Recruitment marketing and career sites · October 2026 Edition
Workable vs Phenom
One of fourteen models named Workable first on the direct prompt; one named Phenom. Workable was named by twelve of the fourteen models and Phenom by thirteen and Workable carries 18 labels and Phenom 30, so the shares are not directly comparable.
Named in thirteen categories this edition.
Named in six categories this edition.
First-choice share7%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%37%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#8A position in a field of 17; printed, not drawn.
Labels1830A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Workable reading right to left. Rank and label count are printed, not drawn.Teamtailor was named alongside these two in twelve of the fourteen direct answers. Teamtailor vs Workable · Teamtailor vs Phenom · Zoho Recruit vs Workable
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 recruitment marketing and career sites page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
WorkableFirst choices, of fourteen modelsPhenom
Direct116 against Phenom
Paraphrase222 against Phenom
Comparative04
Budget-constrained001 against Phenom
Scale-constrained101 against Phenom
Negative001 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.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Workable and Phenom stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | ||||
| GPT-5.4 mini | | | ||||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | ||||
| Grok 4.1 Fast | | |||||
| 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 | | | | |
Workable Phenom first choice named as an alternative argued againstblank: not namedEach cell is one answer, Workable on the left and Phenom on the right.The direct prompt
The plain question, one answer per model, grouped by where Workable and Phenom stood in it.
Workable first, Phenom not the choice
1 of 14 modelsPhenom was named in the answer but not as the choice, or not at all.Muse Glimmer 30BJobvite, Workable alternatives: Teamtailor
Phenom first, Workable an alternative
1 of 14 modelsWorkable was named in the answer but not as the choice, or not at all.Perplexity SonarPhenom alternatives: Joveo, Teamtailor, Workable
Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Kimi K2Teamtailor alternatives: Greenhouse, Lever, Workable
Neither was named
11 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Greenhouse, SmartRecruiters alternatives: Jobilla, Teamtailor
GPT-5.4 miniJobvite alternatives: Appcast, Teamtailor
Gemini 3.5 FlashGem, Teamtailor alternatives: Greenhouse, Lever, Pinpoint
Grok 4.1 FastSmartRecruiters alternatives: Lever, Teamtailor
Mistral SmallGem alternatives: SmartRecruiters
DeepSeek V4 Flash100Hires, Teamtailor alternatives: Recruitee
Llama 4 Maverickno first choice
Qwen 3.7 Flash100Hires alternatives: Gem, SmartRecruiters, Teamtailor
GLM 4.7 FlashXTeamtailor alternatives: Ashby, Lever
MiniMax M2.5Teamtailor alternatives: Beamery, SmartRecruiters
GPT-6 LunaGem alternatives: Teamtailor
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
Workable leads by twelve points.
Workable12%#1 of 14Phenom0%#14 of 14Mid-marketThe figures above
Enterprise
The order flips: Phenom leads at enterprise.
Phenom35%#1 of 13Workable0%#– of 13What the models said about Workable
No label in this category carried a quote.
What the models said about Phenom
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“the best approach is to avoid high-end, enterprise-only "Recruitment Marketing Platforms" (RMPs) like Phenom, Beamery, or Symphony Talent” Gemini 3.5 Flash · budget prompt · hard negative
“Be cautious of platforms like Beamery, Avature, or Phenom People. ... built for the Fortune 500” Gemini 3.5 Flash · direct prompt · hard negative
“Phenom is a massive, AI-powered "Talent Experience Management" (TXM) platform. It is best known for creating highly personalized, consumer-grade front-end career sites.” Gemini 3.5 Flash · comparative prompt · first choice
“I recommend Phenom or MokaHR for a mid-sized B2B company seeking a powerful, AI-driven career site builder” Mistral Small · paraphrase prompt · first choice
“1. Phenom or Symphony Talent - These are among the top-ranked branded careers site builders for 2026” Claude Haiku 4.5 · paraphrase prompt · first choice
Also compared
Teamtailor vs WorkableTeamtailor vs PhenomZoho Recruit vs WorkableZoho Recruit vs PhenomWorkable vs TalentLyftWorkable vs GemWorkable vs RecruiteeWorkable vs JobviteTalentLyft vs PhenomGem vs PhenomRecruitee vs PhenomJobvite vs PhenomAll twenty-eight head-to-head pages and the full recruitment marketing 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.