# HackerRank vs CodeSignal: which do AI models recommend for technical hiring assessm, September 2026

HR AI Recommendation Index, September 2026 Edition, Technical hiring assessments. Six of twelve models named HackerRank first on the direct prompt; two named CodeSignal. Page: https://hr-ai-index.com/talent/technical-hiring-assessments/hackerrank-vs-codesignal/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| HackerRank | 28% | #1 of 6 | 21% | 57 | 12 of 12 |
| CodeSignal | 10% | #4 of 6 | 10% | 41 | 12 of 12 |

## The direct prompt, model by model

- GPT-5.4 mini: hackerrank first (first choices: HackerRank) (alternatives: CodeSignal, CoderPad, Codility)
- Perplexity Sonar: hackerrank first (first choices: HackerRank) (alternatives: CodeSignal, CoderPad, Coderbyte, Goodfit)
- Grok 4.1 Fast: hackerrank first (first choices: HackerRank) (alternatives: CodeSignal, Coderbyte)
- Mistral Small: hackerrank first (first choices: HackerRank) (alternatives: Augment Code, Coderbyte)
- Qwen 3.7 Flash: hackerrank first (first choices: HackerRank) (alternatives: CodeSignal, TestDome, Vervoe)
- GLM 4.7 FlashX: hackerrank first (first choices: HackerRank) (alternatives: CodeSignal)
- DeepSeek V4 Flash: codesignal first (first choices: CodeSignal) (alternatives: Codility, HackerRank, TestGorilla)
- MiniMax M2.5: codesignal first (first choices: CodeSignal) (alternatives: Augment Code, HackerRank, TestGorilla)
- Gemini 3.5 Flash: neither first, one named (first choices: CoderPad) (alternatives: CodeSignal, HackerEarth, TestGorilla)
- Llama 4 Maverick: neither first, one named (alternatives: CodeSignal, CoderPad, Coderbyte, Goodfit, HackerRank)
- Kimi K2: neither first, one named (first choices: Codility) (alternatives: CodeSignal, Coderbyte, HackerRank, TestGorilla)
- Claude Haiku 4.5: neither named

## What the models said about HackerRank

- "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 CodeSignal

- "It punishes deliberate, methodical thinking... a poor score on one application can actively destroy your chances with other companies" (DeepSeek V4 Flash, negative prompt, hard negative)
- "CodeSignal's scoring algorithm incorporates "speed" heavily ... can unfairly penalize candidates who are careful but methodical." (GLM 4.7 FlashX, negative prompt, soft negative)
- "Expensive compared to alternatives ... Assessments have been reported as "flawed" with technical issues" (Kimi K2, negative prompt, soft negative)
- "(or CodeSignal if you like the "certified engineer" benchmark). Both integrate with most ATS platforms" (MiniMax M2.5, paraphrase prompt, first choice)
- "Best for: All-around use, standardized pre-screening at scale, live technical interviews" (DeepSeek V4 Flash, comparative prompt, first choice)
- "Popular ones like CoderPad or CodeSignal have better reps for collaborative/live coding." (Grok 4.1 Fast, negative prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.