hireEZ vs LinkedIn Recruiter
Two of twelve models named hireEZ first on the direct prompt; two named LinkedIn Recruiter. Both were named by all twelve models and hireEZ carries 30 labels and LinkedIn Recruiter 26, so the shares are not directly comparable.
Named in six categories this edition.
Named in three 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 Recruiting CRM and sourcing page.
By framing
hireEZFirst choices, of twelve modelsLinkedIn Recruiter
Across every category in the September 2026 Edition, hireEZ and LinkedIn Recruiter were named in the same answer forty-two times, of the 161 answers naming hireEZ and the 106 naming LinkedIn Recruiter. In those answers LinkedIn Recruiter took the first choice five times and hireEZ five.
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 | | |
hireEZ LinkedIn Recruiter first choice named as an alternative argued againstblank: not namedEach cell is one answer, hireEZ on the left and LinkedIn Recruiter on the right.The direct prompt
hireEZ first, LinkedIn Recruiter an alternative
2 of 12 modelsLinkedIn Recruiter was named in the answer but not as the choice, or not at all.LinkedIn Recruiter first, hireEZ not the choice
2 of 12 modelshireEZ was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 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
LinkedIn Recruiter4%#6 of 13hireEZ0%#13 of 13hireEZ5%#6 of 11LinkedIn Recruiter5%#7 of 11LinkedIn Recruiter12%#3 of 6hireEZ5%#6 of 6What the models said about hireEZ
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“stronger for sourcing quality, but it's generally more of a premium option and pricing is often quote-based” GPT-5.4 mini · budget prompt · soft negative
“For pipeline building and automated outreach, Gem and HireEZ are highly effective” Claude Haiku 4.5 · direct prompt · first choice
What the models said about LinkedIn Recruiter
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Declining Boolean search tools (e.g., older LinkedIn Recruiter features): Reduced accuracy in regulated industries, leading to missed qualified candidates.” Grok 4.1 Fast · negative prompt · soft negative
“A market leader with advanced search... Best for general use but can be expensive, especially for larger teams.” Mistral Small · comparative prompt · soft negative
“remains the go‑to for LinkedIn‑only sourcing, but it's expensive and limited to one network” GLM 4.7 FlashX · comparative prompt · soft negative
“If you want the largest mainstream professional pool, start with LinkedIn Recruiter” GPT-5.4 mini · comparative prompt · first choice
“For many B2B companies, LinkedIn remains the gold standard due to its network effect.” Qwen 3.7 Flash · direct prompt · first choice
“the best candidate sourcing tool is usually LinkedIn Recruiter” GPT-5.4 mini · direct prompt · first choice
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.