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Internal talent marketplace · October 2026 Edition

Fuel50 vs TalentGuard

Twelve of fourteen models named Fuel50 first on the direct prompt; zero named TalentGuard. Fuel50 was named by fourteen of the fourteen models and TalentGuard by eight and Fuel50 carries 41 labels and TalentGuard 17, so the shares are not directly comparable.

Fuel50

endorsed leader

Named in six categories this edition.

TalentGuard

accepted challenger

Named in three categories this edition.

First-choice share47%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate12%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#3A position in a field of 13; printed, not drawn.
Labels4117A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Fuel50 reading right to left. Rank and label count are printed, not drawn.Fuel50 vs Engagedly · Fuel50 vs 365Talents · Fuel50 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 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.
Fuel50First choices, of fourteen modelsTalentGuard
Direct120
Paraphrase80
Comparative10
Budget-constrained224 against Fuel50
Scale-constrained011 against Fuel50
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 October 2026 Edition, Fuel50 and TalentGuard were named in the same answer thirty-five times, of the 206 answers naming Fuel50 and the 63 naming TalentGuard. In those answers TalentGuard took the first choice eleven times and Fuel50 ten.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Fuel50 and TalentGuard stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Fuel50 TalentGuard first choice named as an alternative argued againstblank: not namedEach cell is one answer, Fuel50 on the left and TalentGuard on the right.

The direct prompt

The plain question, one answer per model, grouped by where Fuel50 and TalentGuard stood in it.

Fuel50 first, TalentGuard an alternative

12 of 14 modelsTalentGuard was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Eightfold AI, Fuel50
GPT-5.4 miniFuel50 alternatives: 365Talents, Workday Talent Marketplace
Perplexity SonarFuel50 alternatives: Engagedly
Grok 4.1 FastFuel50 alternatives: 365Talents, TalentGuard
Mistral SmallEngagedly, Fuel50
DeepSeek V4 FlashFuel50 alternatives: Cornerstone OnDemand, Engagedly, TalentGuard, Workday Talent Marketplace
Qwen 3.7 FlashFuel50 alternatives: Nestor
Kimi K2Fuel50 alternatives: 365Talents
GLM 4.7 FlashXFuel50 alternatives: 365Talents, Engagedly, Reejig
MiniMax M2.5Fuel50 alternatives: 365Talents, Engagedly, TalentGuard
GPT-6 LunaFuel50 alternatives: Gloat, Workday’s own Career Hub and Talent Marketplace
Muse Glimmer 30BFuel50, SkillPanel alternatives: Sprad, TalentGuard

Neither was the first choice, one was named

2 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashNestor alternatives: 365Talents, Fuel50, TalentGuard
Llama 4 MaverickSkima AI alternatives: Fuel50, Sprad

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 thirteen points.
TalentGuard18%#1 of 12
Fuel504%#4 of 12
The full small business standing →
Mid-marketThe figures above
The order flips: Fuel50 leads at mid-market.
Fuel5047%#1 of 13
TalentGuard6%#3 of 13
The full mid-market standing →
Enterprise
Fuel50 leads by twenty-two points.
Fuel5022%#2 of 12
TalentGuard0%#– of 12
The full enterprise standing →

What the models said about Fuel50

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 ones like Gloat, Cornerstone, or Fuel50—they're quote-based/custom” Grok 4.1 Fast · budget prompt · hard negative
“Steer clear of enterprise platforms (Gloat, Workday, Fuel50)” DeepSeek V4 Flash · budget prompt · hard negative
“What to Avoid: ... Fuel50” Kimi K2 · budget prompt · hard negative
“For mid-market companies specifically, Fuel50 and Eightfold tend to be the most commonly recommended options” Claude Haiku 4.5 · direct prompt · first choice
“Fuel50 is the best default recommendation for a mid-market B2B company looking for an internal talent marketplace” Perplexity Sonar · direct prompt · first choice
“Fuel50 and Engagedly are frequently highlighted as top choices for mid-market B2B companies” Mistral Small · direct prompt · first choice

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 - Offers comprehensive talent mobility with skills visibility... Good balance of features and affordability for small to mid-sized businesses.” MiniMax M2.5 · budget prompt · first choice
“the strongest fit in the results is TalentGuard because it is explicitly positioned as budget-conscious” Perplexity Sonar · budget prompt · first choice
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.