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Address verification tools · November 2026 Edition

Smarty vs Lob

Thirteen of fourteen models named Smarty first on the direct prompt; zero named Lob. Smarty was named by fourteen of the fourteen models and Lob by ten and Smarty carries 69 labels and Lob 23, so the shares are not directly comparable.

Smarty

endorsed leader

Named in one category this edition.

Lob

accepted challenger

Named in three categories this edition.

First-choice share73%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate1%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 7; printed, not drawn.
Labels6923A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Smarty reading right to left. Rank and label count are printed, not drawn.Melissa Global Address Verification was named alongside these two in twelve of the fourteen direct answers. Smarty vs PostGrid Address Verification · Smarty vs Loqate · PostGrid Address Verification vs Lob

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

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SmartyFirst choices, of fourteen modelsLob
Direct130
Paraphrase120
Comparative100
Budget-constrained101
Scale-constrained20
Negative301 against Smarty
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Smarty and Lob were named in the same answer sixty-eight times, of the 195 answers naming Smarty and the 330 naming Lob. In those answers Lob took the first choice two times and Smarty fifty.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Smarty and Lob stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
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
Smarty Lob first choice named as an alternative argued againstblank: not namedEach cell is one answer, Smarty on the left and Lob on the right.

The direct prompt

The plain question, one answer per model, grouped by where Smarty and Lob stood in it.

Smarty first, Lob an alternative

13 of 14 modelsLob was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSmarty alternatives: Melissa Global Address Verification, PostGrid Address Verification
Gemini 3.5 FlashSmarty alternatives: Lob, Loqate, Melissa Global Address Verification
Perplexity SonarSmarty alternatives: Loqate, Melissa Global Address Verification, PostGrid Address Verification
Grok 4.20Smarty alternatives: Lob, PostGrid Address Verification
Mistral SmallSmarty alternatives: Melissa Global Address Verification
DeepSeek V4 FlashSmarty alternatives: Lob, Loqate, Melissa Global Address Verification, PostGrid Address Verification
Llama 4 MaverickSmarty alternatives: Loqate, Melissa Global Address Verification, PostGrid Address Verification, Radar
Qwen 3.7 FlashSmarty alternatives: Experian Address Validation, Melissa Global Address Verification, PostGrid Address Verification
Kimi K2Smarty alternatives: Loqate, PostGrid Address Verification
GLM 4.7 FlashXSmarty alternatives: Melissa Global Address Verification, PostGrid Address Verification, Shufti Pro
MiniMax M2.5Smarty alternatives: Lob, Melissa Global Address Verification, PostGrid Address Verification
GPT-6 LunaSmarty alternatives: Loqate, Melissa Global Address Verification
Muse Glimmer 30BSmarty alternatives: Loqate, Melissa Global Address Verification, PostGrid Address Verification

Neither was the first choice, one was named

1 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5PostGrid Address Verification alternatives: ComplyCube, Experian Address Validation, Melissa Global Address Verification, Smarty

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Smarty leads by seventy-eight points.
Smarty78%#1 of 6
Lob0%#4 of 6
The full small business standing →
Mid-marketThe figures above
Smarty leads by seventy-one points.
Smarty73%#1 of 7
Lob2%#4 of 7
The full mid-market standing →
Enterprise
Smarty leads by thirty-two points.
Smarty32%#1 of 7
Lob0%#7 of 7
The full enterprise standing →

What the models said about Smarty

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“Smarty's international accuracy can trail its domestic performance in some cases” GPT-5.4 mini · negative prompt · soft negative
“Smarty is widely considered the top choice for mid-market companies needing reliable, lightning-fast API performance and straightforward pricing.” Gemini 3.5 Flash · direct prompt · first choice
“Widely considered the market leader for general API use. It is known for high accuracy, competitive pricing, and excellent CASS certification.” GLM 4.7 FlashX · comparative prompt · first choice
“This makes Smarty the cheapest predictable monthly option for US-focused companies that need real-time validation and autocomplete.” Muse Glimmer 30B · budget prompt · first choice

What the models said about Lob

No label in this category carried a quote.

Also compared

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.