Index › IT › Identity and access › Identity verification › Sumsub vs Veriff
Identity verification · November 2026 Edition

Sumsub vs Veriff

Five of fourteen models named Sumsub first on the direct prompt; zero named Veriff. Both were named by all fourteen models and Sumsub carries 46 labels and Veriff 43, so the shares are not directly comparable.

Sumsub

accepted challenger

Named in two categories this edition.

Veriff

accepted challenger

Named in one category this edition.

First-choice share21%11%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate11%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 11; printed, not drawn.
Labels4643A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Sumsub reading right to left. Rank and label count are printed, not drawn.Persona was named alongside these two in ten of the fourteen direct answers. Sumsub vs Persona · Sumsub vs Didit · Sumsub vs iDenfy

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 identity verification page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SumsubFirst choices, of fourteen modelsVeriff
Direct50
Paraphrase641 against Sumsub
Comparative21
Budget-constrained012 against Sumsub · 1 against Veriff
Scale-constrained01
Negative002 against Sumsub · 2 against Veriff
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, Sumsub and Veriff were named in the same answer ninety-four times, of the 144 answers naming Sumsub and the 132 naming Veriff. In those answers Veriff took the first choice fourteen times and Sumsub sixteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Sumsub and Veriff 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
Sumsub Veriff first choice named as an alternative argued againstblank: not namedEach cell is one answer, Sumsub on the left and Veriff on the right.

The direct prompt

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

Sumsub first, Veriff an alternative

5 of 14 modelsVeriff was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSumsub alternatives: Entrust IDV, Trulioo, Veriff
Mistral SmallComplyCube, Sumsub alternatives: Persona
DeepSeek V4 FlashPersona, Sumsub alternatives: Alloy, Middesk
Kimi K2Persona, Sumsub alternatives: Trustpair, Veriff
Muse Glimmer 30BSumsub alternatives: Persona, Trulioo, Veriff

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Trulioo alternatives: Middesk, Persona, Sumsub, iDenfy
Gemini 3.5 FlashPersona alternatives: Middesk, Sumsub
Perplexity SonarTrulioo alternatives: Middesk, Persona, Sumsub, Veriff
GLM 4.7 FlashXComplyCube, iDenfy alternatives: Jumio, Sumsub
MiniMax M2.5Trustpair alternatives: Incode Technologies, Jumio, Socure, Sumsub

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
Grok 4.20Shufti Pro alternatives: Persona, Socure
Llama 4 Maverickno first choice
Qwen 3.7 FlashiDenfy alternatives: ComplyCube, Middesk, Persona
GPT-6 LunaPersona alternatives: Middesk

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
Sumsub leads by four points.
Sumsub19%#2 of 10
Veriff15%#3 of 10
The full small business standing →
Mid-marketThe figures above
Sumsub leads by nine points.
Sumsub21%#1 of 11
Veriff11%#4 of 11
The full mid-market standing →
Enterprise
Sumsub leads by two points.
Sumsub14%#2 of 11
Veriff12%#4 of 11
The full enterprise standing →

What the models said about Sumsub

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

“One of the lowest-rated verification platforms - Constant rejection of valid verification documents” DeepSeek V4 Flash · negative prompt · hard negative
“independent testing flagged a fraud trade-off: Sumsub accepted 80% of fake documents in KYC AML Guide testing, the highest rate in the pool” Muse Glimmer 30B · paraphrase prompt · soft negative
“often outperforming pricier options like Jumio, Onfido, or Sumsub in value” Grok 4.20 · budget prompt · soft negative
“Sumsub stands out as a comprehensive solution, offering both robust KYC document verification and advanced selfie verification” Mistral Small · paraphrase prompt · first choice
“Sumsub and ComplyCube are the top choices due to their strong compliance features, scalability, and positive user reviews” Mistral Small · direct prompt · first choice
“I recommend Sumsub as the top choice for a mid-sized B2B company needing robust KYC document and selfie verification.” Grok 4.20 · paraphrase prompt · first choice

What the models said about Veriff

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

“Veriff (Trustpilot: ~1.3/5) - Users report the system frequently gets stuck at the selfie step” DeepSeek V4 Flash · negative prompt · hard negative
“Higher price point but reliable for businesses needing more robust verification” Kimi K2 · budget prompt · soft negative
“Data breach exposing 8,583 Total Wireless customers; Vague rejection reasoning” Kimi K2 · negative prompt · soft negative
“Given your size, Persona, 1Kosmos, or Veriff are strong starting points worth evaluating in a pilot.” DeepSeek V4 Flash · scale prompt · first choice
“I'd generally recommend Veriff as the default choice for document + selfie verification” GPT-5.4 mini · paraphrase prompt · first choice
“Choose Veriff for broad international consumer onboarding and fraud prevention.” Perplexity Sonar · comparative prompt · first choice
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.