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Candidate assessment · November 2026 Edition

EmployTest vs Harver

Zero of fourteen models named EmployTest first on the direct prompt; one named Harver. EmployTest was named by eleven of the fourteen models and Harver by six and EmployTest carries 15 labels and Harver 11, so the shares are not directly comparable.

EmployTest

accepted challenger

Named in one category this edition.

Harver

accepted challenger

Named in three categories this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 12; printed, not drawn.
Labels1511A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, EmployTest reading right to left. Rank and label count are printed, not drawn.TestGorilla was named alongside these two in twelve of the fourteen direct answers. TestGorilla vs EmployTest · TestGorilla vs Harver · Criteria Corp vs EmployTest

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 candidate assessment page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
EmployTestFirst choices, of fourteen modelsHarver
Direct01
Paraphrase00
Comparative00
Budget-constrained20
Scale-constrained00
Negative001 against Harver
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.

Every model, every framing

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

The direct prompt

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

Harver first, EmployTest not the choice

1 of 14 modelsEmployTest was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Criteria Corp, Harver, Plum alternatives: JobCannon, SHL, TestGorilla, Vervoe, Wonderlic

Neither was the first choice, one was named

2 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.20Criteria Corp alternatives: Harver, TestGorilla, Thomas International
Llama 4 MaverickThomas International alternatives: Codility, EmployTest, HackerRank, Weirdly

Neither was named

11 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniCriteria Corp alternatives: HighMatch, TestGorilla, Testlify, The Predictive Index
Gemini 3.5 FlashTestGorilla alternatives: Criteria Corp, The Predictive Index, Vervoe
Perplexity SonarCriteria Corp alternatives: Codility, TestGorilla, Vervoe
Mistral SmallCodility, HackerRank alternatives: TestGorilla, Thomas International
DeepSeek V4 FlashTestGorilla alternatives: Canditech, Codility, Criteria Corp, HackerRank
Qwen 3.7 FlashTestGorilla alternatives: HackerRank, PI Online, Spark Hire, Vervoe
Kimi K2TestGorilla alternatives: Codility, Criteria Corp, HackerRank, HireVue, Vervoe
GLM 4.7 FlashXTestGorilla alternatives: Criteria Corp, HireVue, Thomas International
MiniMax M2.5Prevue HR, TestGorilla alternatives: Codility, Criteria Corp, HackerRank, HireVue
GPT-6 LunaCriteria Corp alternatives: TestGorilla
Muse Glimmer 30BCodility, Thomas alternatives: HackerRank, HireVue, Weirdly

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
EmployTest leads by four points.
EmployTest4%#3 of 11
Harver0%#– of 11
The full small business standing →
Mid-marketThe figures above
EmployTest leads by two points.
EmployTest4%#4 of 12
Harver2%#7 of 12
The full mid-market standing →
Enterprise
Level: the same share of first choices.
EmployTest0%#– of 12
Harver0%#11 of 12
The full enterprise standing →

What the models said about EmployTest

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

“EmployTest offers the most financial flexibility if you only test a few candidates per year” Kimi K2 · budget prompt · first choice
“start with Toggl Hire's free plan or EmployTest for low-cost per-test pricing” Mistral Small · budget prompt · first choice
“If you particularly dislike subscription commitments, EmployTest's pay-per-test model is your best bet.” DeepSeek V4 Flash · budget prompt · alternative

What the models said about Harver

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

“heavy reliance on unvalidated or "black-box" AI/personality assessments (e.g., certain features in Harver, Paradox, or generic AI tools)” Grok 4.20 · negative prompt · soft negative
“Criteria Corp, Harver, and Plum bundle personality, cognitive, and behavioral assessments in one platform” Claude Haiku 4.5 · direct prompt · first choice
“include Criteria Corp, TestGorilla, Harver, and HireVue” DeepSeek V4 Flash · scale prompt · alternative
“Solid for high-volume or frontline hiring with good customer support” Grok 4.20 · direct prompt · alternative
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.