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Candidate assessment · November 2026 Edition

CodeSignal vs Harver

Zero of fourteen models named CodeSignal first on the direct prompt; one named Harver. CodeSignal was named by eleven of the fourteen models and Harver by six and CodeSignal carries 14 labels and Harver 11, so the shares are not directly comparable.

CodeSignal

accepted challenger

Named in three categories this edition.

Harver

accepted challenger

Named in three categories this edition.

First-choice share2%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 12; printed, not drawn.
Labels1411A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, CodeSignal 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 CodeSignal · TestGorilla vs Harver · Criteria Corp vs CodeSignal

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.
CodeSignalFirst choices, of fourteen modelsHarver
Direct01
Paraphrase10
Comparative00
Budget-constrained001 against CodeSignal
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 CodeSignal 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
CodeSignal Harver first choice named as an alternative argued againstblank: not namedEach cell is one answer, CodeSignal on the left and Harver on the right.

The direct prompt

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

Harver first, CodeSignal not the choice

1 of 14 modelsCodeSignal 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

1 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

Neither was named

12 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
Llama 4 MaverickThomas International alternatives: Codility, EmployTest, HackerRank, Weirdly
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
Level: the same share of first choices.
CodeSignal0%#– of 11
Harver0%#– of 11
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
CodeSignal2%#6 of 12
Harver2%#7 of 12
The full mid-market standing →
Enterprise
CodeSignal leads by two points.
CodeSignal2%#9 of 12
Harver0%#11 of 12
The full enterprise standing →

What the models said about CodeSignal

No label in this category carried a quote.

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.