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Recruiting CRM and sourcing · November 2026 Edition

LinkedIn Recruiter vs Fetcher

Three of fourteen models named LinkedIn Recruiter first on the direct prompt; two named Fetcher. LinkedIn Recruiter was named by fourteen of the fourteen models and Fetcher by eleven and LinkedIn Recruiter carries 30 labels and Fetcher 18, so the shares are not directly comparable.

LinkedIn Recruiter

accepted challenger

Named in six categories this edition.

Fetcher

accepted challenger

Named in two categories this edition.

First-choice share6%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate20%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#7A position in a field of 13; printed, not drawn.
Labels3018A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, LinkedIn Recruiter reading right to left. Rank and label count are printed, not drawn.hireEZ was named alongside these two in twelve of the fourteen direct answers. Gem vs LinkedIn Recruiter · Gem vs Fetcher · hireEZ vs LinkedIn Recruiter

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 Recruiting CRM and sourcing page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
LinkedIn RecruiterFirst choices, of fourteen modelsFetcher
Direct322 against LinkedIn Recruiter · 1 against Fetcher
Paraphrase00
Comparative40
Budget-constrained003 against LinkedIn Recruiter
Scale-constrained001 against LinkedIn Recruiter
Negative00
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 LinkedIn Recruiter and Fetcher stood in it.
ModelDirectFEParaphraseFEComparativeFEBudget-constrainedFEScale-constrainedFENegativeFE
Claude Haiku 4.5FE
GPT-5.4 mini
Gemini 3.5 FlashFEFE
Perplexity SonarFE
Grok 4.20FE
Mistral SmallFE
DeepSeek V4 FlashFE
Llama 4 MaverickFEFE
Qwen 3.7 FlashFE
Kimi K2
GLM 4.7 FlashXFE
MiniMax M2.5FE
GPT-6 Luna
Muse Glimmer 30BFEFE
LinkedIn RecruiterFE Fetcher first choice named as an alternative argued againstblank: not namedEach cell is one answer, LinkedIn Recruiter on the left and Fetcher on the right.

The direct prompt

The plain question, one answer per model, grouped by where LinkedIn Recruiter and Fetcher stood in it.

LinkedIn Recruiter first, Fetcher an alternative

3 of 14 modelsFetcher was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5LinkedIn Recruiter alternatives: Apollo.io, ZoomInfo
Gemini 3.5 FlashLinkedIn Recruiter alternatives: Fetcher, Findem, SeekOut, ZoomInfo Talent, hireEZ
GPT-6 LunaLinkedIn Recruiter alternatives: Gem, SeekOut

Fetcher first, LinkedIn Recruiter not the choice

2 of 14 modelsLinkedIn Recruiter was named in the answer but not as the choice, or not at all.
Llama 4 MaverickFetcher, Findem, Gem, hireEZ
GLM 4.7 FlashXFetcher, Gem alternatives: hireEZ

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniGem alternatives: LinkedIn Recruiter, Loxo, SeekOut, hireEZ
Mistral SmallGem, hireEZ alternatives: Fetcher, Findem
DeepSeek V4 FlashhireEZ alternatives: Fetcher, Gem, LinkedIn Recruiter, SeekOut
Qwen 3.7 FlashGem alternatives: ContactOut, Fetcher, Lusha, hireEZ
MiniMax M2.5Gem, SeekOut alternatives: Fetcher, Juicebox, hireEZ
Muse Glimmer 30BGem, hireEZ alternatives: Fetcher, Findem, Humanly, Manatal, TheHireHub.AI

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarhireEZ alternatives: Gem, Lever, SeekOut, Workable
Grok 4.20hireEZ alternatives: Findem, SeekOut
Kimi K2Gem alternatives: SeekOut, hireEZ

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
LinkedIn Recruiter leads by two points.
LinkedIn Recruiter4%#5 of 10
Fetcher2%#7 of 10
The full small business standing →
Mid-marketThe figures above
LinkedIn Recruiter leads by two points.
LinkedIn Recruiter6%#5 of 13
Fetcher4%#7 of 13
The full mid-market standing →
Enterprise
LinkedIn Recruiter leads by eleven points.
LinkedIn Recruiter11%#3 of 13
Fetcher0%#– of 13
The full enterprise standing →

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.

“LinkedIn doesn't publish a standard price, so compare a quote rather than assuming it's the cheapest” GPT-6 Luna · budget prompt · soft negative
“without the massive price tag of enterprise solutions like LinkedIn Recruiter ($8,000–$12,000/year)” Gemini 3.5 Flash · budget prompt · soft negative
“you might still consider LinkedIn Recruiter Lite (approx. $9k/year) despite the cost” Qwen 3.7 Flash · budget prompt · soft negative
“The gold standard for professional networking and direct outreach. Access to 1B+ profiles with advanced search, InMail messaging, and analytics.” Grok 4.20 · comparative prompt · first choice
“If you need broad corporate hiring: Start with LinkedIn Recruiter paired with Gem for automated email outreach.” Gemini 3.5 Flash · comparative prompt · first choice
“Core Channel: LinkedIn Recruiter (for direct messaging and broad talent search).” Gemini 3.5 Flash · direct prompt · first choice

What the models said about Fetcher

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

“note that it was reportedly retired in late 2026 per some sources—verify current status” Grok 4.20 · direct prompt · soft negative
“For most mid-market B2B companies, I recommend starting with Gem or Fetcher.” GLM 4.7 FlashX · direct prompt · first choice
“likely to be one of the following: Findem, Gem, hireEZ, or Fetcher” Llama 4 Maverick · direct prompt · first choice
“Fetcher, which takes the work out of sourcing entirely and is best for lean teams wanting delivered candidates” Llama 4 Maverick · budget 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.