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Talent intelligence · November 2026 Edition

Phenom vs Gem

Zero of fourteen models named Phenom first on the direct prompt; zero named Gem. Phenom was named by thirteen of the fourteen models and Gem by ten and Phenom carries 40 labels and Gem 15, so the shares are not directly comparable.

Phenom

criticized challenger

Named in ten categories this edition.

Gem

accepted challenger

Named in eight categories this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate40%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#7#8A position in a field of 15; printed, not drawn.
Labels4015A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Phenom reading right to left. Rank and label count are printed, not drawn.SeekOut Recruit was named alongside these two in twelve of the fourteen direct answers. SeekOut Recruit vs Phenom · SeekOut Recruit vs Gem · Lessie AI vs Phenom

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.
PhenomFirst choices, of fourteen modelsGem
Direct004 against Phenom
Paraphrase201 against Phenom
Comparative00
Budget-constrained015 against Phenom · 1 against Gem
Scale-constrained001 against Phenom
Negative005 against Phenom
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.

Across every category in the November 2026 Edition, Phenom and Gem were named in the same answer sixty-one times, of the 362 answers naming Phenom and the 202 naming Gem. In those answers Gem took the first choice nine times and Phenom five.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Phenom and Gem stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Phenom Gem first choice named as an alternative argued againstblank: not namedEach cell is one answer, Phenom on the left and Gem on the right.

The direct prompt

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

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.
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
DeepSeek V4 FlashSeekOut Recruit alternatives: Gem, hireEZ
Qwen 3.7 FlashLessie AI, hireEZ alternatives: Gem, SeekOut Recruit

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniSeekOut Recruit alternatives: Eightfold AI, hireEZ
Mistral SmallEightfold AI, SeekOut Recruit alternatives: Sapia.ai, iCIMS Talent Cloud
Llama 4 Maverickno first choice
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

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
Gem leads by nine points.
Gem10%#3 of 18
Phenom2%#12 of 18
The full small business standing →
Mid-marketThe figures above
The order flips: Phenom leads at mid-market.
Phenom4%#7 of 15
Gem2%#8 of 15
The full mid-market standing →
Enterprise
Phenom leads by two points.
Phenom2%#5 of 11
Gem0%#– of 11
The full enterprise standing →

What the models said about Phenom

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

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

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.