracy, widely used): Smarty (formerly SmartyStreets), Loqate (Onbuka), Melissa (DataBox).” Qwen 3.7 Flash · scale prompt · first choice
“Best Overall for CRM Hygiene & Global Operations: Loqate (a GBG company) ... Loqate is the gold standard.” Gemini 3.5 Flash · direct prompt · first choice
“It's a strong alternative, especially for companies already using Google Maps or other location services.” Mistral Small · direct 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.