HackerRank vs TestGorilla
Six of twelve models named HackerRank first on the direct prompt; zero named TestGorilla. Both were named by all twelve models and HackerRank carries 57 labels and TestGorilla 31, so the shares are not directly comparable.
Named in four categories this edition.
Named in four categories this edition.
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
HackerRankFirst choices, of twelve modelsTestGorilla
Across every category in the September 2026 Edition, HackerRank and TestGorilla were named in the same answer 122 times, of the 233 answers naming HackerRank and the 238 naming TestGorilla. In those answers TestGorilla took the first choice thirty-five times and HackerRank twelve.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | | | |
HackerRank TestGorilla first choice named as an alternative argued againstblank: not namedEach cell is one answer, HackerRank on the left and TestGorilla on the right.The direct prompt
HackerRank first, TestGorilla not the choice
6 of 12 modelsTestGorilla was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 12 modelsThe answer made no first choice from these two in this category.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
TestGorilla21%#2 of 7HackerRank9%#5 of 7HackerRank28%#1 of 6TestGorilla5%#5 of 6HackerRank42%#1 of 6TestGorilla0%#6 of 6What the models said about HackerRank
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Users frequently complain about "overage fees." ... Googleable Questions: ... default assessments are often easily searchable online.” GLM 4.7 FlashX · negative prompt · hard negative
“buggy UI/UX ... High drop-off rates and "horrible experience" sentiments” Grok 4.1 Fast · negative prompt · hard negative
“Why we recommend avoiding HackerRank or Codility (for now)” Gemini 3.5 Flash · paraphrase prompt · hard negative
“Qualified (free) and HackerRank Starter ($99/mo) offer the best balance of cost, reliability, and candidate familiarity” DeepSeek V4 Flash · budget prompt · first choice
“Best for: End-to-end enterprise technical hiring. ... broadest platform and largest general hiring workflow” GPT-5.4 mini · comparative prompt · first choice
“the best *default* choice is usually HackerRank if your priority is technical hiring at scale” Perplexity Sonar · direct 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
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.