Talent intelligence · November 2026 Edition
SeekOut Recruit vs Gem
Eight of fourteen models named SeekOut Recruit first on the direct prompt; zero named Gem. SeekOut Recruit was named by fourteen of the fourteen models and Gem by ten and SeekOut Recruit carries 45 labels and Gem 15, so the shares are not directly comparable.
SeekOut Recruit
accepted challengerNamed in one category this edition.
Named in eight categories this edition.
First-choice share21%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate18%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#8A position in a field of 15; printed, not drawn.
Labels4515A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, SeekOut Recruit reading right to left. Rank and label count are printed, not drawn.SeekOut Recruit vs Lessie AI · SeekOut Recruit vs Pin · SeekOut Recruit vs Eightfold AI
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 talent intelligence page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SeekOut RecruitFirst choices, of fourteen modelsGem
Direct80
Paraphrase101 against SeekOut Recruit
Comparative00
Budget-constrained014 against SeekOut Recruit · 1 against Gem
Scale-constrained20
Negative003 against SeekOut Recruit
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 SeekOut Recruit and Gem stood in it.
| Model | DirectSR | ParaphraseSR | ComparativeSR | Budget-constrainedSR | Scale-constrainedSR | NegativeSR |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | ||||
| GPT-5.4 mini | SR | SR | ||||
| Gemini 3.5 Flash | SR | SR | SR | SR | ||
| Perplexity Sonar | SR | SR | SR | |||
| Grok 4.20 | SR | SR | SR | SR | SR | SR |
| Mistral Small | SR | SR | SR | SR | ||
| DeepSeek V4 Flash | SR | SR | SR | |||
| Llama 4 Maverick | SR | |||||
| Qwen 3.7 Flash | SR | SR | SR | SR | ||
| Kimi K2 | SR | SR | ||||
| GLM 4.7 FlashX | SR | SR | SR | |||
| MiniMax M2.5 | SR | SR | SR | |||
| GPT-6 Luna | SR | | ||||
| Muse Glimmer 30B | SR | SR | SR |
SR SeekOut Recruit GemSR first choiceSR named as an alternativeSR argued againstblank: not namedEach cell is one answer, SeekOut Recruit on the left and Gem on the right.
GemSR first choiceSR named as an alternativeSR argued againstblank: not namedEach cell is one answer, SeekOut Recruit on the left and Gem on the right.The direct prompt
The plain question, one answer per model, grouped by where SeekOut Recruit and Gem stood in it.
SeekOut Recruit first, Gem an alternative
8 of 14 modelsGem was named in the answer but not as the choice, or not at all.GPT-5.4 miniSeekOut Recruit alternatives: Eightfold AI, hireEZ
Mistral SmallEightfold AI, SeekOut Recruit alternatives: Sapia.ai, iCIMS Talent Cloud
DeepSeek V4 FlashSeekOut Recruit alternatives: Gem, hireEZ
Kimi K2Pin, SeekOut Recruit alternatives: Ashby, Greenhouse
GLM 4.7 FlashXSeekOut Recruit alternatives: Ceipal, Talent.ai
MiniMax M2.5Greenhouse, SeekOut Recruit alternatives: Eightfold AI, hireEZ
GPT-6 LunaSeekOut Recruit alternatives: Lightcast
Muse Glimmer 30BSeekOut Recruit alternatives: Eightfold AI, Lessie AI, hireEZ
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5Arya, Pin alternatives: 365Talents, Eightfold AI, Gem, Loxo, iCIMS Talent Cloud
Gemini 3.5 FlashFindem alternatives: Gem, Loxo, SeekOut Recruit
Perplexity SonarhireEZ alternatives: Gem, SeekOut Recruit
Grok 4.20Loxo alternatives: Eightfold AI, Gem, SeekOut Recruit
Qwen 3.7 FlashLessie AI, hireEZ alternatives: Gem, SeekOut Recruit
Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.Llama 4 Maverickno first choice
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
Mid-marketThe figures above
The order flips: SeekOut Recruit leads at mid-market.
SeekOut Recruit21%#1 of 15
Gem2%#8 of 15Enterprise
SeekOut Recruit leads by four points.
SeekOut Recruit4%#3 of 11
Gem0%#– of 11What the models said about SeekOut Recruit
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid enterprise-heavy options like Eightfold AI, SeekOut, Beamery” Grok 4.20 · budget prompt · hard negative
“Many talent intelligence tools (e.g., those from SeekOut, Beamery, Phenom, Gloat, Censia, Findem, Visier, or LinkedIn Talent Insights) aggregate data from public sources” Grok 4.20 · negative prompt · soft negative
“SeekOut has notable limitations, such as inconsistent contact data quality and some profiles lacking usable emails” Mistral Small · negative prompt · soft negative
“SeekOut: Excellent for sourcing intelligence, diversity, and market mapping. Strong external data + ATS integration. Good for recruiting-heavy needs; often praised for mid-market pricing and ease.” Grok 4.20 · scale prompt · first choice
“I'd lean SeekOut—because mid-market companies often need the strongest balance of candidate discovery, team usability, and practical recruiting workflows” GPT-5.4 mini · direct prompt · first choice
“1. SeekOut - *Best Overall Value* ... Start with SeekOut if you're primarily focused on sourcing and talent discovery” GLM 4.7 FlashX · direct prompt · first choice
What the models said about Gem
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Enterprise suites like Beamery, Eightfold, Phenom, Gem are described as stronger on workforce analytics but "cost far more."” Muse Glimmer 30B · budget prompt · soft negative
Also compared
SeekOut Recruit vs Lessie AISeekOut Recruit vs PinSeekOut Recruit vs Eightfold AISeekOut Recruit vs hireEZSeekOut Recruit vs LoxoSeekOut Recruit vs PhenomLessie AI vs GemPin vs GemEightfold AI vs GemhireEZ vs GemLoxo vs GemPhenom vs GemAll twenty-eight head-to-head pages and the full talent intelligence 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.