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Technical hiring assessments · September 2026 Edition

CoderPad vs TestGorilla

One of twelve models named CoderPad first on the direct prompt; zero named TestGorilla. Both were named by all twelve models and CoderPad carries 40 labels and TestGorilla 31, so the shares are not directly comparable.

CoderPad

accepted challenger

Named in four categories this edition.

TestGorilla

accepted challenger

Named in four categories this edition.

First-choice share21%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%16%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#5A position in a field of 6; printed, not drawn.
Labels4031A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, CoderPad reading right to left. Rank and label count are printed, not drawn.HackerRank was named alongside these two in ten of the twelve direct answers. HackerRank vs CoderPad · HackerRank vs TestGorilla · CoderPad vs Coderbyte

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 technical hiring assessments page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
CoderPadFirst choices, of twelve modelsTestGorilla
Direct10
Paraphrase40
Comparative10
Budget-constrained221 against TestGorilla
Scale-constrained10
Negative304 against TestGorilla
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, CoderPad and TestGorilla were named in the same answer fifty-three times, of the 129 answers naming CoderPad and the 238 naming TestGorilla. In those answers TestGorilla took the first choice eight times and CoderPad ten.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where CoderPad and TestGorilla stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
CoderPad TestGorilla first choice named as an alternative argued againstblank: not namedEach cell is one answer, CoderPad on the left and TestGorilla on the right.

The direct prompt

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

CoderPad first, TestGorilla an alternative

1 of 12 modelsTestGorilla was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashCoderPad alternatives: CodeSignal, HackerEarth, TestGorilla

Neither was the first choice, one was named

6 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniHackerRank alternatives: CodeSignal, CoderPad, Codility
Perplexity SonarHackerRank alternatives: CodeSignal, CoderPad, Coderbyte, Goodfit
DeepSeek V4 FlashCodeSignal alternatives: Codility, HackerRank, TestGorilla
Llama 4 Maverickno first choice alternatives: CodeSignal, CoderPad, Coderbyte, Goodfit, HackerRank
Kimi K2Codility alternatives: CodeSignal, Coderbyte, HackerRank, TestGorilla
MiniMax M2.5CodeSignal alternatives: Augment Code, HackerRank, TestGorilla

Neither was named

5 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Grok 4.1 FastHackerRank alternatives: CodeSignal, Coderbyte
Mistral SmallHackerRank alternatives: Augment Code, Coderbyte
Qwen 3.7 FlashHackerRank alternatives: CodeSignal, TestDome, Vervoe
GLM 4.7 FlashXHackerRank alternatives: CodeSignal

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
CoderPad leads by five points.
CoderPad26%#1 of 7
TestGorilla21%#2 of 7
The full small business standing →
Mid-marketThe figures above
CoderPad leads by fifteen points.
CoderPad21%#2 of 6
TestGorilla5%#5 of 6
The full mid-market standing →
Enterprise
CoderPad leads by nine points.
CoderPad9%#4 of 6
TestGorilla0%#6 of 6
The full enterprise standing →

What the models said about CoderPad

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

“Prioritize platforms that offer work-sample style assessments over pure algorithm tests (e.g., CoderPad, HackerRank Projects, Codility's newer formats)” MiniMax M2.5 · scale prompt · first choice
“1. CoderPad (Best for Real-World, AI-Native Collaborative Hiring) CoderPad is highly regarded for simulating what a developer actually does on the job.” Gemini 3.5 Flash · comparative prompt · first choice
“For ultra-tight budgets: Start with CoderPad's free plan ... CoderPad Starter ($80/month annual) - unlimited users” Kimi K2 · budget prompt · first choice

What the models said about TestGorilla

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

“Billing issues: Multiple reviews mention unethical business practices, with charges continuing after cancellation” MiniMax M2.5 · negative prompt · hard negative
“It has a reputation for being buggy and confusing... making it a poor measure of senior engineering ability” DeepSeek V4 Flash · negative prompt · hard negative
“Frequently called one of the "worst online assessment tools" due to poor usability, confusing interfaces” Grok 4.1 Fast · negative prompt · hard negative
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.