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Index › HR › Talent acquisition › Recruiting CRM › Lever vs Fetcher
Recruiting CRM and sourcing · November 2026 Edition

Lever vs Fetcher

Zero of fourteen models named Lever first on the direct prompt; two named Fetcher. Lever was named by fourteen of the fourteen models and Fetcher by eleven and Lever carries 21 labels and Fetcher 18, so the shares are not directly comparable.

Lever

accepted challenger

Named in twelve categories this edition.

Fetcher

accepted challenger

Named in two categories this edition.

First-choice share8%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 13; printed, not drawn.
Labels2118A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Lever 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 Lever · Gem vs Fetcher · hireEZ vs Lever

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.
LeverFirst choices, of fourteen modelsFetcher
Direct021 against Fetcher
Paraphrase40
Comparative00
Budget-constrained00
Scale-constrained00
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 Lever 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
LeverFE Fetcher first choice named as an alternative argued againstblank: not namedEach cell is one answer, Lever on the left and Fetcher on the right.

The direct prompt

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

Fetcher first, Lever not the choice

2 of 14 modelsLever 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

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashLinkedIn Recruiter alternatives: Fetcher, Findem, SeekOut, ZoomInfo Talent, hireEZ
Perplexity SonarhireEZ alternatives: Gem, Lever, SeekOut, Workable
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

5 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5LinkedIn Recruiter alternatives: Apollo.io, ZoomInfo
GPT-5.4 miniGem alternatives: LinkedIn Recruiter, Loxo, SeekOut, hireEZ
Grok 4.20hireEZ alternatives: Findem, SeekOut
Kimi K2Gem alternatives: SeekOut, hireEZ
GPT-6 LunaLinkedIn Recruiter alternatives: Gem, SeekOut

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
Fetcher leads by two points.
Fetcher2%#7 of 10
Lever0%#– of 10
The full small business standing →
Mid-marketThe figures above
The order flips: Lever leads at mid-market.
Lever8%#4 of 13
Fetcher4%#7 of 13
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Lever0%#– of 13
Fetcher0%#– of 13
The full enterprise standing →

What the models said about Lever

No label in this category carried a quote.

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
Gem vs LeverGem vs FetcherhireEZ vs LeverhireEZ vs FetcherManatal vs LeverManatal vs FetcherLever vs LinkedIn RecruiterLever vs AshbyLever vs Zoho RecruitLinkedIn Recruiter vs FetcherAshby vs FetcherFetcher vs Zoho RecruitAll twenty-eight head-to-head pages and the full Recruiting CRM standing

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.