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Internal talent marketplace · November 2026 Edition

TalentGuard vs 365Talents

Zero of fourteen models named TalentGuard first on the direct prompt; one named 365Talents. TalentGuard was named by seven of the fourteen models and 365Talents by seven and TalentGuard carries 10 labels and 365Talents 16, so the shares are not directly comparable.

TalentGuard

accepted challenger

Named in three categories this edition.

365Talents

accepted challenger

Named in three categories this edition.

First-choice share11%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 13; printed, not drawn.
Labels1016A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, TalentGuard reading right to left. Rank and label count are printed, not drawn.Fuel50 was named alongside these two in eleven of the fourteen direct answers. Fuel50 vs TalentGuard · Fuel50 vs 365Talents · Engagedly vs TalentGuard

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 internal talent marketplace page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
TalentGuardFirst choices, of fourteen models365Talents
Direct01
Paraphrase01
Comparative00
Budget-constrained512 against 365Talents
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.

Across every category in the November 2026 Edition, TalentGuard and 365Talents were named in the same answer fifteen times, of the 49 answers naming TalentGuard and the 101 naming 365Talents. In those answers 365Talents took the first choice zero times and TalentGuard eight.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where TalentGuard and 365Talents 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
TalentGuard 365Talents first choice named as an alternative argued againstblank: not namedEach cell is one answer, TalentGuard on the left and 365Talents on the right.

The direct prompt

The plain question, one answer per model, grouped by where TalentGuard and 365Talents stood in it.

365Talents first, TalentGuard not the choice

1 of 14 modelsTalentGuard was named in the answer but not as the choice, or not at all.
Kimi K2365Talents alternatives: Engagedly, Fuel50

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.
GPT-5.4 miniFuel50 alternatives: 365Talents, Workday Talent Marketplace
Gemini 3.5 FlashNestor alternatives: Fuel50, HiBob, Lattice Grow / Talent, TalentGuard, Workday Talent Marketplace
Perplexity SonarEngagedly alternatives: 365Talents, Fuel50, Hitch Works, Workday Talent Marketplace
Mistral SmallEngagedly, Fuel50 alternatives: 365Talents, MentorcliQ
GLM 4.7 FlashXFuel50, GoFIGR alternatives: 365Talents, Workday Talent Optimization
Muse Glimmer 30BEngagedly alternatives: 365Talents, Fuel50, GoFIGR, HCM4ALL, MentorcliQ

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Grok 4.20Fuel50 alternatives: Eightfold AI, Engagedly, Gloat, Phenom, SAP SuccessFactors Opportunity Marketplace, Workday Talent Marketplace
DeepSeek V4 FlashGoFIGR alternatives: Engagedly
Llama 4 MaverickEngagedly
Qwen 3.7 FlashGoFIGR alternatives: Fuel50, ServiceNow Workforce Transformation, Workday Prism, Workday Talent Marketplace
MiniMax M2.5Engagedly alternatives: Cornerstone OnDemand, Fuel50, HCM4ALL, Workday Talent Marketplace
GPT-6 LunaFuel50 alternatives: Eightfold AI, Gloat, Workday Talent Marketplace

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
TalentGuard leads by fourteen points.
TalentGuard14%#1 of 16
365Talents0%#11 of 16
The full small business standing →
Mid-marketThe figures above
TalentGuard leads by four points.
TalentGuard11%#3 of 13
365Talents6%#4 of 13
The full mid-market standing →
Enterprise
TalentGuard leads by two points.
TalentGuard2%#– of 10
365Talents0%#8 of 10
The full enterprise standing →

What the models said about TalentGuard

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“TalentGuard appears to be the best choice due to its combination of affordability (starting at $7/user/month) and free trial option” Claude Haiku 4.5 · budget prompt · first choice
“For most companies with a limited budget, TalentGuard offers the best balance of affordability and functionality.” DeepSeek V4 Flash · budget prompt · first choice

What the models said about 365Talents

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“use quote-based pricing and are generally oriented toward larger organizations” Perplexity Sonar · budget prompt · soft negative
“their pricing is custom/quote-only and demo only in most comparison tables” 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.