Eight of fourteen models named SeekOut Recruit first on the direct prompt; zero named Phenom. SeekOut Recruit was named by fourteen of the fourteen models and Phenom by thirteen and SeekOut Recruit carries 45 labels and Phenom 40, so the shares are not directly comparable.
Named in one category this edition.
Named in ten categories this edition.
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.
Across every category in the November 2026 Edition, SeekOut Recruit and Phenom were named in the same answer seventy-three times, of the 130 answers naming SeekOut Recruit and the 362 naming Phenom. In those answers Phenom took the first choice two times and SeekOut Recruit eleven.
| 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 |
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.
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
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“Why to Avoid: Despite its popularity among large enterprises, implementation is notoriously difficult.” Qwen 3.7 Flash · negative prompt · hard negative
“Phenom is often grouped with platforms to avoid due to negative user experiences and limitations” Mistral Small · negative prompt · hard negative
“Median contract ~$98K/year; full talent experience platform may be overkill” Kimi K2 · direct prompt · hard negative
“My default recommendation: Phenom—if you want one platform to connect external recruiting with internal mobility.” GPT-6 Luna · paraphrase 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.